yaojin

说明：  VC与MATLAB混合编程，示范例子 使用C++开发(VC versus MATLAB )

Chinese remainder theorem

基于GA优化的SVM算法，它可以被用于预测分类(SVM algorithm based on GA optimization for prediction classification)

运用MATLAB编程并结合simulink解决简单的电路问题。 自选题目：图1所示为典型的直流电阻电路[3], 含有电压控制的受控电流源VCCS，其中，R1=1Ω,R2= 2Ω, R3=3Ω,US=10V, IS=15A, VCCS= ，现需分析计算电流i1和电压u2 (Combined with the use of MATLAB simulink program to solve simple circuit problems. Optional Title: Figure 1 shows a typical DC resistance of the circuit [3], with voltage-controlled current source controlled VCCS, which, R1 = 1Ω, R2 = 2Ω, R3 = 3Ω, US = 10V, IS = 15A, VCCS =, now need to be analyzed to compute the current and voltage u2 i1)

VARHMMBOX, version 1.1, Iead Rezek, Oxford University, MAR 2002 Matlab toolbox for Hidden Markov Models (Adapted from Machine Learning Toolbox Version 1.0 01-Apr-96 Copyright (c) by Zoubin Ghahramani, University of Toronto) The software uses some NETLAB routines (see http://neural-server.aston.ac.uk/netlab/index.html) so you ll need to have NETLAB on your search path See the file VERSION for what s new in this version.

This MATLAB code performs image deconvolution.

用MATLA实现机器学习中的批处理梯度下降法和随机梯度下降法(Batch gradient descent method and stochastic gradient descent method in machine learning using MATLA)

添加水印，在图项中添加，matlab，实现图像的保护等等 (Add watermark, add items in the map, matlab, image protection, etc.)

assingment problem With this package, I provide some MATLAB-functions regarding the rectangular assignment problem. This problem appears for example in tracking applications, where one has M existing tracks and N new measurements. For each possible assignment, a cost or distance is computed. All cost values form a matrix, where the row index corresponds to the tracks and the column index corresponds to the measurements. The provided functions return an optimal or suboptimal assignment - in the sense of minimum overall costs - for the given matrix.

说明：  趋势EA，不加仓，不网格，每单都带止损止盈，加载周期30分(Trend EA, no warehousing, no grid, stop-loss and stop-profit for each single, loading cycle 30)