cvxbook-stanford

S变换的matlab源码，并应用几个信号作为例子来说明怎么使用s变换以及s变换可以用来做些什么事情。s变换是时频分析领域中一个较新的内容，现在在信号处理，地震勘探，语音识别等领域都开始了对它的应用研究，是目前的一个热点。(S transform matlab source, and apply some signal as an example to illustrate how to use s and s transform transform can be used to do things. s transform time-frequency analysis are a relatively new area of content, now in the signal processing, seismic exploration, speech recognition and other areas of the beginning of its applied research, is a hotspot.)

说明：  matlab_数字图像处理源程序,学习之需要(matlab )

说明：  本文件是脑电信号分析MATLAB工具箱，是做信号处理的必备工具，尤其针对生物医学信号处理，更合适。(This file is EEG analysis MATLAB toolbox, is the necessary tool for signal processing, especially for biomedical signal processing, more appropriate)

Implement primitive realloc(3) functionality.

The optimization behavior of the self-adaptation (SA) evolution strategy (ES) with intermediate multirecombination (the (=I )-SA-ES) using isotropic mutations is investigated on the general elliptic objective function. An asymptotically exact quadratic progress rate formula is derived. This is used to model the dynamical ES system by a set of difference equations. The solutions of this system are used to analytically calculate the optimal learning parameter  . The theoretical results are compared and validated by comparison with real (=I )-SA-ES runs on typical elliptic test model cases. The theoretical results clearly indicate that using a model-independent learning parameter  leads to suboptimal performance of the (=I )-SA-ES on objective functions with changing local condition numbers as often encountered in practical problems with complex fitness landscapes.

多个目标提取，原始帧和背景帧相减，提取目标(Multiple target detection, the original frame and background frame subtraction, extraction of target)

d-statcom matlab simulation(matlab6)

Basic MATLAB code for Image Processing

说明：  ％ PURPOSE : Demonstrate the differences between the following filters on the same problem: ％ ％ 1) Extended Kalman Filter (EKF) ％ 2) Unscented Kalman Filter (UKF) ％ 3) Particle Filter (PF) ％ 4) PF with EKF proposal (PFEKF) ％ 5) PF with UKF proposal (PFUKF)( PURPOSE: Demonstrate the differences between the following filters on the same problem: 1) Extended Kalman Filter (EKF) 2) Unscented Kalman Filter (UKF) 3) Particle Filter (PF) 4) PF with EKF proposal ( PFEKF) 5) PF with UKF proposal (PFUKF))

用Pisarenko谐波分解法估计一组实验数据的正弦频率及幅度。得出真实功率谱密度。(Pisarenko harmonic decomposition method with a set of experimental data estimate the sinusoidal frequency and amplitude. The true power spectral density obtained.)