capacity_comparison_bidirectional

遗传算法是一种进化算法，应用广泛，此文件包含基本遗传算法，顺序选择遗传算法，适值函数标定的遗传算法，大变异遗传算法，自适应遗传算法，双切点交叉遗传算法，多变异位自适应遗传算法matlab源代码，供大家参考(Genetic algorithm is an evolutionary algorithm, widely used, this file contains the basic genetic algorithm, genetic algorithm selection order coincided with the genetic algorithm calibration function, a large variation of genetic algorithm, adaptive genetic algorithm, two-cut point crossover genetic algorithm, variable ectopic Adaptive genetic algorithm matlab source code for your reference )

CRC16 Algorithms and Test Example

8PSK 调制，AWGN信道下的信道容量的matlab 仿真程序。(8PSK modulation, channel capacity under AWGN channel matlab simulation program.)

MATLAB实现多属性目标决策选择，从而选择最优的决策(MATLAB to achieve multi-attribute objective decision making the choice to select the optimal decisions)

ECG Signal Analysis and Classification using Data Mining and Artificial Neural Networks

Windowed Fourier transform for fringe pattern analysis (with GUI) (• Run WFT in MATLAB environment. All processed data are automatically saved in result.mat 4. File list o wft2fw.m: the basic WFT algorithm. o unwrapping_qg_trim.m: quality guided phase unwrapping o WFT.m+WFT.fig: WFT overall interface o WFTKernel.m+WFTKernel.fig: interface for WFT parameter selection o imwritescale: to save data into image o readme.docx: this file. • 5. Notice Though wft2fw.m has been used by us for some years, the GUI was developed quite recently. The purpose is to make it easier to be used. Please feedback bugs to mkmqian@yahoo.com.sg. For more information, please refer to www.ntu.edu.sg/home/mkmqian. )

很好的卡尔曼滤波器，应实现过了，程序中有解释说明部分，只须修改参数即可(Good Kalman filter should be realized, the program has some explanation, you can only modify the parameters)

D-S证据理论数据融合，包括压缩比、运行时间和计算复原图像的峰值信噪比,合成孔径雷达（SAR)目标成像仿真。( D-S evidence theory data fusion, Including compression ratio, image restoration computing uptime and peak signal to noise ratio, Synthetic Aperture Radar (SAR) imaging simulation target.)

又一个很好的MATLAB应用范例。是关于MATLAB在upf领域的应用问题。(a very import tings!)

The book is organized for use as a text for an introductory course in stochastic processes at the senior level and as a?rst-year graduate-level course in Kalman ?ltering theory and application.It could also be used for self-instruction or for purposes of review by practicing engineers and scientists who are not intimately familiar with the subject.The organization of the material is illustrated by the following chapter-level dependency graph,which shows how the subject of each chapter depends upon material in other chapters.The arrows in the?gure indicate the recommended order of study.Boxes above another box and connected by arrows indicate that the material represented by the upper boxes is background material for the subject in the lower box.