daima

说明：  实现了图像友RGB空间转换为Luv空间，函数以RGB图像为参数，输出Luv图像(Achieved image Friends of the RGB space is converted to Luv space, function to RGB image as a parameter, the output Luv image)

matlab program for power system optimzation using GA tool

Octave Neural Network rewritten to be compatible with Matlab.

说明：  给出了一个控制系统的模型，此模型采用ＭＡＴＬＡＢ模块搭建，解决跟踪问题(Gives a control system model, this model structures using MATLAB module to address the tracking problem)

二阶线性系统常规模糊滑膜控制仿真的M语言代码，对象为：G(s)=133/s(s+25)(Fuzzy linear systems control simulation of the M synovial language code)

无约束问题最优化方法的核心问题是选择搜索方向。 以正定二次函数为例，来观察两个方向关于矩阵Ａ共轭的几何意义(Unconstrained optimization problems are most core issue is to choose the search direction. In definite quadratic function, for example, to observe both directions on the matrix A conjugate geometric meaning)

this is the modulation techniques in matlab

优秀论文及配套源码。首先阐述了负荷预测的应用研究现状，概括了负荷预测的特点及其影响因素，归纳了短期负荷预测的常用方法，并分析了各种方法的优劣；接着介绍了作为支持向量机（SVM）理论基础的统计学习理论和SVM的原理，推导了SVM回归模型；本文采用最小二乘支持向量机（LSSVM）模型，根据浙江台州某地区的历史负荷数据和气象数据，分析影响预测的各种因素，总结了负荷变化的规律性，对历史负荷数据中的“异常数据”进行修正，对负荷预测中要考虑的相关因素进行了归一化处理。LSSVM中的两个参数对模型有很大影响，而目前依然是基于经验的办法解决。对此，本文采用粒子群优化算法对模型参数进行寻优，以测试集误差作为判决依据，实现模型参数的优化选择，使得预测精度有所提高。实际算例表明，本文的预测方法收敛性好、有较高的预测精度和较快的训练速度。(first expounds the recent application research of load forecasting, summarized the characteristics of load forecasting and influencing factors, summed up common methods of short-term load forecasting, and analyzed the advantages and disadvantages of each method then introduced statistical learning theory and the principle of SVM as the basis of support vector machine (SVM ) theory, SVM regression model is derived this paper adopted least squares support vector machine (LSSVM) model, according to the historical load data and meteorological data of a certain area of Zhejiang Taizhou, Analysised the various factors affecting the forecast, summed up the regularity of load change , amended "outliers" in the historical load data,the load forecasting factors to be considered were normalized. The two parameters of LSSVM have a significant impact on the model, but it is still soluted based on the experience currently. So, this paper adopted particle swarm optimization algorithm to optimized )

说明：  多个系统数据同步公共部分函数源代码，太麻烦了，每次说明都要这么多字(data synchronization system over some public function source code, too cumbersome, each note must so many characters)

bpsk,qpsk误码分析，基于高斯白噪声信道(Error analysis of BPSK and QPSK)