Acoustic_MOdeling_Single_Diagonal_Gaussian_HMM_Sp

MATLAB模拟人走路姿势，各个节点的选取和函数的调用是我们学习的很好例子(MATLAB simulation of human walking, each node of the selection and function calls is a good example of learning)

粒子群优化算法，最经典的原始MATLAB算法，执行效率高(Particle swarm optimization algorithm, the most classic of the original MATLAB algorithm, the implementation of high efficiency)

Lorenz-Matlab函数，该程序可以用于毕业设计用。(Lorenz function)

单阵纯方位目标运动分析及双阵纯方位目标运动分析 包括观察者运动与目标运动函数修正 可惜修改两者运动轨迹(Single sensor bearings-only target motion analysis and dual-array bearings-only target motion analysis, including observer movement and target movement function correction Unfortunately, modify both trajectory)

matlab6.0图形图像函数，介绍应用matlab进行图形图像处理时应用到得函数(matlab6.0 graphic image function, introduced graphical application matlab image processing function, when applied to get)

COST207.m... ..COST模型 GWSSUS.m.........高斯白噪声 信道模型的ppt(COST207.m ... .. COST model GWSSUS.m ......... white Gaussian noise channel model ppt)

说明：  DSP实验的matlab实现，如 离散时间系统，傅里叶变换，快速傅里叶变换等(dsp FFT)

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)

用巴特沃斯法实现数字带通滤波器的设计,用matlab一步一步实现，以数字低通滤波器的设计为基础。(Apply butterworth to design DF.)

window平台下clearcase的使用指南，包括安装与使用(A component of the Windows platform use guidelines, including installation and use)