libsvm

此文件为FIR滤波器设计.m源文件，用于matlab仿真中使用(this document FIR filter design. M source document for the use of Matlab simulation)

解决中国31个城市周游问题，已注解，可直接运行(31 cities to travel around China to solve the problem, annotated, can be run directly)

主成分分析PCA(含有详细推导过程以及案例分析matlab版).doc(Principal component analysis PCA (containing detailed derivation and case studies matlab version). Doc)

排队论，讨论单窗口单队情形，两窗口单队情形。分别计算平均等待时间，平均逗留时间，平均每分钟服务的顾客人数。(Queuing theory to discuss the situation single-window single team, two windows one team situation. Calculate the average waiting time, average length of stay, the average number of customers per minute service.)

相控阵天线的方向图（切比雪夫加权），DC-DC部分采用定功率单环控制，esprit算法对有干扰的信号频率进行估计。( Phased array antenna pattern (Chebyshev weights), DC-DC power single-part set-loop control, esprit algorithm signal frequency interference can be assesse.)

this code used for mimo radar code detection.

matlab绘图结果在VB的picture控件中显示(matlab drawing the results of the picture controls in VB to display)

dsb调制与解调的MATLAB的M文件实现(dsb modulation and demodulation realize MATLAB M-files)

Prony算法工具箱。Prony方法是用一组指数项的线性组合来拟和等间距采样数据的方法,可以从中分析出信号的幅值、相位、阻尼因子、频率等信息。considerations including data preprocessing, model order selection, model order selection criteria, signal subspace selection, signal and noise separation, root inspection and assessing residuals. The PTbox provides flexibility to compare and display analysis results simultaneously for several parameter variations.(Prony algorithm toolbox. Prony method is used for a group of items to be linear combination of distance and other data sampling methods be able to analyze the signal amplitude, phase, the damping factor, frequency, and other information. Considerations including data preprocessing , model order selection, model order selection criteria. signal subspace selection, signal and noise separation, root inspection and assessing residuals. The P Tbox provides flexibility to compare and displ ay analysis results simultaneously for severa l parameter variations.)

贝叶斯决策实验，matlab实现方法，概率分布(Bayesian decision experiment, matlab implementation)