fullyctrlRL

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.)

matlab语言与控制系统仿真实训教程的simulink仿真文件(the matlab language with the control system simulation training tutorial simulink simulation file)

基于牛顿-拉夫逊法的电力系统潮流计算程序，matlab(Based on the Newton- Raphson method of power flow calculation program, matlab)

系统辨识与自适应控制程序 小程序，请指教！(System identification and adaptive control procedures)

IDW（距离权倒数插值法）是空间插值中最常用的插值方法之一。本程序基于MATLAB开发，功能齐全，希望用得开心。(IDW (interpolation from the bottom right) is the most commonly used spatial interpolation of the interpolation methods. The program is based on MATLAB development, full-featured, in the hope joy.)

基于matlab的基本粒子群优化算法，可应用与最优潮流计算等(Matlab-based optimization of the particle swarm algorithm can be applied with optimal power flow calculation)

说明：  服务桥结构静态参数识别算法Levenberg-Marquardt（L-M方法）matlab源程序(Algorithm for static parameter identification of service bridge structures Levenberg-Marquardt (L-M method) matlab source program)

能量算子的matlab实现程序及其详细算法，可用于包络解调，瞬时频率计算等方面(Energy operator of matlab realization process and its detailed algorithms, can be used for envelope demodulation, instantaneous frequency calculation, etc.)

This code uses MATLAB s Internal Functions and Memory Preallocations to apply a Fast Implementation of kmeans algorithm. This is a efficient code for clustering a gray or Color image or it can be used for clustering a Multidimensional Array. Comparison. 1. Faster than MATLAB s internal kmeans function. 2. Consistant Output than internal kmeans. 3. 100 convergence.

Updating MATLAB(R) figure inserted on a Excel(R) Sheet