attachments-(1)

MImo detector , very useful for student

压缩感知中全变分（TV）重构算法，本程序主要用于图像重构(Total variation in the compressed sensing (TV) reconstruction algorithm, this procedure is mainly used for image reconstruction)

小波变换的实例，直接放在MATLAB里就可以运行，但需要换入自己的图片(Wavelet transform instance, can be placed directly inside MATLAB to run, but needs to be replaced into its own image)

产生k分布，瑞利分布，正太分布，PSK_lfm,RAY,等信号的matlab文件(Generated k distribution, Rayleigh distribution, normally distributed, PSK_lfm ray signals such as Matlab files)

采用Matlab实现GMSK的正交调制与解调，要求画出基带调制信号及GMSK信号的波形(Achieved using Matlab quadrature GMSK modulation and demodulation, asked to draw GMSK baseband modulation signal and the signal waveform)

信号分解为六层的细节信号的谱分析小波包络谱分析修改版6层( Wavelet envelope spectrum analysis of a modified version of layer signal is decomposed into six layers of detail signal spectrum analysis)

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)

说明：  matlab的中文帮助文档，便于学习的好资料，欢迎大家下载。。。(matlab help documentation in Chinese, easy to learn any information, welcome to download. . .)

kohoenn neural network

采用卡尔曼滤波器滤除语音信号中的有色噪声，采用Matlab实现，并给出了实例(Kalman filter to filter the speech signal colored noise, using Matlab to achieve, and gives an example)