SVMcg

Matlab中的遗传算法工具箱，内含多个功能函数，方便调用。(Genetic Algorithm in Matlab toolbox containing a number of performance function to facilitate the call.)

Incremental Linear Discriminant Analysis

optical fiber communications

地震信号研究中，建立主频freq为15Hz的单道雷克子波，并进行频谱分析。这个是自己学习时编的，每步都有详细说明和个人认识。(Study of seismic signals, the establishment of frequency freq 15Hz single-channel Ricker wavelet and spectral analysis. This learning series, each step in detail and personal understanding.)

LDA和PCA的一个程序，主要是LDA和PCA，并不是一个完整的工程，仅供大家参考。(LDA and PCA program, mainly LDA and PCA, is not a complete project, only for reference.)

variational bayesian blind image restoration

工具箱 (整数线性规划工具箱) Matlab中使用(Kit (Integer Linear Programming Kit) Matlab using)

三相光伏逆变器孤岛仿真包括pWM整流器、PI调节器等。(PV inverter islanding simulation.it icludes PWM rectifier and PI regulator)

说明：  这里介绍了一种基于自适应滤波的噪声抵消法，采用归一化最小均方误差算法，采集实际噪声环境下各种不同信噪比的带噪语音样本进行降噪处理，实验结果表明，处理后信号的信噪比得到了较大程度的提高，大大改善了听音效果，具有很高的可懂度，且语音自然度好，没有失真；并与谱减法进行了比较，自适应噪声抵消法的降噪幅度比谱减法有一定提高，在听音效果上，用自适应噪声抵消法处理后的语音在清晰度，自然度方面优于谱减法。(Here a novel adaptive noise cancellation method using normalized least mean square algorithm, collecting a variety of actual noise environment, the SNR of noisy speech samples for noise reduction, experimental results show that treatment After the signal to noise ratio was greater improvement in the level, greatly improved the listening results, with high intelligibility and naturalness of speech is good, no distortion and were compared with the spectral subtraction, adaptive noise cancellation law than the spectral subtraction noise reduction rate of a certain improvement in the listening results, and with the adaptive noise cancellation method in the treatment of voice clarity, naturalness is better than spectral subtraction.)

Common spatial pattern 公共空间模式滤波是处理脑电信号的一种方法，它可以使两类想象运动EEG的协方差之间的差距最大化，便于后期的分类处理。(Common spatial pattern model of public space filtering is a method of EEG signal processing, it can make two types of movement EEG covariance imagine the gap between the maximum, to facilitate the later classification.)