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matlab编程基础 实例介绍解析 附有源码(matlab Programming examples with source code analysis)

Steve Gunn 开发的svm工具箱源代码，用于分类和回归(Developed by Steve Gunn，used in classification and regression)

说明：  直方图阈值的双峰法 该阈值化方法的依据是图像的直方图， 通过对直方图进行各种分析来实现对图像的分割。(Bimodal histogram threshold method of the threshold value method is based on the histogram of the image, to achieve the image segmentation by the various analyzes of the histograms.)

复杂网络拓扑生存算法，对可能出现的拓扑不连通的状况进行了考虑，并支持网络拓扑的动态变化(Survival of a complex network topology algorithm, consider the situation that may appear disconnected topology and supports dynamic changes in the network topology)

fsk 使用matlab进行二进制振幅调制(fsk using matlab binary amplitude modulation)

About correlation. In signal processing, cross-correlation is a measure of similarity of two waveforms as a function of a time-lag applied to one of them. This is also known as a sliding dot product or inner-product. It is commonly used to search a long duration signal for a shorter, known feature. It also has applications in pattern recognition, single particle analysis, electron tomographic averaging, cryptanalysis, and neurophysiology.

Wireless Sensor Networks have been proposed for a multitude of location-dependent applications. For such systems, the cost and limitations of the hardware on sensing nodes prevent the use of range-based localization schemes that depend on absolute pointto- point distance estimates. Because coarse accuracy is sufficient for most sensor network applications, solutions in range-free localization are being pursued as a cost-effective alternative to more expensive range-based approaches.

基于MATLAB软件的有关雷达杂波的很多个程序，相信对初学者很有帮助(MATLAB-based software clutter on the radar of a lot of procedures, I believe very helpful for beginners)

Lyapunov指数生成程序。该指数是判断系统是否处于混沌状态的有力工具，很好用(Lyapunov index generator. The index is to determine whether the system is a powerful tool in a chaotic state, that is great)

给定一个普通多项式p(x)，用列向量表示，阶次从高到低排列，此函数返回p(x)的切比雪夫多项式展开的系数，返回的的结果也是一个列向量，同样按切比雪夫多项式的阶次从高到低排列 另外该函数用cos(x)项傅里叶级数展开一个多项式( ChebyshevExpansion.m by David Terr, Raytheon, 5-26-04 Given a polynomial f(x) of degree n expressed as a row vector of coefficients of x^k with highest power on the left, expand f(x) as a sum of scalar multiples of Chebyshev polynomials, i.e. return the column vector of coefficients a_k with k running from n to 0 from top to bottom such that f(x) = sum_{k=0}^n{a_k P_k(x)}.)