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ACE自适配通信环境（ADAPTIVE Communication Environment）是可自由使用、开放源码的面向对象（OO）框架（framework），它实现了许多用于并发通信软件的核心模式。ACE提供了一组丰富的可重用C++包装外观（wrapper facade）和框架组件，可跨多种平台完成通用的通信软件任务，其中包括：事件多路分离和事件处理器分派、信号处理、服务初始化、进程间通信、共享内存管理、消息路由、分布式服务动态（重）配置、并发执行和同步，等等。(ACE Adaptive Communication Environment (ADAPTIVE Communication Environment) is free to use, open source object-oriented (OO) framework (framework), it implements a number of concurrent communication software for the core model. ACE provides a rich set of reusable C++ Packaging appearance (wrapper facade) and the framework components, can be a variety of cross-platform communications software to complete common tasks, including: multi-way separation of incident and event processor assignment, signal handling, service initialization, interprocess communications, shared memory management, message routing, distributed service dynamically (re) configuration, concurrent execution and synchronization, and so on.)

计算脑电信号非线性参数，心电信号分析与滤波以及去基线漂移(Calculation of EEG non-linear parameters, ECG analysis and filtering, as well as to baseline drift)

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OFDM系统中用限幅法降低系统的峰值平均功率比(OFDM system limiting method used to reduce the peak-to-average power ratio)

Press Numerica Methods in Engineering with MATLAB 2005

瑞利衰落信道的Matlab仿真模型程序，这个是关于OFDM 的循环卷积源代码(Rayleigh fading channel simulation model of the process, this is the cycle of OFDM convolution source code)

MATLAB+7.0从入门到精通-D0613075，里面有2-15章所有的程序。(MATLAB+7.0 Mastering,including 2-15 Chapter program)

实现mimo-ofdm系统的交织功能，可供参考(Implement the mixed function of mimo- ofdm system, available for reference)

This program will detect the license plate region with segmentation and extraction and recognition

matlab 遗传算法GA，粒子群算法PSO,蚁群算法AS 前段时间上智能计算方法实验课上，自己做的程序。帖到这里，希望有人能改进它们，交流经验这样更有价值。 遗传算法解决最小生成树问题，PURFER编码。 粒子群算法做无约束最优化问题。 蚁群算法解决TSP问题。 如果有宝贵经验希望能交流一下，谢谢，呵呵(matlab genetic algorithm GA, particle swarm optimization PSO, ant colony algorithm for calculation of AS some time ago on the intelligent test classes, make their own procedures. Quote here, hope someone can improve them, and exchange of experience which is more valuable. Genetic algorithm to solve the minimum spanning tree problem, PURFER coding. Particle swarm optimization to do unconstrained optimization problem. Ant colony algorithm to solve the TSP problem. If there is hope to exchange our experience, thank you, He He)