ProgrammingWithMATLAB

Mean-scales data table Z (new operation or based on know parameters), or reverses mean-centering operation.

make ccs project by matlab

a matlab code for calculating the lyapunov exponents for any given system

#include "comparer.h" #include <iostream> using namespace std int Comparer::compareByName(Student& s1,Student& s2) { return strcmp(s1.m_szName,s2.m_szName) } int Comparer::compareBySurname(Student& s1,Student& s2) { return strcmp(s1.m_szSurname,s2.m_szSurname) } int Comparer::compareByGroup(Student& s1,Student& s2) {

MMA盲均衡算法，上传供交流，希望大家提供宝贵的意见(MMA blind equalization algorithm, uploads for the exchange, we hope to provide valuable advice)

精馏过程二次高斯性控制算法，非常非常的重要的程序(Quadratic Gaussian distillation process control algorithms, very, very important program)

说明：  这次上传的程序源码是关于使用BP神经网络预测数据。(The upload program source code is on the use of BP neural network forecasts.)

Speech Quantization_Compare SNRs of speech cs5 with mu-law companding and uniform quantization (Speech Quantization_Compare remnants of spee ch cs5 with mu-law companding and uniform quant ization)

说明：  用于分类，使用的是matlab工具，代码很简单，但是很实用。。。。。(class)

支持向量机的研究现已成为机器学习领域中的研究热点，其理论基础是Vapnik[3]等提出的统计学习理论。统计学习理论采用结构风险最小化准则，在最小化样本点误差的同时，缩小模型泛化误差的上界，即最小化模型的结构风险，从而提高了模型的泛化能力，这一优点在小样本学习中更为突出。SVM理论正是在这一基础上发展而来的，经过十几年的研究和发展，已开始逐步应用于一些领域。在解决小样本、非线性及高维模式识别问题中表现出许多特有的优势，已经在模式识别、函数逼近和概率密度估计等方面取得了良好的效果。( Support Vector Machine (SVM) is a new machine learning technique in recent years developed based on statistical learning theory (SLT). It wins popularity due to many attractive features and emphatically performance in the fields of nonlinear and high dimensional pattern recognition. The theory and algorithm of SVC is studied at first, then, simulation is to recognize handwritten numeral with the Lib-SVM toolbox. At last, we study the result, which shows that the SVC can do the classification problem with good performance, shorter operation time and is more suitable for real-time implementation.)