WLS_MV

Earthquake Engineering and Structural Dynamics(You can input any number of stores by giving the mass, stiffness and damping values. Input the gamma and beta values which are related to Newmark Integration Mtd. Press Newmarks Integration button to input the values. Input the any number of storey that you expected to see the deflection for particular Earthquake. Press “Storey No” button to get that number. If you like only, you will input the period and press “Period” button. Finally press calculate button to see final results. Also you can see the both graphs in log scales also.(Please right click on the graph as shown above). You may see what type of analysis method is used. (Average acceleration relation ship or Linear variation of acceleration).)

用matlab实现了对Hindmarsh-Rose神经元模型各个参数的仿真。包括了HR神经元模型和主程序，下载即可执行。(Hindmarsh-Rose neuron is analyzed with matlab)

单信源情况下线阵的波束形成基本简单源程序，初学者参考(Single-source situation downline array beamforming basic simple source, beginners reference)

Obtain Quadrature Amplitude Modulation. Plot its BER vs SNR curve at different amplitudes.

Peak signal to noise ratio(psnr) of the image

计算统计手册采用matlab实现，书中详细介绍了数理统计的各种方法给出了对应的matlab程序，包括时下比较热门的非参数估计（PDF估计等）(There are wonderful books that cover many of the techniques in computational statistics and, in the course of this book, references will be made to many of them. However, there are very few books that have endeavored to forgo the theoretical underpinnings to present the methods and techniques in a manner immediately usable to the practitioner. The approach we take in this book is to make computational statistics accessible to a wide range of users and to provide an understanding of statistics from a computational point of view via algorithms applied to real applications.)

Matlab Optimization of braced structures

Efficient frontier from Yahoo or database data. (Efficient frontier from Yahoo or database data.)

说明：  matlab 系统仿真 实例第五章所有例子，可以学习下；(matlab simulation examples of Chapter V all the examples, you can learn from the next )

k-means clustering for image classification