GA-and-CSA

dc to dc buck boost converter with variable frequency

EMD一维信号分解 ；有注释说明，方便阅读；(EMD-dimensional signal decomposition annotated instructions, easy to read )

M序列信号算法仿真在系统辨识中有着很大的应用前景。多谐差相方法辨识精度很高有着很苛刻的要求，要求已知辨识参数个数已知并且需要整周截断。而M序列信号的测试方法没有这个方面的要求。其辨识未知模型时，可以用最小二乘算法观察辨识系统的精度来确定模型的阶次。本算法里面不但给出了用于M序列生成的本原多项式计算方法，同时编写了M序列信号的生成算法，并编写了相关辨识方法的算法。(M sequence signal simulation algorithm for identification in the system have great application prospects. Identification of multi-harmonic differential phase method with high precision has very stringent requirements, demand parameters are known to identify the number of known and need to cut off the whole week. The M sequence signal testing methods do not have this requirements. Its identification unknown model, you can observe the identification system using least-squares algorithm to determine the accuracy of the model order times. This algorithm is used which not only gives the M sequence generated by primitive polynomial method of calculation as well as prepare the M sequence signal generation algorithm, and the preparation of the relevant identification method algorithms.)

Svm is algorithm which helps in classification of data

Wavelets and Filter Banks Wavelets and Filter Banks Mallat Mallat pyramid algorithm pyramid algorithm

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 )

This function produces an image of a 3D object defined by matrix a(l,m,n) in terms of voxels the image is a view after rotating the object by angles alfa and beta (in degree) b is the image and d is its ditance to the viewer matrix The first figure depicts the object using only its gray level values The second image depicts the object using some lighting effect rotate3d may be used for reorientation but the obtained image is planner

Tools to matlab optimization

说明：  基于boost电路的双闭环PI控制单相有源功率因数校正仿真模型(Single-phase Active Power Factor Correction Simulation Model of Double Closed-loop PI Control Based on Boost Circuit)

平面波展开法计算能带，计算速度快，资源占用少(Plane wave expansion method to calculate the energy band, fast calculation)