code-examples

susan matlab源码 FDTD教程 必看(susan matlab Fdtd)

This book is about communication system by matlab.

线性矩阵不等式的完整程序，对初学者来说是不错的资料，快下载吧。(LMI complete program for beginners is good information, fast to download it.)

Making Cylinder code for matlab using top and bottom point with radius

【谷速软件】红外与可见光图像自适应融合源代码 ( 在学习过程中作为参考使用)

基于MATLAB的KMEANS 聚类程序 程序和数据如下: (MATLAB-based clustering procedure KMEANS program and data are as follows:)

测试文本，选用著名的gettysburg这篇英文文本做为测试文本(Second, it fuses the features of the first singular value component and the second one, and then gets the complex feature vectors which reflect not only the statistic frequency but also the sequential structure of letters. In the end, the cosine similarity of texts is used to measure the similarity between the query and documents.)

说明：  用matlab语言实现的将图像的进行dpcm编码算法，之后进行图像重构，进行前后图像的对比。(With matlab language will be dpcm image coding algorithm, after the image reconstruction, the images before and after contrast. )

IS-95前向链路系统的仿真，包括扩频调制，匹配滤波，RAKE接收等相关通信模块。 (IS-95 forward link system simulation, including the spread spectrum modulation, matched filter, RAKE receiver and other related communication module.)

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 )