dbscan

介绍了matlab中常用到的函数和一些相关的使用法则对初学者非常有用(Describes the commonly used matlab functions and some related to the use of law is very useful for beginners)

EEG brain signal anlaysis codes. Extract event-related potential (ERP) compoents from brain signal. Estimate ERP waveforms, and the assoimated single-trial latencies and amplitudes. Estimate spectrum of on-going activities. Two algoithms, dVCA and AESO, are implemeneted. Could be useful for researchers and students in biomeical engineering.

这是 Registered DIPUM Toolbox v2.0.1 m code 版本 对图像处理非常有用(This is the Registered DIPUM Toolbox v2.0.1 m code version is very useful for image processing)

本算法是个B样条曲线拟合算法，包括2D的和3D的两种曲线拟合算法。用户可以自己设定拟合的点数，也可以让算法根据拟合效果自动确定。(This algorithm is a B-spline curve fitting algorithms, including 2D and 3D two curve fitting algorithm. Users can set their own fitting points, but also allows the algorithm automatically determined according to the fitting effect.)

simulation of electromagnetic by 1d FDTD

自适应数值积分算法， 自适应数值积分算法， 自适应数值积分算法，(Adaptive numerical integration algorithm, adaptive numerical integration algorithm, adaptive numerical integration algorithm,)

基于NPC/H桥三相五电平逆变器的七段式SVPWM控制策略仿真(Seven-stage SVPWM control strategy simulation based on NPC/H bridge three-phase Five-Level Inverter)

利用MATLAB进行仿真，对图像进行dct变换，探究变换后与原图像的差别(Using MATLAB simulation, the image dct transform, transform and explore the difference between the original image)

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：  knn分类程序，基于matlab开发 (Commission classification procedure based on the development of Matlab)