onda_finale_E

两种interpolate图像的算法， 一种是OptimalRecovery, 另一种不知。(two algorithms to interpolate images, one is optimalRecovery, another one unknown.)

说明：  新型PID控制及其应用 陶永华编 PDF格式(PID PDF)

finite-time稳定控制算法，李雅普诺夫方法得出LMI算法，进而求出反馈增益矩阵(finite-time stability control algorithm)

先进pid参数整定，包含各种用于pid参数整定的算法(Advanced pid parameter tuning)

说明：  电磁波在自由空间传播的MATLAB编程，给出了仿真的波形(MATLAB programming for electromagnetic wave propagation in free space)

时域信号转换为频域信号的几个例子，本人都用过的，绝对能运行(Time-domain signal is converted to frequency domain signal a few examples, I have been used, absolutely can run)

说明：  运用模拟退火算法对战区通信网频率进行了规划，其中用到了matlab-gui设计了界面(The use of simulated annealing algorithm for the theater communications network frequency planning, which uses the matlab-gui designed interface)

利用方波调制和调制，可以设置不同的占空比以及幅值(Using a square wave modulation and modulation, can set different duty cycles and the amplitude)

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)

基于小波的图像去噪，用MATLAB实现，(Image denoising based on wavelet)