Matlab_Packages.tgz

matlab中的相关算法已通过验证，以及声音谱的对比(matlab related algorithms have been validated, as well as the voice of spectral contrast)

通过主成分分析和偏最小二乘分析，然后画出数据的PCA主轴和PLS主轴(Principal component analysis and partial least squares analysis, and then draw the PCA and PLS spindle axis data)

多因子量化选股策略，包括数据导入，分组，回测分析(Multi-factor stock selection strategies to quantify, including data import, grouping, backtesting analysis)

采用rls算法对多径信号下到达波束的形成，其在不同情况下的学习速度(Rls algorithm for multipath signals to reach the formation of the beam, the speed of their learning in different situations )

2008年数码相机matlab源代码，利用ransac仿射算法，分享了，大家训练时可以参考(2008 digital camera matlab source code, the use of ransac affine algorithm, shared, and we can refer to training)

包含了几乎所有的聚类算法，用matlab实现的。里面有demo示例，可直接运行。(Contains almost all of the clustering algorithm, implemented using matlab. There are demo example, can be directly run.)

本书以有限单元基本理论为重点，以MATLAB程序为平台，以工程实例为背景，介绍 了有限元法及其程序设计方法。 本书讲述结构分析中有限元法的基本原理，单元类型包括平面杆系，空间杆系，平面等 参元，空间等参元，薄板壳单元和厚板壳单元等。内容涉及杆系结构、平面问题、空间问题和板壳问题。以结构线弹性静力分析为主，同时也讲述了结构的振动、稳定和动力响应分析。(This book is the basic theory of finite elements as the key to the MATLAB program as a platform to project examples as the background, the finite element method and its programming. This book describes the structural analysis of the basic principles of the finite element method, cell types including flat bar, space bar, flat isoparametric element, space isoparametric element, sheet shell and thick shell element and so on. Covering the truss structure, flat issues, space issues and shell problems. Structural linear elastic static analysis-based, but also about the structural vibration, stability and dynamic response analysis.)

switching median filter for removing impulse noise

it s knn implementation by using toolbox matlab

对混沌时间序列相空间重构中最佳延迟时间间隔和嵌入维数的选取方法作 了综述,提出了同时考虑这2 个参数选取的重构展开虚假邻点法以及预测误差最小(Of chaotic time series phase space reconstruction of the best delay time interval and the embedding dimension of the selection methods were reviewed and put forward these two parameters taking into account the reconstruction of the selected start-point method of false neighbors, as well as the minimum prediction error)