convolve2signals

BP网络的MATLAB工具箱的实现。。 ——Bpnet(BP network MATLAB toolbox implementation. .- Bpnet)

用四元十字阵做被动声定位算法设计，现在是用matlab神经网络工具箱构建RBF神经网络然后仿真显示图形(With a four-element Array do passive acoustic localization algorithm design, now using matlab neural network toolbox and then build on RBF neural network simulation display graphics)

matlab从入门到精通第9章书后源码对初学者很有帮助(matlab)

给出了平方率检波下，求检测门限值的程序。(Gives the square of the rate of detection, the detection threshold seeking procedure.)

利用matlab能够实现语音信号的分割与储存(Can be achieved using matlab segmentation and storage of speech signals)

matlab+车牌识别定位程序，可以给需要的朋友做一些参考。(Matlab+ license plate recognition positioning procedures, needs to be a friend to do some reference.)

传统的短时谱估计语音增强算法通常假设语音谱分量相互独立，没有考虑语音谱分量间的相关性。针对这 一问题，该文提出一种新的基于多元Laplace分布模型的短时谱估计算法。首先，假设语音的离散余弦变换(DCT) 系数服从多元Laplace分布，以此利用谱分量间的相关性；在此基础上，利用多元随机矢量的高斯尺度混合模型表 示，推导得到语音DCT系数矢量的最小均方误差(MMSE)估计的解析表达式；并进一步推导了基于该分布模型的 语音存在概率，对最小均方误差估计子进行修正。实验结果表明，该算法在抑制背景噪声和减少语音失真等方面优 于传统的语音增强方法。(The spectral components of speech are usually assumed to be independent in traditional short-time spectrum estimation, which is not the case in practice. Tosolve this problem, a new speech enhancement algorithm with multivariate Laplace speech model is proposed in this paper. Firstly, the speech Discrete Cosine Transform (DCT) coefficients are modeled by a multivariate Laplace distribution, so the correlations between speech spectral components can be exploited. And then a Minimum-Mean-Square-Error (MMSE) estimator based on the proposed model is derived using a Gaussian scale mixture representation of random vectors. Furthermore, the speech presence uncertainty with the new model is derived to modify the MMSE estimator. Experimental results show that the developed method has better noise suppression performance and lower speech distortion compared to the traditional speech enhancement method. )

Linear programming with matlab. A good book about thia topic.

判断系统上升时间，峰值时间，超调量和调整时间。《自动控制》清华出版社的课后编程题目。(Determine the system rise time, peak time, overshoot and time to adjust. )

％WAVETEST Example Matlab script for WAVELET, using NINO3 SST dataset ％ ％ See "http://paos.colorado.edu/research/wavelets/" ％ Written January 1998 by C. Torrence ％ ％ Modified Oct 1999, changed Global Wavelet Spectrum (GWS) to be sideways, ％ changed all "log" to "log2", changed logarithmic axis on GWS to ％ a normal axis. ( WAVETEST Example Matlab script for WAVELET, using NINO3 SST dataset See http://paos.colorado.edu/research/wavelets/ Written January 1998 by C. Torrence Modified Oct 1999, changed Global Wavelet Spectrum ( GWS) to be sideways, changed all log to log2 , changed logarithmic axis on GWS to a normal axis.)