lyapunov

。本文研究了SC-FDE系统中的最小均方误差判决反馈 均衡（MMSE-DFE）和基于LMS准则的自适应均衡算法， MATLAB仿真表明，由于LMS自适应均衡算法能有效的跟 踪信道变化并更新均衡器的抽头系数，其性能略优于最小 均方误差判决反馈均衡算法。(. In this paper, the SC-FDE system, the minimum mean square error decision feedback Equalization (MMSE-DFE) and criteria based on LMS adaptive equalization algorithms MATLAB simulation results show that LMS adaptive equalization algorithm as effective with Track changes and update the channel equalizer tap coefficients, its performance slightly better than the minimum Mean square error decision feedback equalization algorithm.)

《精通MATLAB R2011a》电子版，内容详细，有代码示例(" Mastering MATLAB R2011a electronic version, detailed code examples)

在matlab下模擬hamming codeing的編解碼過程,碼率為7/11,提供初學者學習(At Analog hamming codeing under matlab codec process, rate of 7/11, to provide beginners Study)

云分类器，一种基于云模型理论的分类程序。程序中使用云分类器对Iris数据集进行了测试(cloud classifier, a theoretical model based on cloud classification procedure. Procedures used for cloud classification of Iris data set for testing)

说明：  运用随机森林方法对数据进行建模，可以用模型进行预测与分类(Random forest prediction and classification)

说明：  有关于胎儿心电信号提取算法研究 .rar(suanfa )

正弦波脉宽调制技术（SPWM）相电压波形的产生与实现(Phase voltage waveform of the sinusoidal pulse width modulation (SPWM))

用于近场信号的参数估计，如信号方位、距离(estimation of DOA)

说明：  同步电机特性仿真 包括外特性、调整特性和功率特性 本程序仅对功角特性进行仿真(Simulation synchronous motor including external features, adjust the characteristics and power performance characteristics of this procedure only for the simulation of power angle)

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)