LMSPandPVSS_LMS

UPFC SIMULTION IN MATLAB MODEL

本程序是基于WaveLab802平台作的。 包括 VisuShrink方法、SUREShrink方法、BayesShrink等方法。噪声方差大小和小波可以自行设定。(This procedure is based on the platform for WaveLab802. VisuShrink methods including, SUREShrink methods, BayesShrink and other methods. Size and wavelet noise variance can be set.)

定点频域ICA，使用高斯函数、负熵最大化来处理语音信号分离问题的演示(FIXED-POINT FREQUENCY DOMAIN ICA with GENERALIZED GAUSSIAN FUNCTION BASED NEGENTROPY APPROXIMATION for SPEECH SIGNAL SEPARATION)

high patch filtering

matlab画等温函数曲线、matlab图像GUI设计(matlab painting isothermal function curves, matlab image GUI design)

very important for pattern recognition using neural networks

二阶锁相环 m 文件，运行有图，应用广泛(Second-order phase-locked loop m documents, there are plans to run a wide range)

k-nearest neighbor algorithm

用MATLAB让ASK信号产生~~~~~~~~~~~~~~~~~~~~~~~~(ASK signal using MATLAB to generate ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~)

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.)