buxiangguanqingxing

btt源码 六自由度仿真，全弹道仿真，倾斜转弯(btt source 6-DOF simulation)

Fisher Linear Discriminant for text classification

模式识别的批处理matlab源代码，包括学习文档，和实验图像。(Pattern recognition matlab source code of the batch, including the study documentation, and experimental image.)

A Guide to MATLAB for Beginners and Experienced Users - Hunt Lipsman & Rosenberg(A Guide to MATLAB for Beginners and Experienced Users- Hunt Lipsman & Rosenberg)

FFH中传统门限的比较获取，SNR的不同，BER不同，从中最佳(FFH traditional door limit access to the SNR different BER, from which the best)

遗传算法解决背包问题。内含genetic工具包。(Genetic algorithm to solve knapsack problem. Contains genetic toolkit.)

基于SimMechanics的刚体系统建模的案例fourbar(SimMechanics modeling)

ve-DYNA® 为用户提供了车辆动力学、车辆非线性行为的可配置仿真模型。用户根据自己的工程问题选择合适的车型（轿车，货车，拖车）和适当的版本（低级，标准，高级）就能实现不同的应用。用户基于模型就能开发自己的控制算法或者部件，然后通过离线仿真和硬件在回路仿真来进行检验和验证。只需要进行鼠标键盘的操作，就可以对种种的动力学问题进行分析，比如悬架动力学，车辆动力性或操纵稳定性。这样 就 能够减少昂贵而且费时甚至是危险的实车试验。可以在无人监控的情况下完成整个的测试、优化和系统验证 。本文为veDYNA软件的相关例程介绍。(ve-DYNA ® provides users with vehicle dynamics, nonlinear behavior can be configured vehicle simulation model. Users according to their engineering problems select the appropriate models (cars, trucks, trailers) and the appropriate version (low, standard, advanced) will be able to implement different applications. Users can develop their own model-based control algorithms, or parts, and then off-line simulation and hardware in the loop simulation to be tested and verified. Only for mouse and keyboard operation, it can analyze the various dynamics, such as suspension dynamics, vehicle dynamic performance or handling and stability. This can reduce the costly and time-consuming and even dangerous in real vehicle tests. No one can monitor the situation in the completion of the testing, optimization and system verification. This article related to software routines for the veDYNA introduction.)

这是中国数学建模中编程交流上贪婪算法内容，里面提供了很多贪婪算法的例子(This is the exchange of mathematical modeling in the programming content on the greedy algorithm, which provides many examples of greedy algorithm)

开发环境:Matlab 简要说明:动量-自适应学习调整算法。在实际应用中，原始的BP算法很难胜任，因此出现了很多的改进算法。BP算法的改进主要有两种途径，一种是采用启发式学习方法，另一种则是采用更有效的优化算法。本例采用动量BP算法，来实现对网络的训练过程，动量法降低了网络对于误差曲面局部细节的敏感性，有效地抑制网络陷于局部极小。(development environment : Matlab Brief Description : Momentum-adaptive learning algorithm adjustments. In practical application, the original BP algorithm competence, resulting in a lot of improved algorithm. BP algorithm improvements There are two main ways of using a heuristic approach to learning Another is the use of a more effective method of optimization. Momentum cases using the BP algorithm to achieve the network training process, Momentum for reducing error of the network for local surface details of the sensitivity, to effectively curb the network into local minima.)