bp-ga

gray level run length martix

说明：  基于协同优化算法的多目标轧制规程优化设计(Optimize the design of rolling schedule based on the multi-objective collaborative optimization )

基于灰度图像的目标物的提取、边缘检测、迭代收缩(Extract target grayscale images based on edge detection, iterative shrinkage)

This script will setup the nonlinear simulation (UAV_NL.mdl) and call trim and linearization routines. Select the desired aircraft here in this script, via the "UAV_config()" function call.

Matlab辅助激光光学分析与应用——武汉某光电公司的技术总结。(Matlab-assisted laser optics analysis and applications- Wuhan, a photovoltaic company s technical summary.)

matlab数字信号处理（实例 _实现）PDF,数字信号处理常用的MATLAB程序及常用函数(matlab Digital Signal Processing (examples _ realization) PDF, digital signal processing and common procedures commonly used MATLAB function)

MATLAB命令大全，方便你检索在MATLAB使用过程中的各种命令！(Guinness MATLAB command to facilitate retrieval in MATLAB you use a variety of command!)

采用matlab进行GUI设计的一个实例(GUI design using matlab to an instance of)

说明：  MATLAB 代码 第1章 BP神经网络的数据分类——语音特征信号分类 第2章 BP神经网络的非线性系统建模——非线性函数拟合 第3章 遗传算法优化BP神经网络——非线性函数拟合 第4章 神经网络遗传算法函数极值寻优——非线性函数极值寻优 第5章 基于BP_Adaboost的强分类器设计——公司财务预警建模 第6章 PID神经元网络解耦控制算法——多变量系统控制 第7章 RBF网络的回归--非线性函数回归的实现 ....等58章(MATLAB code The first chapter is BP neural network data classification -- speech characteristic signal classification The second chapter is the nonlinear system modeling of BP neural network nonlinear function fitting The third chapter, genetic algorithm optimization BP neural network - nonlinear function fitting The fourth chapter, neural network, genetic algorithm, function extreme value optimization nonlinear function extremum seeking The fifth chapter is based on BP_Adaboost's strong classifier design -- the company financial early-warning model The sixth chapter is PID neural network decoupling control algorithm multivariable system control The seventh chapter is the regression of RBF network the realization of nonlinear function regression .........the last is 58 chapters)

BPSK程序，完成二进制调制过程，用于仿真，初步认识MATLAB仿真过程。(BPSK program, the completion of the binary modulation process for the simulation, an initial understanding of MATLAB simulation.)