traffic_of_cross_street

Speech recognition matlab code

二维简单理想导体方柱在MATLAB环境下实现自动剖分，编码。自己整合方程并且求解，得到各点的场值(Simple two-dimensional perfectly conducting square cylinder in the MATLAB environment for automatic generation, coding. Their integration and for solving equations, the various points of market value)

渐入渐出动画 无闪烁 无黑底 Demo，应用程序编程源码，很好的参考资料。(The fade in and fade out animation flicker free no black Demo, application programming source code, a good reference.)

如何运用朴素贝叶斯的公式对两类特征进行分类(How to use simple bayesian formula characteristics of two kinds of classification)

扩张状态观测器，用来观测系统状态以及干扰量，设计前馈补偿量进行系统矫正(State Observation Using Extended State Observer)

this codel model rician clutter

说明：  Matlab数理统计方面的图书源码聚类分析，希望对您有用(Matlab mathematical statistics, cluster analysis of source books, I hope useful for you)

将压缩感知用于谱估计中，根据论文谱压缩感知的一些程序(Compressive sensing (CS) is a new approach to simultaneous sensing and compression of sparse and compressible signals based on randomized dimensionality reduction. To recover a signal from its compressive measurements, standard CS algorithms seek the sparsest signal in some discrete basis or frame that agrees with the measurements. A great many applications feature smooth or modulated signals that are frequency sparse and can be modeled as a superposition of a small number of sinusoids. Unfortunately, such signals are only sparse in the discrete Fourier transform (DFT) domain when the sinusoid frequencies live precisely at the center of the DFT bins. When this is not the case, CS recovery performance degrades significantly. In this paper, we introduce a suite of spectral CS (SCS) recovery algorithms for arbitrary frequency sparse signals. The key ingredients are an over-sampled DFT frame, a signal model that inhibits closely spaced sinusoids, and classical sinusoid parameter e)

说明：  电力系统专业研究生必备，最经典的短路计算程序，东南大学教学资料，注释很全(The power system postgraduate essential, the most classic short-circuit calculation program, Southeast University, teaching materials, the comment is)

CAO、FNN算法计算混动时间序列的延迟时间(CAO delay time)