good_forced

说明：  基于BP神经的改进遗传算法，对初学者会有帮助(Based on improved genetic algorithm BP neural)

This is about least squares algorthims

基于子空间的盲多用户检测技术，里面包含PASTd算法和秩算法的介绍与计算。下面我会把自己的翻译也上传上来。(Subspace-based blind multi-user detection technology, which containing PASTd algorithm and rank algorithm describes calculation. I will own translation post it here.)

ITS ALL ABOUT BLDC MOTOR AND USED IN FUZZY LOGIC APPLICATION.IT A VERY GOOD PAPER FOR BEGINERS

利用夹角余弦距离进行样本数据分类。实现步骤主要分为以下两部分：a、待测样品X与训练集里每个样品Xi的距离采用夹角余弦距离公式计算。b、循环计算待测样品和训练集中各已知样品之间的距离，找出距离待测样品最近的已知样品，该已知样品的类别就是待测样品的类别。(Using the sample data classification Angle cosine distance.Implementation steps are divided into the following two parts: a, sample under test with each of the samples in the training set X Xi distance using the included Angle cosine distance formula.B, loop calculation under test samples and the distance between the known samples training focus, find out the known closest to the sample under test samples, the samples of known category is the category of the sample under test.)

Simulation of Chaotic Henon Map

Edge detector of Canny.

说明：  这是一本介绍matlab的书，书中有许多实例，讲解详细，从入门到综合，适用于初学者(This is an introduction matlab The book has many examples to explain in detail, from the entry to the synthesis, for beginners)

风电叶片设计，利用Glauert公式计算诱导因子a，b(Glauert formula to calculate the induced factor a and b)

The zip file contains several matlab files. These files implement the optimal vlassifier (optimal_classifier.m), a sub-optimal classifier (SOS_STBC_Classifier.m) which is based on Second Order Statistic and a low-complexity sub optimal code-parameter classifier (CP_Classifier.m). See reference [1] for the theoretical background. Example: To create the fig 3,4 and 5 of the paper, call the routine: Blind_recognition_STBC2_simulation_results(512,4, PSK ,4) Reference: [1] V. Choqueuse, M. Marazin, L. Collin, K. Yao and G. Burel "Blind recognition of STBC: A Likelihood-based Approach", IEEE Transactions on Signal Processing (IF: 2.33), vol. 58(3), pp : 1290-1299, March 2010.