Chip heat dissipation structure and method for improving photoelectric conversion efficiency of chip

The invention belongs to the technical field of semiconductor laser chip heat dissipation, and particularly relates to a chip heat dissipation structure and a method for improving the photoelectric conversion efficiency of a chip. According to the chip heat dissipation structure, ions are injected into a precursor injection damage zone of an epitaxial wafer device layer, the device layer is transferred to a high-thermal-conductivity substrate material by combining a surface activation bonding technology, and lattice defects of a bonding interface are repaired by combining thermal annealing and femtosecond laser irradiation. The chip heat dissipation structure prepared by the invention has the advantages of high heat dissipation efficiency, simple preparation process and suitability for large-scale industrial production.

Orthogonal wavelet blind equalization method based on immune clone particle swarm optimization

The invention discloses an orthogonal wavelet blind equalization method based on immune clone particle swarm optimization. The method comprises the steps of: by regarding a particle swarm as an immune system, randomly initializing particles in a search space, namely, initializing the speed and the positions of antibodies, wherein the position vectors of the particles are taken as the weight vectors of an equalizer and the number of the weight vectors is taken as the scale of the particles; randomly generating an initial population, wherein the position vector with a maximal fitness value (that is optimal solution) is used as an antigen, the particles are used as the antibodies, the affinity degree is used for presenting the approaching degree of the antibodies and the antigen, and a fitness degree function of the particle swarm optimization is selected as the affinity degree of the antibodies; carrying out immune clone operation on the antibodies with higher fitness degree through iteration ...

Orthogonal wavelet transformation super-exponential iteration (SEI) blind equalization algorithm based on ant colony optimization

The invention discloses an orthogonal wavelet transformation super-exponential iteration (SEI) blind equalization method based on ant colony optimization. The method utilizes ant colony optimization to search the optimal weight vector as an initial weight vector value inputted by an equalizer so as to avoid local convergence of the algorithm. The method utilizes a positive feedback mechanism to increase convergence rate, utilizes the whitening action of the super-exponential iteration (SEI) method on data, utilizes orthogonal wavelet transformation to perform decorrelation on signals and fully utilizes the global convergence of ant colony optimization. Underwater acoustic channel simulation results show that compared with the orthogonal wavelet transformation super-exponential iteration constant modulus algorithm (WT-SEI-CMA), the method has higher convergence rate and smaller state error, and an equalized eye pattern is clearer and compacter. Thus, the method has certain practical valve ...

Card case of convenient access

The utility model discloses a card case of convenient access, its characterized in that, be equipped with holding tank, holding tank below the base, pop out device and dead lever. The utility model discloses the when used drives an axle bed piece downstream of popping out the mechanism through pressing the button, receives the restriction of dead lever, cuts the fork telescopic link and takes place deformation, extends in vertical direction, and is ejecting with the card that corresponds, the user loosens the button, and under the spring action, the bracket falls after rise promptly, when keeping, with the card directly place in a memory cell can, novel structure, convenient to use.

Sparse tracking method on basis of gradient texture features

The invention provides a sparse tracking method. Gradient texture features and affine transformation parameters of targets are jointly used for building appearance models of the targets. The sparse tracking method includes steps of creating initial dictionaries; extracting candidate particles; creating the gradient texture features; extracting gradient texture features of dictionary templates; extracting gradient texture features of candidate samples; linearly expressing the candidate samples by all templates in the dictionaries; solving sparse coefficients; creating reconstruction errors. The sparse tracking method on the basis of the gradient texture features has the advantages that the problem of change of the appearance of targets due to rotation, scale and illumination change and the like can be effectively solved by the aid of the gradient texture features; challenge due to scale variation or view angle variation can be effectively handled by means of affine transformation; the templates ...

Group delay effect and non-linear constraint based satellite channel modeling method

The invention relates to a satellite channel modeling method, particularly discloses a group delay effect and non-linear constraint based satellite channel modeling method which organically combines non-linear and group delay non-linear effects of a high-power amplifier, and solves the problem that channel models in the prior art have low simulation tracking performances of real satellite channels. A satellite channel is innovatively considered to be composed of four parts of a linear channel, a non-linear channel, a group delay channel 1 and a group delay channel 2; each part is approached by a linear part and a no-linear part of a Wiener model respectively, and when the approach process is converged, features of the Wiener model are retained; when the approach process is not converged, a control function is defined as a constraint function of input and output of the non-linear channel for replacing a non-linear function of the Wiener model so as to control convergence of the approach ...

Combination optimization self-adaptive frequency domain blind equalization method and system

The invention discloses a combination optimization self-adaptive frequency domain blind equalization method and a system for achieving the method. Through combination of two frequency domain equalizers of two different types, automatic switching of two work modes can be achieved without error threshold selection; in the frequency domain blind equalization work mode, when the equalization beginning stage or channels suddenly change, intersymbol interference is eliminated; when the frequency domain blind equalization work mode obtains steady-state mean square error which is low enough, a frequency domain judging guiding mode is switched to. Combination output is obtained by combining the output of the two equalizers through combination parameters, the combination output is used for defining a time domain cost function of the whole combination optimization self-adaptive frequency domain blind equalization system to adjust the combination parameters; judging output of the combination output ...

Wavelet constant modulus blind equalization method in MIMO (Multiple Input Multiple Output) system

The invention discloses a wavelet constant modulus blind equalization method in a MIMO (Multiple Input Multiple Output) system from the aspect of reducing?inter channel?and inter signal?correlation, so as to overcome defects that the traditional constant modulus blind equalization method in the MIMO system is weak in inter channel interference inhibition ability, slow in the convergence rate and large in steady-state errors. According to the method, singular value decomposition is used for reducing the correlation of channel output signals; an orthogonal wavelet base function is used for carrying out orthogonal wavelet transformation on MIMO channel output signals and autocorrelation of input signals of a blind equalizer is reduced; on the basis of fully considering the inter channel correlation, a cost function of MIMO system constant modulus blind equalization algorithm is redefined, and cross-correlation of output signals of the blind equalizer is reduced; and a variable step size function ...

Wavelet blind equalization method for fusing spline function Renyi entropy and time diversity

The invention discloses a wavelet blind equalization method for fusing a spline function Renyi entropy and a time diversity. The method comprises the following steps: passing transmission signals a(k) to through four channels c(k) so as to respectively obtain four outputs x1(k); adopting four channel noises n1(k) and x1(k) to obtain four channel output signals y1(k); obtaining the input R1(k) of four equalizers f1(k) by virtue of passing the four y1(k) respectively through a switch k1 and four orthogonal wavelet transducers (WTs); obtaining the summation signals z1(k) of the four equalizer outputs through the f1(k); similarly, obtaining four output vectors x1(k) by virtue of passing the a(k) respectively through the time interval Tc and the other four channels c(k); adopting the four channel noises n2(k) and x2(k) to obtain four channel output signals y2(k); obtaining the input R2(k) of the four equalizers f2(k) by virtue of passing the four y2(k) through the switch k1 and the four WTs; ...

Rapidly-convergent immune-clone-based orthogonal wavelet transform constant modulus blind equalization algorithm

The invention discloses a rapidly-convergent immune-clone-based orthogonal wavelet transform constant modulus blind equalization algorithm, which is characterized by comprising the following steps of: initializing a population; calculating an affinity value; performing clonal selection; implementing a king-crossover method; performing high frequency variation; calculating the affinity value; performing selection; judging whether to perform termination or not; and selecting an optimal weight vector individual. In the invention, an immune clonal selection algorithm is introduced into an orthogonal wavelet transform based constant modulus blind equalization algorithm (WT-CMA), the characteristics of multi-modal function optimization of a clonal selection method are utilized, weight vectors of an equalizer serve as antibodies, and the autocorrelation of signals is reduced by adopting orthogonal wavelet transform. Compared with the WT-CMA, the algorithm provided by the invention is high in the ...

Orthogonal wavelet super-exponential iteration blind equalization method based on self-adaptive immune clone

The invention discloses an orthogonal wavelet super-exponential iteration blind equalization method based on self-adaptive immune clone. The orthogonal wavelet super-exponential iteration blind equalization method includes the steps as follows: population initialization, calculation of an affinity value, clonal selection, high frequency variation, calculation of an affinity value, selection, judgment of whether stopping is performed, and selection of an optimum weight vector individual. The multimodal optimizing characteristic of a self-adaptive immune clone selection algorithm is utilized in the method, the weight vector of an equalizer serves as an antibody, the autocorrelation of signals is lowered by adopting orthogonal wavelet transformation, and whitening is conducted on input data of the equalizer by utilizing a super-exponential iteration (SEI) method. The result of the embodiment of the invention shows that compared with an orthogonal wavelet super-exponential iteration (WTSEI) ...

Intelligent acupotomy treatment auxiliary system based on CMOS image chip

The invention discloses an intelligent needle-knife treatment auxiliary system based on a CMOS image chip, the system comprises an image acquisition device, a support structure, a control center and a server, the image acquisition device is fixed on the support structure, a part to be subjected to a needle-knife operation is arranged in an image sampling area of the image acquisition device, and the control center is connected with the server. The image acquisition device is in communication connection with the control center, the control center is in communication connection with the server, and the server is in network connection with the cloud. Compared with the prior art, based on a human body three-dimensional model and a modern medicine hybrid network, the intelligent needle-knife auxiliary treatment system is utilized to ensure the flexibility and reliability of a needle-knife operation; meanwhile, based on local and remote databases, the feasibility and safety of the needle-knife ...

SCM (single chip microcomputer) based ultrasonic rainfall measurement device

The invention provides an SCM ( single chip microcomputer) based ultrasonic rainfall measurement device which comprises an SCM, a water inlet tube and a measuring tube, wherein the water inlet tube comprises a water inlet, a filter screen and a water inlet valve; the measuring tube adopts a double-tube structure, and the bottom of the double-tube structure is provided with a communication opening; the left tube of the measuring tube is connected with the water inlet tube, an ultrasonic probe and a temperature sensor are hermetically arranged above the right tube of the measuring tube, and a vent hole is arranged above the wall of the right tube of the measuring tube; and the ultrasonic probe and the temperature sensor are connected with the SCM. The SCM based ultrasonic rainfall measurement device provided by the invention is high in measurement accuracy and low in implementation cost; and by using the SCM based ultrasonic rainfall measurement device, the automatic and accurate rainfall ...

Hybrid wavelet neural network blind equalization method controlled by fuzzy neutral network

The invention discloses a hybrid wavelet neural network blind equalization method controlled by a fuzzy neutral network, and the method comprises the following steps: a. emission signals x (n) go through a pulse response channel, thus obtaining channel output vectors b (n); b. input sequences of a blind equalizer is obtained by adopting channel noise N (n) and the channel output vectors b (n) in Step a; and c. the input sequences y (n) of the blind equalizer in Step b go through an improved hybrid wavelet neural network sequentially, thus obtaining output signals, then iteration steps of a shift factor and a scale factor in a neuron wavelet function in the improved hybrid wavelet neural network are regulated by utilizing the fuzzy neural network (FNN), and a mean-square error E (n)=MSE (n) and the deviation of the mean-square error delta E (n) =MSE (n)-MSE (n-1) serve as input of a controller of the fuzzy neural network. The system has high flexibility and can avoid getting into dilemmas ...

Ultrasonic rainfall measuring device based on single chip microcomputer

The utility model provides a ultrasonic rainfall measuring device based on a single chip microcomputer; the ultrasonic rainfall measuring device comprises a single chip microcomputer, a water intake tube and a measuring tube; the water intake tube comprises a water inlet, a filter screen and a water inlet valve; the structure of the measuring tube is a dual-tube body, the bottom of which is connected with a connecting port; the left tube of the measuring tube is connected with the water intake tube; an ultrasonic probe and a temperature sensor are enclosed and installed above the right tube of the measuring tube; a vent hole is reserved above the right tube wall; the ultrasonic probe and the temperature sensor are connected with the single chip microcomputer. The ultrasonic rainfall measuring device disclosed by utility model has high measurement precision and low cost; and the rainfall under the conditions of any rainfall intensities can be automatically and accurately measured.

Multi-wavelet feedback blind equalization method for nonlinear satellite channel

The invention discloses a multi-wavelet feedback blind equalization method for a nonlinear satellite channel. According to the characteristic of the satellite channel nonlinearity, the nonlinear satellite channel receives signals outputted by a filter, multi-wavelet transform is conducted on the signals, and then obtained signals are inputted in a Wiener balancer; in this way, the linear module structure and the nonlinear module structure of the Wiener balancer are established, and the satellite channel nonlinearity is compensated for through the nonlinear module structure of the Wiener balancer. Compared with a method adopting a Volterra model balancer, the method has the advantages that influences of the nonlinear satellite channel on communication quality are effectively eliminated, the convergence rate is high, the mean square error is small, and satellite communication quality is effectively improved.

Medical cell edge detection method based on morphology and ant colony algorithm

The invention discloses a medical cell edge detection method based on morphology and ant colony algorithm, comprising the following steps: an initialization, a construction process, an updating process and a judgment process. The method of the invention can effectively detect complete contour under the condition of maintaining the cell sizes, and remove noise points.

Improved affine combination adaptive filtering method

The invention provides an improved affine combination adaptive filtering method which is realized based on an affine combination adaptive filtering system. The affine combination adaptive filtering system is composed of a known expectation filter and a combination adaptive filter, wherein the combination adaptive filter comprises two subfilters. According to the method, the known expectation filter generates expectation signals of the subfilters and the combination adaptive filter, output signals of the two subfilters are combined through combination parameters to obtain an output signal of the whole combination adaptive filter, and the operation of the two subfilters is controlled through the combination parameters; the weight vectors of the two subfilters are updated with the minimum mean square error method, and the combination parameters are updated through the output signals of the two subfilters; real-time track enables the subfilters to be high in performance, high in convergence ...

Orthogonal wavelet transform constant modulus blind equalization algorithm based on optimization of DAN genetic algorithm

The invention discloses an orthogonal wavelet transform constant modulus blind equalization algorithm based on optimization of the DAN genetic algorithm (DNA-GA-WTCMA). According to the algorithm, the DNA genetic algorithm is combined with the WTCMA and the advantages of the WT-CMA and the advantages of the DNA genetic algorithm are thoroughly utilized. According to the orthogonal wavelet transform constant modulus blind equalization algorithm, a weight vector of the blind equalization algorithm is shown according to a coding method based on a DNA nucleotide chain and interlace operation and mutation operation are conducted on the coded DNA chain to find an optimal individual in a DAN group, the decoded optimal individual serves as an optimal initial weight vector of a blind equalization device, and the shortages that the WTCMA is low in convergence rate, large in mean square error and prone to getting into local minimum are overcome. Compared with the WTCMA and the GA-WTCMA, the DNA-GA-WTCMA ...

Frequency-domain small wave blind equalization method based on united combining space-time diversity

The invention discloses a frequency-domain small wave blind equalization method based on united combining space-time diversity, comprising the following steps: firstly, realizing a single channel frequency-domain small wave blind equalization method (FWTCMA) by utilizing an FFT technique and an overlap retaining method; and secondly, constructing a united combining space-time diversity system model, wherein the united combining space-time diversity system model is characterized in that each branch path adopts different space diversity modules on the basis of time diversity; the output of combined space diversity modules is used as the input of a time diversity combiner; and a signal combined by the time diversity combiner is used as the input of a whole system. The frequency-domain small wave blind equalization method has high convergence speed, small steady state error and low computing complexity.

Frequency-domain blind equalization method (T/2FF-CMA) based on T/2 fraction space

The invention discloses a frequency-domain blind equalization method (T/2FF-CMA) based on T/2 fraction space, which aims at the shortages of the large steady state error and the low convergence speed of a baud spaced blind equalization method, avoids frequency spectrum aliasing due to sampling lacking by a fraction spaced blind equalizer so as to effectively reduce the steady state error of the blind equalizer, and realizes the frequency-domain blind equalization method (T/2FF-CMA) by a fast Fourier transform technique (FFT) and an overlay retaining method so as to improve the convergence property of the blind equalizer and reduce the computing complexity. The frequency-domain blind equalization method (T/2 FF-CMA) has small steady state error, high convergence speed and low computing complexity; and in addition, a water sound channel embodiment shows that the frequency-domain blind equalization method (T/2FF-CMA) has superior property compared with a baud spaced time-domain blind equalization ...

Bayesian estimation sparse representation face recognition method based on dictionary reconstruction

The invention provides a Bayesian estimation sparse representation face recognition method based on dictionary reconstruction, and belongs to the technical field of image recognition. The method is used for solving the problems that when an existing recognition method is used for recognizing an image of a face in disguise, robustness is not good, and the recognition rate is low. The method comprises the following steps that a dictionary reconstruction method is used, and after gray threshold conversion and smoothing processing are carried out on a test face image, the original test image and a processed test image are fused to obtain a new test image; the Bayesian estimation sparse representation recognition method is used for carrying out classification and recognition on the original test image. According to the Bayesian estimation sparse representation face recognition method based on dictionary reconstruction, the original image and noise can be effectively separated, the high recognition ...

Method for building meteorological satellite channel probability statistic characteristic simulation models

The invention provides a method for building meteorological satellite channel probability statistic characteristic simulation models, comprising the following steps of: 1) calculating meteorological satellite sending signals; 2) deducing envelope probability density distributions of corresponding receiving signals according to the situation that the meteorological satellite sending signals and receiving signals arriving in a ground receiving site are different in components because the meteorological satellite sending signals are subjected to a multipath effect, a scattering effect, a shadow shielding effect and the like in different weather conditions, , and building corresponding simulation models according to signal expression forms received by a meteorological satellite ground receiving system in different weather conditions. The simulation models built in the invention are clear in physical meaning, are easy to realize, and can be applied to the simulation of a meteorological satellite ...

Sound source positioning method for seven-element microphone array

The invention discloses a sound source positioning method for a seven-element microphone array. The method comprises the steps that a seven-element microphone array model and an indoor sound field model are built; the microphone array is utilized for receiving indoor sound source voice signals, and collection, filtering, windowing, spectral subtraction and cepstrum treatment are carried out on the received voice signals; phase conversion is utilized for weighting the GCC-PHAT to obtain time delay among microphones; a three-dimensional space positioning method and a coordinate rotation digital computer method are applied to sound source position determination. According to the sound source positioning method, the sound source position can be accurately determined under the indoor environment where reverberation, noise and other interference signals exist, the real-time performance is high, the accuracy is high, and the sound source positioning method is widely applied in the field of voice ...

Fractionally spaced decision feedback Rayleigh Renyi entropy wavelet blind equalization method

The invention discloses a fractionally spaced decision feedback Rayleigh Renyi entropy wavelet blind equalization method, which comprises the following steps of: performing T/4 fractional spacing on the pth sub-channel on a transmitted signal sequence a(k) taking the symbol length T as a period to obtain the pth feedforward filter input sequence y<(p)>(k); performing orthogonal wavelet transform on the feedforward filter input sequence y<(p)>(k) to obtain an output signal R<(p)>(k) of a wavelet transformer; transmitting the wavelet transformed output signal R<(p)>(k) to the pth sub-equalizer to obtain the output signal z<(p)>(k) of the pth sub-equalizer, and adding and combining all output signals to obtain the output signal z(k); adding the output signal z(k) of the equalizers and the output signal zd(k) of a feedback filter to obtain a decider input signal g(k); and causing the decider input signal g(k) to pass through a decider to obtain the estimate hat{a(k)} of the transmitted signal ...

Frequency-domain small wave blind equalization method based on united combining space-time diversity

The invention discloses a frequency-domain small wave blind equalization method based on united combining space-time diversity, comprising the following steps: firstly, realizing a single channel frequency-domain small wave blind equalization method (FWTCMA) by utilizing an FFT technique and an overlap retaining method; and secondly, constructing a united combining space-time diversity system model, wherein the united combining space-time diversity system model is characterized in that each branch path adopts different space diversity modules on the basis of time diversity; the output of combined space diversity modules is used as the input of a time diversity combiner; and a signal combined by the time diversity combiner is used as the input of a whole system. The frequency-domain small wave blind equalization method has high convergence speed, small steady state error and low computing complexity.

Simulated rain field image generation method and system

The invention discloses a simulated rain field image generation method and system, and the method comprises the following steps: S1, obtaining a rain image data set, and carrying out the preprocessing of the rain image data set, and obtaining a preprocessed image; s2, performing normalization processing on the preprocessed image to obtain a normalized sample, and dividing the normalized sample into a training set image and a test set image; s3, constructing a simulated rain field generation network; s4, training the simulated rain field generation network by using the training set image, and improving the training ability by using a spectrum normalization and self-attention mechanism for a discriminator; s5, obtaining a trained simulated rain field generation network through a large amount of training and optimization hyper-parameters; and inputting a to-be-processed rain image into the trained simulated rain field generation network to generate a simulated rain field image. Through the ...

T/2 fraction spaced blind equalization method (T/2-FSE-WNN) introducing small wave neural network

The invention discloses a T/2 fraction spaced blind equalization method (T/2-FSE-WNN) introducing a small wave neural network. In the method, the small wave neural network is merged into the T/12 fraction spaced blind equalization method by utilizing higher approaching capability of the small wave neural network and the advantage that the fraction space has over sampling for a blind equalizer receiving signal on the basis of analyzing the small wave neural network and the fraction space theory. Compared with a T/2 fraction spaced feed forward neural network blind equalization method (T/2-FSE-FNN) and a small wave neural network blind equalization method (WNN), the T/2 fraction spaced blind equalization method (T/2-FSE-WNN) has higher convergence speed, smaller steady state error and mean square root error and carrier wave recovery property, and a water sound channel simulation result ventilates the effectiveness of the T/2 fraction spaced blind equalization method (T/2-FSE-WNN).

Blind source separation method based on improved artificial bee colony algorithm

The invention discloses a blind source separation method based on an improved artificial bee colony algorithm. The method includes the following steps that an observation signal X(k)=[x[1](k), x[2](k),..., x[M](k)] is obtained by a source signal S(k)=[s[1](k), s[2](k),..., s[M](k)] through a nonsingular hybrid matrix A; the obtained observation signal X (k) is sent to a preprocessing filter, and an output signal Z(k) of the preprocessing filter is obtained; the output signal Z(k) of the preprocessing filter is sent to a separation matrix W(k), and a separation signal Y(k) is obtained; an initial optimized separation matrix Wopt (0) of the W(k) is obtained through the improved artificial colony algorithm; after the initial optimized separation matrix Wopt (0) of the W(k) is obtained, the W(k) is updated. According to the method, the improved artificial bee colony algorithm is adopted for optimizing the blind source separation method NGA based on natural gradient so that the initial ...

Blind equalization method for wavelet neural network based on space diversity

The invention discloses a blind equalization method for a wavelet neural network based on space diversity. On the basis of analysis of a space diversity technology and the equalization performance of a wavelet neural network, the method reduces the influence of fading by utilizing the space diversity and overcomes intersymobl interferences by using the stronger approximation capacity of a blind equalizer of the wavelet neural network. The invention overcomes the intersymobl interferences caused by the multipath propagation and the fading characteristic of a channel at a receiving end, improves the communication quality and has high convergence speed and small mean square error. The effectiveness of the method is verified by an acoustic channel simulation result. The method can effectivelyrealize the separation of signals and noise and the real-time restoration of the signals.

Face image local enhancement method based on multi-feature fusion

The invention discloses a face image local enhancement method based on multi-feature fusion. The method comprises the following steps: establishing a face image training set; performing face detection, face alignment and face segmentation on each image in the face image training set to obtain each segmented image; obtaining a segmented biased face image set, and determining the area proportion similarity of each image in the segmented biased face image set, the length-width ratio similarity of each image in the segmented biased face image set, and the face similarity of each image in the segmented biased face image set; carrying out weighted fusion on the three features to obtain a multi-feature fusion template coefficient; and determining an average face contour template according to the face contour template, and obtaining a face image after local image enhancement in combination with the image of the face to be recognized. According to the method, a face segmentation step in face image ...

Blind equalization method based on balanced orthometric multi-wavelet

The invention discloses a blind equalization method based on balanced orthometric multi-wavelet (MWTCMA). The invention is characterized in that the properties of multiple wavelets, such as symmetry, support, second-order vanishing matrices and orthogonality are fully utilized, the defect that the properties can not be simultaneously satisfied by a single wavelet except for a Haar wavelet is overcome, the pretreatment that the multiple wavelets are necessary to carry out in application is avoided, the properties of the multiple wavelets are kept, and the calculation efficiency is improved. Simulation results of a submarine sound channel indicate that the method has higher convergence speed than a WTCMA (a blind equalization method based on orthogonal wavelet transformation) and a CMA (a constant modulus algorithm blind equalization method), particularly when a treatment object is a signal with extremely rich high-frequency information. Accordingly, the method can more effectively realize ...

Feedback blind equalization method of dynamic wavelet neural network based on fuzzy control

The invention discloses a feedback blind equalization method of a dynamic wavelet neural network based on fuzzy control, which comprises the following steps: a) passing a transmitted signal sequence x(n) through an unknown channel h(n), and then superimposing on a Gaussian white noise N(n) to obtain an observation sequence y(n); b) processing an error signal e(n) by a constant modular algorithm (CMA) to obtain a tap coefficient c(n) of a linear segment formed by transversal filters in a wavelet neural network; c) passing an input value deviation E(n) and a deviation change deltaE(n) of a fuzzy neural network controller through a fuzzy neural network controller to obtain an iteration step change value delta mu of an extension factor and a shift factor of a wavelet function in a nonlinear segment formed by wavelet neural networks in a dynamic wavelet neural network; and d) sequentially passing the observation sequence y(n) through the dynamic wavelet neural network and a judger to obtain ...

Orthogonal wavelet transform and time diversity technique fused blind equalizing method

The invention discloses a blind equalization method with the integration of orthogonal wavelet transformation and time diversity technique. Integrated with time diversity technique, wavelet transformation technique, phase-lock ring technique and decision-directed (DD) algorithm, the blind equalization method can reduce the influences of multipath effect by using time diversity, can overcome the disadvantages of asymmetry of constant modulus error function by using a hyperbolic tangent error function, can lower the self-correlativity of input signals of a blind equalizer by using orthogonal wavelet transformation to improve the convergence speed, can reduce stable error by using DD algorithm, and can correct phase rotation by using digital phase-lock ring technique. The method has the advantages of high convergence speed and less mean square error, and can effectively suppress phase rotation.

Medical cell edge detection method based on morphology and ant colony algorithm

The invention discloses a medical cell edge detection method based on morphology and ant colony algorithm, comprising the following steps: an initialization, a construction process, an updating process and a judgment process. The method of the invention can effectively detect complete contour under the condition of maintaining the cell sizes, and remove noise points.

Compressed infrared image restoration method based on deep denoising device

The invention discloses a compressed infrared image restoration method based on a deep denoising device, and the method comprises the steps: firstly, carrying out the coding measurement of an original infrared image, obtaining an original measurement value, and inserting a deep denoising device obtained through deep network learning in a conventional optimization-based algorithm when the original infrared image is restored, then, a deep de-noising device is obtained by designing a feature extraction network based on space attention and channel attention, and finally, the two sub-processes are iteratively solved to obtain a restored infrared image, so that the method has interpretability of a model-based optimization algorithm and robustness and rapidity of a convolutional neural network at the same time; and the image restoration quality is improved.

Blind equalization method for wavelet neural network based on space diversity

Orthogonal wavelet transform and time diversity technique fused blind equalizing method

The invention discloses a blind equalization method with the integration of orthogonal wavelet transformation and time diversity technique. Integrated with time diversity technique, wavelet transformation technique, phase-lock ring technique and decision-directed (DD) algorithm, the blind equalization method can reduce the influences of multipath effect by using time diversity, can overcome the disadvantages of asymmetry of constant modulus error function by using a hyperbolic tangent error function, can lower the self-correlativity of input signals of a blind equalizer by using orthogonal wavelet transformation to improve the convergence speed, can reduce stable error by using DD algorithm, and can correct phase rotation by using digital phase-lock ring technique. The method has the advantages of high convergence speed and less mean square error, and can effectively suppress phase rotation.

PCNN-based method for de-noising wavelet domain ultrasonic medical image

The invention discloses a PCNN-based method for de-noising a wavelet domain ultrasonic medical image, which comprises the following steps: firstly, performing logarithmic transformation and wavelet transformation on a noise image and the corresponding pretreatment on a wavelet coefficient; secondly, processing the wavelet coefficient by using a PCNN method and performing the corresponding post-treatment on the wavelet coefficient; and finally, performing the inverse wavelet transformation and exponential transformation on the wavelet coefficient subjected to the post-treatment to obtain a de-noised image. Compared with wavelet de-noise, the method makes the edge of the de-noised image clearer, well retains image details and improves a signal to mean square error ratio; and compared with PCNN, the method overcomes the drawback that during the removal of speckle noises, the PCNN has difficulty in determining model parameters and step length and realizes a higher signal to the mean square ...

Improved T/2 fractional spaced coordinate transforming blind equalization method

The invention discloses an improved T/2 fractional spaced coordinate transforming blind equalization method (T/2-FSE-RCTCMA). Aiming at the defects of low convergence speed and large remainder error of a fractional spaced blind equalization method (T/2-FSE-CMA) during equalizing a higher order QAM signal, the improved method adopts the following steps: separately equalizing a real part and an imaginary part of an input signal of a fractional spaced blind equalizer by analyzing the distribution characteristic of a 16QAM signal constellation diagram; transforming output signals onto the same circle by utilizing coordinate transformation so as to obtain a constant modulus error function after the coordinate transformation; and using the error function to adjust weight vectors of each path of blind equalizers of the T/2 fractional spaced blind equalizer. The improved method effectively overcomes erroneous judgments of the T/2 FSE CMA method to multi-modulus higher order QAM signals during equalizing ...

RBF-based blind equalization method for fuzzy-neural network

The invention discloses a radial basis function (RBF)-based blind equalization method for a fuzzy-neural network. The method analyzes the relation between input signals and emission signals of an equalizer to confirm an initial center value of an RBF equalizer so as to optimize the structure of a blind equalizer and increase the convergence speed, adopts a fuzzy C-mean cluster algorithm to sort the input signals of the blind equalizer to various centers according to different membership grade values, and makes greater response to signals with great membership grade values or else makes little or no response so as to reduce a mean square error.

Multi- drosophila-group collaborative optimization wavelet norm blind equalization method

The invention discloses a multi-drosophila-group collaborative optimization wavelet norm blind equalization method. According to the method, coevolution is introduced into a drosophila optimization method to provide a multi-drosophila-group collaborative optimization method, and the multi-drosophila-group collaborative optimization wavelet norm blind equalization method MFOA-WTCMA is invented; the initial weight vector optimization problem of the wavelet norm blind equalization method WTCMA is converted into the problem of using multiple drosophila groups for collaboratively searching for the lowest food taste concentration, and the drosophila group finding the lowest food taste concentration is the optimal drosophila group; the current position vector of the drosophila group is taken as the initial optimal weight vector of the WTCMA. Simulation results show that compared with the WTCMA and a single-drosophila-group optimization wavelet norm blind equalization method SFOA-WTCMA, the MFOA-WTCMA ...

Balance orthogonal multi-wavelet transform-based fuzzy neural network blind equalization method

The invention discloses a balance orthogonal multi-wavelet transform-based fuzzy neural network blind equalization method. The method comprises the following steps of: firstly, performing balance orthogonal multi-wavelet transform on time domain signals so as to transform the time domain signals into transform domain signals; secondly, performing energy normalization on the transformed signals; and finally, constructing a fuzzy rule by analyzing a mean-square error curve and constructing a blind equalization controller by utilizing an automatic adjustment function of a neural network and the processing capacity of a fuzzy theory on undetermined information so as to overcome the conflict between convergence speed and convergence precision caused by that the traditional constant modulus method adopts fixed step length, wherein the blind equalization controller can automatically adjust the step length in the iteration process according to the fuzzy rule. The balance orthogonal multi-wavelet ...

Hyperspectral image target tracking method based on adaptive weight and confidence coefficient

The invention discloses a hyperspectral image target tracking method based on adaptive weight and confidence, and the method comprises the steps: obtaining a first frame of hyperspectral image, a tth frame of hyperspectral image and an adjacent frame of hyperspectral image after normalization, carrying out the dimension reduction of the images through a principal component analysis method, and respectively obtaining three single-band gray images Z1 and Zt; the tth frame is a search image, respectively extracting depth features of the dimensionality-reduced images, and carrying out naive correlation on the features of the template image and the search image in pairs; an initial response graph R1 and an adjacent response graph are obtained, adaptive weights w1 and w2 are adopted to fuse the two response graphs to obtain a fused response graph, confidence determination and scale estimation are performed on the fused response graph, and a tracking target of a current frame of hyperspectral ...

Hyperspectral video target tracking method based on depth spectrum cascade texture features

The invention discloses a hyperspectral video target tracking method based on depth spectrum cascade texture features, which comprises the following steps of: obtaining a spectral curve of a local region of a tth frame of hyperspectral image, subtracting a spectral curve of an unknown region pixel from the spectral curve of the local region, segmenting the image into a target region and a background region, and importing a (t + 1) th frame, the method comprises the following steps: acquiring a spectral curve of each pixel point in a search area, performing dimension reduction processing on the spectral curve to obtain a band image after dimension reduction, extracting a depth feature and a texture feature of the image, acquiring a weight of each spectral channel according to an image signal-to-noise ratio curve, multiplying the weight with the corresponding texture feature to obtain a spectral cascading feature, covering the spectral cascading feature with a set mask, and obtaining a target ...

Medical image ROI (Region of Interest) compression method based on lifting wavelet and PCNN (Pulse Coupled Neural Network)

The invention publishes a medical image ROI compression method based on a lifting wavelet and a PCNN, which comprises the following steps of: circling a region of interest by a doctor, and separating the region of interest from a region of no interest by a difference image method; adopting lossless compression in the region of interest, constructing compactly supported biorthogonal wavelet transformation through a lifting scheme, and then carrying out Huffman encoding; adopting lossy compression in the region of no interest, segmenting gray-value pixel approximate points through the PCNN, carrying out ignition operation, and then carrying out run-length encoding; and finally carrying out inverse transformation restoration, merging the region of interest and the region of no interest, and eliminating a boundary discontinuity problem through linear interpolation. Experimental results prove that the region of interest can be flexibly selected and controlled by the compression method, the used ...

Hyperspectral target tracking method based on spatial spectrum similarity dimensionality reduction

The invention discloses a hyperspectral target tracking method based on spatial spectrum similarity dimension reduction, which comprises the following steps of: obtaining a normalized first frame and tth frame hyperspectral image, determining a local spectral curve Cl, a target spectral curve Ct and a spectral curve Ci, j of a pixel Hi, j, calculating Cl and Ct according to a spectral angular distance formula to determine a segmentation threshold value, determining a dimension reduction result image Ir and a mask through the segmentation threshold value, and tracking the hyperspectral target according to the dimension reduction result image Ir and the mask. The method comprises the following steps: extracting depth features of Ir through DenseNet, determining fusion weights of texture features through variances, carrying out fusion to obtain recombined texture features, covering the recombined texture features by using a mask to obtain fused texture features, and carrying out discriminant ...

Particle swarm optimization based orthogonal wavelet blind equalization method

The invention discloses a particle swarm optimization based orthogonal wavelet blind equalization method. The method comprises the following steps of: allowing a transmitted signal a(k) to pass through a pulse response channel h(k) to acquire a channel output signal x(k); acquiring an orthogonal wavelet transformation (WT) input signal y(k) through channel noise n(k) and x(k); performing WT on the input signal y(k) to acquire an output signal R(k); taking the input signal y(k) as input of a particle swarm optimization (PSO) algorithm and randomly initializing a group of weight vectors, wherein each particle corresponds to each group of weight vectors one to one; determining a fitness function of PSO through a cost function of an orthogonal wavelet transformation-constant module algorithm (WT-CMA) blind equalization method; when a fitness value is the maximum, finding out an optimal position vector in the group and taking the optimal position vector as an initialization weight vector W(k ...

Improved self-adaption blind source separation method

The invention provides an improved self-adaption blind source separation method NVS-NGA, and the improved self-adaption blind source separation method overcomes the defect that no blind source separation scheme capable of effectively handling the contradiction between the rate of convergence and babbling errors exists in the prior art. Firstly, a traditional separation system structure is improved, the performance index of blind source separation is improved, the improved separation performance index serves as an independent variable, and a Rayleigh distribution function serves as a dependent variable and a variable step size function. Compared with a traditional blind source separation method, the improved self-adaption blind source separation method can rapidly and effectively separate an original signal from a received mixed signal, can effectively handle the contradiction between the rate of convergence and the babbling errors, is high in rate of convergence, small in babbling error ...

Three-dimensional space sound source positioning method

The invention provides a three-dimensional space sound source positioning method, and belongs to the technical field of sound source positioning. The method includes the steps that a double-L-shaped microphone array is established; on the basis of the normalization frequency domain minimum mean square method, a penalty function is introduced to correct frequency spectrum energy, and then impulse responses of different array elements are adaptively estimated and delay inequality is calculated; position coordinates of a sound source are determined through the relation between the acquired delay inequality and the position of double-L-shaped microphones. Compared with a traditional positioning method, the array structure is simple, the calculated quantity is small, anti-noise performance, reverberation resistance and positioning accuracy are effectively improved, and the method is more suitable for indoor three-dimensional sound source positioning and can be widely applied to a car hands-free ...

Combined super-exponential iteration blind equalization algorithm based on orthogonal wavelet transform

The invention discloses a super-exponential interative combined blind equalization method based on orthogonal wavelet transformation (WT-CSEI). The WT-CSEI algorithm is implemented by incorporating the orthogonal wavelet transformation in the super-exponential interative (SEI) algorithm, correcting by use of the weight vector iterative formula of the orthogonal wavelet transformation relative to the SEI algorithm, simultaneously combining the decision directed (DD) algorithm with the soft-switching method, and introducing a phase-locked loop (PLL) technique with regard to the characteristics of time-variable Doppler frequency shift of under acoustic channel. The WT-CSEI algorithm corrects the phase rotation by means of the PLL technique, accelerates the convergence rate by means of the orthogonal wavelet transformation, reduces the steady-state error by means of the combination of the soft switching method and the DD algorithm, can effectively track the time varying characteristics of the ...

Dual mode variant step blind balance method based on orthogonal wavelet packet transform

The invention discloses a double-modulus variable step-size blind equalization method based on orthogonal wavelet packet transformation (WPT-VDMA). The method achieves the effect of switch between the constant-modulus blind equalization algorithm based on orthogonal wavelet packet transformation (WPT-CMA) and the decision directed blind equalization algorithm based on orthogonal wavelet packet transformation (WPT-DD) by means of the symbol judgment, thereby reducing the mean square error; and the method accelerates the convergence rate of the WPT-CMA by employing the output signal power as the variable step-size of the independent variable, thereby further improving the convergence property of the WPT-VDMA algorithm. The method has the advantages of high convergence speed and small mean square error.