资源列表
积分
- 一个用C++编写的积分算法,可以用VC编译.-an integral prepared by the algorithm can be used in VC compiler.
插值计算
- 主要是进行插值方面的数值计算，是用c编的-interpolation is primarily for the numerical calculation, is part of the c
Basic_of_ICA
- 基于独立分量分析进行盲信号分离的原理简介和例程-based on independent component analysis for the Blind Signal Separation Principle and routines
GlobalOpt
- 我找到的较好用的高维非线性函数的全局优化程序，使用说明参见解压后的MCS包。该程序不需要Hessian矩阵。-I find a better use of high-dimensional nonlinear function of the global optimization process, See Note the use of the MCS unpacked package. The program does not need Hessian matrix.
Basic_of_CMA
- 恒模算法的简介，它适用于信道的盲均衡。Matlab程序提供基本的框架，可以修该里面的参数以测试该算法的性能-CMA briefings, which applies to Channel Blind balanced. Matlab to provide a basic framework, it can be done inside of the parameters to test the performance of the algorithm
Poland
- 自动计算公式，会根据优先级 输入5+9*9，会计算出86 -automatic formula, according priority to import 5 9 * 9, reckoned 86
ln_cascade_zip
- parallel cascade identification of nonlinear system-parallel cascade identification of nonli near system
queueing4
- N个并列的单通道等待制系统，各服务员能力相等，服务时间服从指数分布，顾客的总体到达服从指数分布，用Monte－Carlo方法，按1…N的顺序循环排入-N tied for the single-channel system, the attendant equal ability, service to follow exponential distribution, customers submit to reach the overall index distribution, Monte-
BtworthFilter
- 构造级联型Butterworth滤波器，可以是任意阶数，并计算出频率幅度响应，非常实用，封装成为一个类，以便大家使用。开发环境为VC 6.0-tectonic Cascade Butterworth filter, can be arbitrary order. to work out the frequency response range, very practical, Packaging, as a category, so that we use. Development enviro
一种规则和贝叶斯方法相结合的文本自动分类策略
- 一种规则和贝叶斯方法相结合的文本自动分类策略-rules and a Bayesian approach is a combination of automatic text classification strategy
BSplineInterpolatePrj
- B样条插值，基于散乱数据的B样条插值基本算发。做的动态链接库。-B-spline interpolation, scattered data on the B-spline interpolation basically been made. The dynamic link library.
卡尔曼滤波forMatrixVb
- 我用matrixVb编的卡尔曼滤波程序，很简单，但也费我不少工夫，希望对大家有点用，我就工夫没白费了，有问题互相切磋吗-I used matrixVb series Kalman filtering process is very simple, but I have spent a lot of efforts and I hope that we are a bit used to, I did not work in vain, to learn the problem?