xiangguanfenxifa

matlab5入门与应用，虽然讲的版本有点老，但是对刚上手的菜鸟来说，还是有一定的指导做用(matlab5 entry and application, although a little talk about the old version, but just for the rookie-to-use, or have to do with some guidance)

MATLAB语言常用算法程序集，包含基础的变成技巧以及数值算法，是很好的学习材料(Assembly algorithm used MATLAB language, including basic skills and become a numerical algorithm, is a very good learning materials)

Some New Indexes of Cluster Validity

c# language specification book (zip version)(pdf inside)

svm3.0 用于svm算法（支持向量机）程序可直接调用，matlab语言(svm3.0 algorithm for svm (support vector machine) can directly call the procedure, matlab language)

说明：  一种在代数结构中的常用算法，对于伽罗华域的各种计算，非常适合各种编码算法(Algebraic structure of a common algorithm, for a variety of computing Galois field, ideal for a variety of coding algorithms)

This program is desiged to evaluate the space-frequency codes According to our desgn criteria for space-frequency codes used in OFDM system

CSAPP Code Optimization lab

第9章共振峰的估算方法259 9.1预加重和端点检测259 9.1.1预加重259 9.1.2端点检测260 9.2倒谱法对共振峰的估算260 9.2.1倒谱法共振峰估算的原理260 9.2.2倒谱法共振峰估算的MATLAB程序261 9.3LPC法对共振峰的估算262 9.3.1LPC法共振峰估算的原理262 9.3.2LPC内插法共振峰的估算263 9.3.3LPC求根法共振峰的估算266 9.4连续语音LPC法共振峰的检测268 9.4.1简单LPC共振峰检测268 9.4.2改进的LPC共振峰检测270 9.5基于HilbertHuang变换(HHT)的共振峰检测274 9.5.1希尔伯特变换275 9.5.2语音信号的另一种模型——AMFM模型278 9.5.3对AMFM模型的分析279 9.5.4语音信号共振峰特征参数提取的HHT方法279 9.5.5基于HilbertHuang变换的共振峰检测步骤和MATLAB程序280(Estimation Chapter 9 259 9.1 formant pre-emphasis and pre-emphasis endpoint detection 259 259 9.1.1 9.1.2 9.2 endpoint detection principle cepstrum estimate 260 to 260 9.2.1 formant formant estimation cepstrum 260 9.2.2 cepstrum estimate estimate estimate formant MATLAB program 261 9.3LPC method formant 262 9.3.1LPC law principle of formant estimation interpolation within 262 9.3.2LPC formants 263 9.3.3LPC Root Law resonance estimate peak 266 9.4 Continuous Speech LPC formant detection method is simple LPC formant 268 9.4.1 268 9.4.2 Improved detection LPC 270 9.5 formant detection based HilbertHuang transform (HHT) 274 9.5.1 formant detection Hill Another model 275 9.5.2 Hilbert transform voice signals- AMFM model 278 9.5.3 Analysis of the AMFM model HHT Method 279 9.5.4 formant speech signal feature extraction based HilbertHuang transform 279 9.5.5 Resonance peak detection step and MATLAB program 280)

monte carlo的matlab仿真的差错率(monte carlo simulation matlab the error rate)