MPTK-Source-0.7.0

蚁群算法的matlab实例源代码。基于蚁群算法的路径规划(Ant Colony Algorithm)

Set-based stochastic optimization for evolving instinct-learning balance

用vs2013写的霍夫曼编码程序，可将.txt中的英文字符串（包括各种字符如：逗号）编码后输出到一个.txt中，并且可输出构建的霍夫曼树,保存编码方式。(Huffman coding using vs2013 to write programs in English can be txt string (including a variety of characters such as: the comma). Encoded output to a txt, and can output to build Huffman tree, save the encoding. .)

一种盲源分离的联合对角化算法源代码，可以用来盲源分离多信号混叠和特征提取(A blind source separation algorithm for joint diagonalization source code, can be used to blind source separation and multi-aliasing feature extraction)

chirp信号仿真,用于超宽带通信系统中,编码简单易懂(chirp signal simulation for UWB communication systems, easy-to-read code)

该程序代码为阻尼牛顿法matlab源代码，其特点有：简单易读，适于做优化。(code for the damping Newton Matlab source code, its characteristics are : simple accessibility, suitable for making optimization.)

格兰杰因果检验的matlab程序，很好用(Granger causality test matlab)

本书纤细介绍了什么是S函数，以及如何编写S函数和注意事项，另外给出了一些实例(This book describes what S function, and how to write S function and attention, in addition gives some examples)

该文件是间接式双级矩阵变换器的开环仿真模型。输出结果符合理论推导。采用s函数编程的方法实现空间矢量调制策略(This file is indirect two-stage matrix converter of the open loop simulation model. Output the results accord with theoretical derivation. The s function programming method of space vector modulation strategy. )

Texture Analysis Using DWT for Grape Plant Species Classification:- By observing leaf, we can easily identify plant but it is difficult to identify its species. In this project we developed an algorithm that gives user the ability to identify plant species based on photographs of the leaf. The core theme of this application is an algorithm that acquires statistical features of the leaves, and then classifies the species based on a novel combination of the computed texture feature analysis and wavelet analysis. While implementing this algorithm we have considered the Grape plant and its four species viz. Clone, Sonaka, Thomson and Manik. The algorithm is first trained against several samples of known plant species and then used to classify unknown query species. By using this algorithm we have achieved 93.33 efficiency