多步预测,设计简单规范,基于信息建模,具有很强的抗干扰性和鲁棒性....

一个bp实现回归的nn程序，可以从中学习神经网络在回归中的应用-Bp realize a return nn procedures, neural networks can learn from the reunification of the application

卡尔曼滤波模拟器

回溯法求01背包问题,c语言版本，由于时间关系没有将代码进行很好的整理，所有代码都在一个文件中-Retrospective Method 01 knapsack problem, c language versions, due to time not finishing a very good code, all code in one file

Bayes网络工具箱，可以用作分类或者拟和，希望对大家有用-Bayes network toolbox, can be used as a classification or proposed and, in the hope that useful to everybody

遗传算法在TSP中的应用的原代码， 具体的代码见内。-Genetic algorithm source code applies in TSP with detailed code

The Netlab toolbox is designed to provide the central tools necessary for the simulation of theoretically well founded neural network algorithms and related models for use in teaching, research and applications development. It contains many techniques which are not yet available in standard neural network simulation packages-The toolbox is designed to provide t he central tools necessary for the simulation o f theoretically well founded neural network al gorithms and related models for use in teaching , research and applications development. It c ontains many techniques which are not yet avail able in standard neural network simulation pac kages

有关摄像头定标的C++代码，标定摄像头的12个参数-Related to camera calibration C++ Code, camera calibration parameters 12

这是一个nsga的应用问题。算法可能不是最优的。-application of nsga

人工智能模式识别中基于非负矩阵分解生成特征空间的算法-artificial intelligence pattern recognition based on non-negative matrix factorization generation features of the algorithm space

此为疾病诊断专家系统，用这种结构建立的知识库可以很方便地实现上面所提到的各种功能。这种结 构的最独特之处就是依靠相同的关键（疾病名或其代码）来实现一种疾病与其症候之 间的相互联系。疾病名与症候分别用二叉树进行排序。排序后可由疾病名而查到与该 疾病名有关的所有详细情况，也可由一种症候而查到哪些疾病有这种症候，以及该症 候可能引起各种疾病的概率。-This is the disease diagnosis expert system, using this structure to establish the knowledge base can easily realize the above mentioned features. The structure of the most unique is that relying on the same key (the disease or its code) to achieve a disease and its symptoms between. Name and symptoms of disease were treated with binary tree sort. Sort by the disease after the name of the disease were found with all the details of which can also be a symptom of the diseases that have found such a symptom, as well as the symptoms may lead to the probability of various diseases.