ssvm

file for mosaicing image

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.)

说明：  多目标遗传算法是NSGA-II[1]（改进的非支配排序算法）,该遗传算法相比于其它的多目标遗传算法有如下优点：传统的非支配排序算法的复杂度为 ，而NSGA-II的复杂度为 ，其中M为目标函数的个数，N为种群中的个体数。引进精英策略，保证某些优良的种群个体在进化过程中不会被丢弃，从而提高了优化结果的精度。采用拥挤度和拥挤度比较算子，不但克服了NSGA中需要人为指定共享参数的缺陷，而且将其作为种群中个体间的比较标准，使得准Pareto域中的个体能均匀地扩展到整个Pareto域，保证了种群的多样性。（消除了共享参数）。(Multi-objective genetic algorithm is nsga-ii [1] (improved non-dominant sorting algorithm), which has the following advantages compared with other multi-objective genetic algorithms: the complexity of the traditional non-dominant sorting algorithm is, while the complexity of nsga-ii is, where M is the number of objective functions and N is the number of individuals in the population.The introduction of elite strategy to ensure that some good individuals in the evolutionary process will not be discarded, thus improving the accuracy of the optimization results.The comparison operator of crowding degree and crowding degree not only overcomes the defect that NSGA needs to specify the Shared parameter artificially, but also takes it as the comparison standard between individuals in the population, so that individuals in the quasi-pareto domain can uniformly expand to the whole Pareto domain, ensuring the diversity of the population.(eliminating Shared parameters).)

This is a Matlab v6.5 implementation of the Lagrange interpolation algorithm.

薛定宇 控制系统计算机辅助设计（第二版） 源代码/源程序(On Compensation Control System Computer Aided Design (Second Edition) source code/source)

LTE下行链路的仿真代码 基本模块都有 对系统仿真很有帮助(LTE downlink simulation code module has a helpful system simulation)

VC和MATLAB混合编程 使用MATLAB工具函数计算(VC and hybrid programming using MATLAB tool MATLAB function to calculate)

MATLAB Simulation文件，摩托车仿真，具体操作步骤见说明文档(MATLAB Simulation file, motorcycle simulation, specific steps see documentation)

很多经典函数的图形演示，让你更直观的了解一些经典函数的模样。其中的函数可以直接用来参考应用(Many of the classic function of graphical presentation, make you more intuitive understanding of some of the classic function looks like. One of the functions can be directly used to refer to the application)

改进的粒子群算法，有更好的性能，提高了算法的搜索能力(Improved particle swarm optimization, better performance, improved search ability of the algorithm)