Matlab

提供了一个非常简洁的MVDR的matlab m函数(Provides a very simple matlab m function the MVDR)

说明：  通过并行压缩进行二维信号压缩，提出了一种利用并行压缩传感技术对二维信号进行压缩的新方案。根据这个原理，译码器的重新构造可以并行进行。通过对二维信号进行某些排列，可以确保所有列具有大致相同的密度级别，并且可以使用相同的测量矩阵进行采样。这样可以避免二维信号的矢量化，从而大大减小测量矩阵的尺寸。我们证明，如果排列良好，重建均方误差的上限会更紧。为了说明这一方案，我们将其应用于视频压缩并使用不同帧的排列有两种：参考帧的基于Z字形扫描的排列和非参考帧的基于块测试的排列。仿真结果表明，在相同的压缩比下，峰值信噪比比比在无置换情况下可提高3-7db左右。(we propose a new scheme to compress 2D signals using parallel compressed sensing. According to this seheme, the reeonstruction at the decoder can be performed in parallel. By performing certain permutation on a 2D signal, all columns are insured to have approximately the same density level and can be sampled using the same measurement matrix. In this way, vectorization of a 2D signal can be avoided, and thus the size of the measurement matrix can be dramatically reduced. We prove that with a good permutation, we can have a tighter upper bound on reconstruction mean square error. To illustrate this scheme, we apply it to video compression and use two kinds of permutations for different frames: the zigzag-scanbased permutation for reference frames and the block-test-based permutation for non-reference frames. Simulation results show that under the same compression ratio, the peak signal-to-noise ratio can be improved by approximately 3-7 dB compared to the case without permutation.)

说明：  MATLAB编程，国外高校电子信息类优秀教材，英文影印版(MATLAB programming, outstanding foreign university electronic information materials, photocopying English version)

永磁同步电机simulink仿真 (Permanent magnet synchronous motor simulink simulation)

粒子群优化算法:是通过模拟鸟群觅食行为而发展起来的一种基于群体协作的随机搜索算法。(Particle Swarm Optimization)

FEM1D_SPECTRAL_NUMERIC is a MATLAB program which applies the spectral finite element method to solve the problem u = - pi^2 sin(x) over [-1,+1] with zero boundary conditions, using as basis elements the functions x^n*(x-1)*(x+1), and carrying out the integration numerically using MATLAB s quad() function. This function solves the problem u = - pi^2 * sin( pi * x ) for x in (-1,1), with boundary conditions u(-1) = u(1) = 0.

Simulink engineer orchard

rbf神经网络自适应控制matlab仿真实例(Matlab simulation example of RBF neural network adaptive control)

说明：  MATLAB 学习小程序： BP神经网络的数据分类-语音特征信号分类(MATLAB learning applet: data classification of BP neural network-speech feature signal classification)

信息理论用的工具包，算法已经很全了matlab编写的(Information theory with the toolkit, the algorithm is already very wide, prepared by the matlab)