code4

天在维普下载了一篇SPIHT算法改进的论文，（耿兴云，《基于改进SPIHT的静态图像编码》，电脑知识与技术：学术交流-2007年5期），我根据该文提出的改进算法，用Matlab来实现，却发现改进算法的程序运行速度比原算法还要慢，希望有兴趣的朋友进来看看，评论一下原因。(Days in the VIP downloaded a SPIHT algorithm to improve the paper, (Gengxing Yun, " based on improved SPIHT still image coding," Computer Knowledge and Technology: 5-year academic exchange-2 007), in accordance with this paper the improved algorithm Matlab to achieve, but found that the improved algorithm runs faster than the original algorithm is also slow, hope to have interested friends come to see, comment on why.)

This paper addresses the issues relating to the enforcement of robust stability when implementing the Adaptive Inverse Control (AIC) scheme. In this scheme, an adaptive FIR filter is added to a closed-loop system in order to reduce the output error caused by external disturbances, enhancing the performance achieved by linear time-invariant controllers alone.(This paper addresses the issues relating to theenforcement of robust stability when implementing the AdaptiveInverse Control (AIC) scheme. In this scheme, an adaptiveFIR filter is added to a closed-loop system in order toreduce the output error caused by external disturbances, enhancing the performance achieved by linear time-invariantcontrollers alone.)

依据感应电机实际参数，利用MATLAB的M函数编写程序，并进行实际的仿真(Based on the actual parameters of the induction motor using MATLAB M-function programming, and the actual simulation)

hybrid power train simulation

说明：  细菌觅食优化算法 ，解决比例积分控制器参数优化的程序，对初学细菌算法很有帮助。(Bacterial foraging optimization algorithm to solve PI controller parameter optimization procedure, useful for beginners bacterial algorithm.)

基于BP神经网络的R实现，改进了BP神经网络，可运行。(R implementation based on BP neural network)

best Frequency Modulation

利用MATLAB对原始数据特征提取（数据降维）((Data dimensionality reduction of raw data feature extraction using MATLAB))

用于实现灰度图像阈值分割的一维otsu方法，matlab源程序(Used to achieve gray image threshold segmentation of the one-dimensional Otsu method, matlab source)

经典的MUSIC算法，由特征值分解得到噪声子空间，再进行谱峰搜索(Classic MUSIC algorithm, the eigenvalue decomposition noise subspace, then the peak search)