fingfang_v27

Introduction to MATLAB - Sikander M. Mirza.pdf

matlabFEM is fem lab progrma source code to solve equation diferential

使用Matlab编程实现发送端信源编码（图像压缩）和接收端信源解码（图像重建），其中的编解码算法可采用基于DCT变换的JPEG图像压缩标准；测试图像加噪，然后对去噪后的图像进行压缩与重建，分析压缩性能；研究基于下采样和内插的图像压缩算法；可将8bit/pixel灰度图像扩展至24bit/pixel彩色图像，或者采用无损压缩算法对图像压缩。(Sender using the Matlab programming source coding (image compression) and the receiver source decoding (image reconstruction), one of the decoding algorithm can be used DCT-based JPEG image compression standard test image with noise, then the denoised image compression and reconstruction, compression performance analysis of down-sampling and interpolation based on image compression algorithm 8bit/pixel grayscale images can be extended to 24bit/pixel color images, or the use of lossless compression algorithms for image compression. )

MATLAB编程实例100例。。。。。。。。。。(100 cases of examples of MATLAB programming. . . . . . . . . .)

Binary frequency shift keying

胡广书现代信号处理导论随书光盘，包括各个章节，很全，大部分能直接拿来用，很实用(Hu Guang-shu of modern signal processing Introduction to CD-ROM)

基于短时傅里叶变换的对鼾声信号进行分析，可以计算一些判断OSAHS的指标。(snoring analysis based on STFT)

The matlab code is for calling the Halftoning algorithm for colored images using the Jarvis method.

粒子优化通用程序，可以在MATLAB上运行(PSO)

本文将排课五要素绑定、封装成课元、课栈两个向量，并以二维权值矩阵描述课元 和课栈之间的关联系。 提出了最佳匹配和遗传算法的排课算法，以随机生成的二维数字矩阵来反映课元和 课栈的关联权重，对数字矩阵组处理和最佳匹配得到的匹配偶图组为遗传算法的初始种 群，以排课各种原则的加权和为目标函数，在遗传算子控制下迭代来寻求更优的匹配结 果即使目标函数最小的偶图匹配结构，进而得到满意的排课结果。 提出了关联匹配和禁忌搜索的排课算法，以随机二维数字矩阵描述课元和课栈之问 的关联权重，按照重权优先并根据正确性原则进行约简，获得课元和课栈之间的匹配偶 图。在此基础上，引入禁忌搜索算法，以排课的完备性原则、合理性原则和人性化原则 的加权和为目标函数，以随机二维权值矩阵生成的匹配偶图为初始解，对二维权值矩阵 进行扰动构成搜索邻域，以生成的匹配偶图为禁忌对象，采用全局藐视准则，获得最优 的排课方案。 以Matlab为平台，利用Excd数据库和Mallab的互联实现数据交换，编写了两套 算法的应用程序，通过实例来验证两套排课算法，结果表明两套算法是可行的。(Arranging the five elements of this paper, binding, packaging into a class element, class stack of two vectors and matrices described by two classes per Rights And the relationship between class stack link. Offers the best match and Genetic Algorithm Platoon algorithm to randomly generated two-dimensional figures to reflect the class element and matrix Class stack associated with weight, the digital matrix group received treatment and the best matching group bipartite graph matching the initial kind of genetic algorithm Group to the weighted course arrangement of principles and the objective function, under the control of the genetic operator iteration to seek the better match Results Results even if the objective function structure of the smallest bipartite graph matching, and then Timetabling satisfactory results. Match the proposed association Timetabling algorithm and tabu search, a random two-dimensional digital matrix element and the class description class stack of Q)