MatlabWaveletToolbox

NSGA原代码，很多人在找这个，对搞智能优化很有帮助(NSGA original code, a lot of people looking for this, very helpful to engage in intelligent optimization)

说明：  matlab遗传算法的程序，希望能够对大家有用处！(Matlab GA procedures, we hope to be able to be useful!)

HOUGH变换进行图像分割，matlab实现，先进行灰度变换(HOUGH transform for image segmentation, matlab implementation, the first gray-scale transformation )

自定义MATLAB函数的输入输出变量个数控制，实现简单的加法运算(Since the number of control input and output variables defined MATLAB function, simple addition)

本文件夹共三个matlab文件和一个word文档， 内容分别为用MATLAB验证时域抽样定理，连续系统的频域分析和连续系统的频域分析。matlab刚捡起来，望大家多多指教与探讨。(A total of three of the matlab folder of documents and a word document, the contents of MATLAB were used to verify time-domain sampling theorem, continuous system for frequency domain analysis and frequency domain analysis system. matlab to just pick up, hope you and explore the exhibitions.)

独立成份分析（ＩＣＡ）以及ｗｉｎｎｅｒ滤波 Source separation of complex signals with JADE. Jade performs `Source Separation in the following sense: X is an n x T data matrix assumed modelled as X = A S + N where o A is an unknown n x m matrix with full rank. o S is a m x T data matrix (source signals) with the properties a) for each t, the components of S(:,t) are statistically independent b) for each p, the S(p,:) is the realization of a zero-mean `source signal . c) At most one of these processes has a vanishing 4th-order cumulant. o N is a n x T matrix. It is a realization of a spatially white Gaussian noise, i.e. Cov(X) = sigma*eye(n) with unknown variance sigma. This is probably better than no modeling at all...( Source separation of complex signals with JADE. Jade performs `Source Separation in the following sense: X is an n x T data matrix assumed modelled as X = A S+ N where o A is an unknown n x m matrix with full rank. o S is a m x T data matrix (source signals) with the properties a) for each t, the components of S(:,t) are statistically independent b) for each p, the S(p,:) is the realization of a zero-mean `source signal . c) At most one of these processes has a vanishing 4th-order cumulant. o N is a n x T matrix. It is a realization of a spatially white Gaussian noise, i.e. Cov(X) = sigma*eye(n) with unknown variance sigma. This is probably better than no modeling at all...)

说明：  对于较低版本的matlab用户可以直接进行DW检验！但是要求残差向量要大于15(it can do wd)

Paper Abstract – An adaptive control of Distributed Generation (DG) to provide predictable active power output at the primary distribution substation is described. Often, distribution networks accommodate renewable energy different energy sources and thus using different energy conversion sources. As the amount of generation that comes intermittent renewable sources (e.g. wind energy) increases, network operators start to concern with the uncertainty of generation. However, when the power output intermittent renewable sources is predicted, the network operators can reduce the operational costs of the network and the DG owners may go on the market. Thus, our challenge with this work was to develop an algorithm which can predict the active power output the aggregation of wind and biomass energy at the primary distribution substation of a typical distribution network. Wind and biomass energy plant are onto the same distribution network but not necessarily onto the same feeder.

独立分量分析（ICA）以非高斯源信号为研究对象，在统计独立的假设下，对多路观测到的混合信号进行盲信号分离，已广泛应用于无线通信、生物信号提取、语音信号处理、图像处理和噪声抑制等领域。 (The independent component analysis (ICA) addresses non-Gaussian source signals under amusing independent each other, it performs blind separation for multi-channel observed signals. It has widely applied in wireless communication, biological signals extraction, audio signal processing, image processing, and noise reducing and so on.)

matlab经典绘图案例。包括三维曲面z=x^2+y^2的动画、正弦曲线的动画、切片图、向量图、三维彗星图、三角形网格图、三角形表面图、球面、等值线图、三维瀑布图、三维火柴杆图、三维散点图、柱形图、三维条形图、三维饼图、带形图、曲线图、高斯分布函数的曲面图、高斯分布函数的网格图、5阶高斯分布矩阵、梯度场矢量图、罗盘图、玫瑰花图、羽列图、数据向量的单轴对数坐标图、矩阵的条形图 矩阵的面积图、二维饼图、散点图、误差图、火柴杆图和碗状曲面图等等。 (Drawing matlab classic case. Including three-dimensional surface z = x ^ 2+ y ^ 2 animation, animated sine curve, slices, vector graphics, three-dimensional map comet, triangular grid map, triangular surface plots, spherical, contour, 3D waterfall, three-dimensional grid graph matchstick figure, three-dimensional scatter plot, bar chart, the three-dimensional bar charts, three-dimensional pie charts, strip charts, graphs, surface, Gaussian distribution function, the Gaussian distribution function, fifth-order Gaussian distribution matrix gradient vector field, compass, rose diagram, feather column chart, the data vector uniaxial logarithmic graph, bar graph matrix Area chart matrix, two-dimensional pie charts, scatter plots, error plots, matchstick figure and bowl surface map and so on.)