using the cepstrum, neural network to increase but not a success, poor stability

自适应共振神经网络可以实现自动学习与分类具有自适应的功能-adaptive resonance neural network can automatically learning and classification of adaptive function

搜索文章中的文字 更快找到符合要求的内容-English text article more quickly find the content to meet the requirements

实现了RBF网络，已载入训练和测试样本，可根据需要将其更换-Achieved a RBF network, has been printed in the training and test samples may be needed to replace

使用遗传算法、模拟退火算法求解设计结构矩阵，并进行对比分析-The use of genetic algorithms, simulated annealing algorithm design structure matrix, and a comparative analysis of

the matlab code of ginisvm - an svm implementation good at probability regression.-the matlab code of ginisvm- an svm implementation good at probability regression.

自组织系统Kohonen网络模型。对于Kohonen神经网络，竞争是这样进行的：对于“赢”的那个神经元c，在其周围Nc的区域内神经元在不同程度上得到兴奋，而在Nc以外的神经元都被抑制。网络的学习过程就是网络的连接权根据训练样本进行自适应、自组织的过程，经过一定次数的训练以后，网络能够把拓扑意义下相似的输入样本映射到相近的输出节点上。网络能够实现从输入到输出的非线性降维映射结构：它是受视网膜皮层的生物功能的启发而提出的。~..~-Kohonen network model. For Kohonen neural network, competition is this : For the "winner" of neurons c, in its switching around the region neurons in varying degrees, to be excited, and the switching outside the neurons were inhibited. Network learning is a process in the network connecting the right under the training samples for adaptive, self-organizing process, after a certain number of training, network topology can sense similar to the mapping of the input samples similar to the output nodes. Network can be achieved from input to output of nonlinear reduced-dimensional mapping structure : it is subject to retinal cortex of the biological function inspired by. ~ ~ ..

这个主要介绍会计中软件的应用和会计电算法，里面含有一些讲稿和题目-This focuses on the application of accounting and accounting software, power algorithm, which contains a number of lectures and topics

CCE is a multi-instance learning method solving multi-instance problems through adapting multi-instance representation to single-instance algorithms, which is quite different from existing multi-instance learning algorithms which attempt to adapt single-instance algorithms to multi-instance representation

模拟退火c++的算法程序，广泛应用于最优化、运筹学、人工智能、遗传算法等领域，具有很好的学习价值-simulated annealing algorithm procedures, the most widely used optimization, operations research, artificial intelligence, genetic algorithms and other areas of learning is very good value

face recognition test source code