bat_algorithm

遗传算法中的简单遗传算法，用matlab实现。(genetic algorithm simple genetic algorithm, using Matlab to achieve.)

signals and systems laboratory with matlab

basic signal plotting exponential

实现输入一串数字，然后matlab可以将数字对应的蜂鸣音播放出来（类似于电话的拨号）(Achieve input a string of numbers, then you can figure corresponding matlab beep play out (similar to dial-up phone))

伪彩色图、等高线图、三维曲面图matlab例程。数据来自2011年全国大学生数模竞赛本科组A题。 (Pseudo-color map, contour, 3D surface chart matlab routine. Data the 2011 National Undergraduate Mathematical Contest in Modeling undergraduate group A title.)

实现电力线信道通信建模及其基于OFDM调制系统的设计与仿真(To realize power line communication channel modeling and its design and simulation based on OFDM modulation system )

给出了用MATLAB实现FFT算法，压缩包内还有源程序(Given by MATLAB realize FFT algorithm, compressed source code package also)

本程序主要是关于基本的music的MATLAB仿真，是关于这方面的一个例子，由仿真结果可以看出这个程序的代表性。(This procedure is mainly on the basic music of the MATLAB simulation, is an example in this regard, the simulation results show that the representation of this process.)

本书基于MATLAB的图像处理工具箱,全面系统介绍了图象处理工具箱在图形绘制,图像几何变换,图像增强,小波分析和分形几何用于图像处理,以及图形用户界面设计等在工程中的实际应用.(book based on MATLAB Image Processing Toolbox. a comprehensive system of image processing toolbox in graphics rendering, image geometry transform, image enhancement, Wavelet analysis and fractal geometry for image processing, and graphical user interface design project in the practical application.)

包括kf，ekf，pf，upf可以自己定制模型参数，完成滤波(ReBEL currently contains most of the following functional units which can be used for state-, parameter- and joint-estimation: Kalman filter Extended Kalman filter Sigma-Point Kalman filters (SPKF) Unscented Kalman filter (UKF) Central difference Kalman filter (CDKF) Square-root SPKFs Gaussian mixture SPKFs Iterated SPKF SPKF smoothers Particle filters Generic SIR particle filter Gaussian sum particle filter Sigma-point particle filter Gaussian mixture sigma-point particle filter Rao-Blackwellized particle filters The italicized algorithms above are not fully functional yet (or included in the current release), but will be in the next or future releases. The code is designed to be as general, modular and extensible as possible, while at the same time trying to be as computationally efficient as possible. It has been tested with Matlab 7.2 (R2006a). )