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一个关于SVM支持向量机的计算例程, 用MATLAB做的,请多指教(one of the SVM SVM calculation routines, using MATLAB do, please enlighten)

Sharpness detection algorithm.

瑞利衰落信道条件下的MATLAB程序，是值得参考的程序(Rayleigh fading channels under the MATLAB program, the program is worth considering)

对正弦信号自相关和互相关运算的实验。在进行算法模拟时首先应对一个实时数字信号处理的任务选择一种方案和多种算法，用计算机高级语言如（c、Matlab等工具)验证算法能否满足系统的性能指标；然后从多种信号处理算法中找出最佳或准最佳算法。(right sinusoidal signal autocorrelation and cross correlation of the experimental operation. Conducting simulation algorithm deal with a first real-time digital signal processing tasks to choose a variety of programs and algorithms, Senior computer language such as (c, Matlab, and other tools) verification algorithm can meet the performance indicators; Then from a variety of signal processing algorithms to find the best or potential best algorithm.)

美国莱斯大学压缩感知稀疏学习工具箱，能把信号进行稀疏表示，进而实现远低于奈奎斯特抽样速率的压缩感知(Rice University study Toolbox sparse compressed sensing, sparse representation of the signal can, thus achieving much lower than the Nyquist sampling rate of the compressed sensing)

线性系统的时域分析法,涵盖各方面内容（包括稳定性分析）(The time-domain analysis of the linear system, covering all aspects of content (including stability analysis))

This is code for Haralick feature extraction for image in matlab. The basis for these features is the gray-level co-occurrence matrix. This matrix is square with dimension Ng, where Ng is the number of gray levels in the image. Element [i,j] of the matrix is generated by counting the number of times a pixel with value i is adjacent to a pixel with value j and then dividing the entire matrix by the total number of such comparisons made.

This file includes demodulation algorithm who is using and studying the matlab simulink. I hope this zip file would be helpful for them.

MATLAB图像处理源文件，每章节的对应matlab源代码已整理好，可对应ppt和视频配套学习(MATLAB image processing source files, each chapter corresponds matlab source code has been collated.)

使用最小二乘法对模型阶数和时滞未知的一种柔性机器人手臂进行辨识与建模。(Identification and modeling of a flexible robot arm with the least square method for model order and time delay.)