熵权法

用matlab编写的数字信号处理源码，包含很多常用信号分析功能，非常使用。(using Matlab prepared by the Digital Signal Processing Source include many commonly used signal analysis functions, very used.)

我自己用matlab编写的文件,对于基础的图像处理学习者有很大帮助,文件大约4kb.用于对图像的基础处理时检测图像质量.(File matlab prepared for my own use, for the basic image processing learners great help file about 4kb. Used for basic image processing to detect image quality.)

PROJECT 02-02 Reducing the Number of Intensity Levels in an Image (a) Write a computer program capable of reducing the number of intensity levels in a image from 256 to 2, in integer powers of 2. The desired number of intensity levels needs to be a variable input to your program. (b) Download Fig. 2.21(a) from the book web site and duplicate the results shown in Fig. 2.21 of the book. Laboratory Projects_DIP3E 的02-02項目(PROJECT 02-02 Reducing the Number of Intensity Levels in an Image (a) Write a computer program capable of reducing the number of intensity levels in a image from 256 to 2, in integer powers of 2. The desired number of intensity levels needs to be a variable input to your program. (b) Download Fig. 2.21(a) from the book web site and duplicate the results shown in Fig. 2.21 of the book.)

压缩感知：2维压缩感知SL0重构算法，涉及两个测量矩阵，两个方向进行。是本人精心编写调试好的，请放心使用。(cs:2 dimensional compressive sensing using 2D_SL0 reconstruction algorithm, involving two measurement matrices, two directions.)

《MATLAB神经网络30个案例分析》中的第9个例子，案例9 离散Hopfield神经网络的联想记忆—数字识别。希望对大家有一定的帮助！(The MATLAB neural network analysis of 30 cases of example, 9, 9 cases of discrete Hopfield neural network associative memory- digit recognition. Hope to have certain help to everybody! )

Aunthetication token.

RLS算法 matlab例子 内有注释 可供参考(Notes RLS algorithm matlab example for reference)

Fisher分类函数 对应《模式识别与智能计算的matlab实现》中的例2.4(Pattern Recognition and Intelligent Computing matlab achieve the Fisher classification function corresponding Example 2.4)

含有时滞的奇异切换系统的稳定性分析判据,该判据是个时滞无关的判据，具有更小的保守性(Delay-independent criteria for exponential admissibility of switched descriptor delayed systems)

This is level-set image segmentation method.