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基于MATLAB的GMSK和基带信号功率谱密度仿真实验开发 (Experiments development of GMSK and power spectral density of base-band signals based on Matlab simulation)

special case of dedge detection ,,,,

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LBG算法进行矢量量化器的设计,用分裂法获得初始码书(Using vector quantization LBG algorithm design, with split method to obtain the initial codebook)

fundamentals_of_dsp_solutions for matlab

一个四节点，电力系统潮流计算程序，采用pq分解法计算潮流(power flow code of PQ)

park反变换，matlab simulink仿真模型搭建(Park inverse transformation)

说明：  录制一段个人的语音信号，并对录制的信号进行采样；画出采样后语音信号的时域波形和频谱图；给定滤波器的性能指标，采用双线性变换法和窗函数法设计滤波器，并画出滤波器的频率响应；然后用自己设计的滤波器对采集的信号进行滤波，画出滤波后信号的时域波形和频谱，并对滤波前后的信号进行对比，分析信号的变化；回放语音信号；最后，设计一个信号处理系统界面。(Record a personal voice signal, and recording the signal is sampled draw sampled speech signal time-domain waveform and frequency spectrum for a given filter performance, the bilinear transformation and design of filter window functions and draw the frequency response filter then filter of their own design collection of the signal filtering, to draw the filtered signal in time domain waveforms and frequency spectrum, and filtering the signal before and after comparison, analysis of signal changes playback audio signals Finally, a signal processing system interface design.)

说明：   Buck－Boost电路的建模与仿真主程序

Matlab好课程,内容比较详细，容易懂，适合查询用(Matlab a good course, more detailed content, easy to understand, for queries with)