robust

IIR Decomposition Parallelization Methods

说明：  采用正交匹配追踪（OMP）算法实现信号重构(Orthogonal matching pursuit algorithm for signal reconstruction)

包含有DCT水印嵌入算法，DWT水印嵌入算法，以及水印攻击和性能测试程序。参考价值极大(mark )

说明：  用CA(元胞自动机)判断网络两点之间的连通性(Using CA to determine the connectivity between two nodes of network)

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)

MATLAB命令大全，非常简单实用的教程。适合初学者使用，()

罚函数法是将有约束最优化问题转化为求解无约束最优化问题。在此给出罚函数法的Matlab源程序。(Penalty function method is a constrained optimization problem into solving unconstrained optimization problems. This gives the penalty function in Matlab source.)

采用差异算法的LT码，好不容易写的啊，希望对同学们有用(Difference algorithm using the LT code, finally write ah, I hope be useful for students)

多项式的曲线拟合，使用MATHCAD实现(Polynomial curve fitting using MATHCAD achieve)

Add myaa.m to your path and enjoy anti-aliased professionally looking graphics in Matlab at any time. Myaa works with any kind of graphic (3-D, plots, scatterplots, ...) and even adds anti-aliasing to text, ui controls and grids. Myaa is ideal for complex, cluttered and saturated plots.