prony

矢量量化 含说明文档和源码和图像 值得下载(Vector quantization with documentation and source code and image is worth downloading)

A program implementing PID controller for vehicle fuel system

Decoding LDPC codes under MATLAB, I have written, in 7 / 0, validated(Decoding golay codes under MATLAB, I have written, in 7/0, validated)

电力系统分析（英文）书的附带matlab潮流与稳定分析源码，对电力系统入门的学生具有很好的参考价值(Trends and stability analysis with matlab source power system analysis (in English) of the book, Getting the power system for students with a good reference value)

说明：  spwvd时频分析的MATLAB程序，包括源代码和求解SPWVD分布的M文件(SPWVD time-frequency analysis )

通用的牛顿拉夫逊法潮流计算程序，可以自行输入支路参数矩阵，节点参数矩阵。(Universal Newton Raphson power flow )

通过matlab 实现通信的模拟调制与解调(analog AM)

matlab 并联机构 工作空间程序(matlab parallel mechanism workspace program)

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.)

Face Detection using local SMQT features and split up SnoW classifier