隐马尔科夫模型工具箱最新版本，可以广泛应用于识别等领域...

模糊神经网络采用matlab编程 o install NEFCON follow these steps: 1. Unpack the tar file NEFCON.TAR into your MATLAB working directory: tar xf NEFCON.TAR 2. Start MATLAB 3. Change to the installation directory. 4. Change to the NEFCON directory. 5. Start the STARTUP M-file to initialize NEFCON.-FNN using Matlab programming o install NEFCON follow these steps : 1. Unpack the tar file NEFCON.TAR MATLAB into your working directory : tar xf NEFCON.TAR 2. Start MATLAB 3. Change to the installation directory. 4. Change to the NEFCON directory. 5. Start the STARTUP M-file to initialize NEFCON.

支持向量机的matlab代码.很有参考价值的源代码-Support vector machine matlab code. A good reference source code

是一个非常全面的pso的程序，有16个函数的测试，并且用三维图形将寻优过程显示出来。对所有的参数都可以修改测试-Is a very comprehensive procedure for the PSO, there are 16 function testing, and using three-dimensional graphics optimization process will be displayed. For all the parameters can modify the test

一个机器人信息显示系统，代码比较全，你会喜欢的-Information display system of a robot, code-wide comparison, you would like

停车诱导系统中车位预测模型的研究 摘 要 研究城市停车诱导系统的停车车位占有率预测问题。首先提出墓于B P神经网络的车位占有预测模型， 同时将自适应 学习速率调整法和加入动量项方法用于改善基本B P神经网络， 优化了学习速率， 减少了训练过程的震荡趋势， 改善了网络的收效 隆。以此为基础实现了停车位的智能预测 0最后， 进行了多种方法比对实验-err

利用空间表示的rcc8模型进行空间推理， 解决csp问题，可以自动产生csp问题，然后解决，利用了不同的算法并且做了比较，有仿真试验。-said that the use of space rcc8 model spatial reasoning, problem solving csp. csp can be generated automatically, and then resolved, the use of different algorithms and made a comparison, a simulation test.

使用遗传算法求解邮递员问题，从而可以同时求得多个最优解-The use of genetic algorithm postman problem, which can be obtained at the same time more than the optimal solution

fp_growth，apriori算法的升级版，减少了扫描数据库的次数-fp_growth, apriori algorithm upgrades, reducing the number of scanning the database

％ RBF 神经网络用于函数拟合　 ％ 使用平台 - Matlab6.5- RBF neural network used for function fitting platform- Matlab6.5

一种通过自组织竞争学习网络实现数据降维和可视化的单层神经网络模型。用此算法可以把输入空间的多维映射到低维的（一维或者二维）的离散网络上，并将保持相同性质的输入数据在映射到低维空间时的拓扑一致性。iris以及letter两个数据集进行分类-A competitive learning through self-organizing network for data dimensionality reduction and visualization of single-layer neural network model. Using this algorithm can be multi-dimensional input space is mapped to the low-dimensional (one-dimensional or two-dimensional) discrete network, and will remain the same as the nature of the input data is mapped to the low-dimensional space of topological consistency. iris as well as the letter the two data sets to classify