RS_STTC_tailbiting

Creating the training and testing sets

说明：  超宽带通信仿真程序，脉冲成型仿真技术(ultra-wideband communications simulation program, pulse shaping simulation technology.)

数字信号处理基于matlab实现的很好的电子书，里面含有大量的实例和讲解，不容错(Matlab-based digital signal processing to achieve a good e-book, which contains a large number of examples and explanations, is not fault-tolerant)

energy leach a new version

matlab经典算法程序中关于插值和拟合的具体指导资料 给需要的朋友们以启发(classical algorithm matlab program on interpolation and fitting specific guidance information to a friend who needs to inspire)

说明：  多类划分 matlab中使用数据挖掘的实例一个 方便新人参考(Matlab data mining multi-class classification)

这是个RS编码的matlab仿真程序，提供给大家，希望能带给大家帮助(it is a program of encode and decode of rs for a picture,wish it can help you)

在matlab上读取数据 应用广泛 便于以后对数据进行进一步的处理 (Input the data by matlab)

以matlab为仿真程序的电机双闭环控制仿真,simulink(The motor dual closed-loop control simulation)

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)