资源列表
ganzhiqi
- 感知器，主要有单层和多层感知器的应用的仿真程序设计-Perceptron, there are single and Multilayer Perceptron application simulation program design
fankuishenjingwanglou
- 反馈神经网络，主要有离散Hopfield、连续Hopfield、Elman网络的工程应用-Feedback neural networks, mainly discrete Hopfield, continuous Hopfield, Elman network engineering applications
BP-SHENJINGWANGLOU
- BP 神经网络，有BP神经网络在函数逼近、语音特征信号分类、非线性等的应用-BP neural network, BP neural network approach has the function, speech characteristic signal classification and nonlinear applications
HS
- 和声搜索算法，一种智能优化算法，国外学者编写的源码，可以运行，附带有测试函数和简要的算法介绍，供大家学习参考。-Harmony search algorithm, a kind of intelligent optimization algorithm, foreign scholars write the source code, It can run smoothly with test function and algorithm is introduced briefly, consul
AFSA
- 超级实用的人工鱼群算法，代码简洁，注释清楚，功能强大。-AFSA super practical, concise code, comments clear and powerful.
Pattern-Recognition
- 模式识别与人工智能书籍及源代码，对学习相关知识的人员具有很好的参考意义。-Pattern Recognition and Artificial Intelligence, books and source code, to learn the knowledge of the staff has a good reference value.
EKFUKFCKkk
- 卡尔曼滤波程序代码，包括EKF UKF CKF-EKF UKF CKF
ml
- BP神经网络的Java示例，通过样本训练，能够准确地判断出它是奇数还是偶数，正数还是负数。-Java example BP neural network trained by the sample, can accurately determine that it is odd or even, positive or negative.
CNN-with-three-pooling-strategy
- 这是matlab的代码，将cnn进行三次池化的代码，可以作为学习卷积神经网络的入门例子-This is a matlab code that will perform three pooled cnn code can be used as a convolution neural network learning introductory example
[codes]joint-bayesian
- 这个是联合贝叶斯网络，可以用来作为学习和理解的例子-This is a joint Bayesian network can be used as an example of learning and understanding
[codes]LeNet-5
- 是matlab的代码，关于yann Lecun在89年提出的cnn的原型，这个代码成功应用于欧洲很多国家的手写支票识别-Is matlab code on cnn yann Lecun prototype made in 1989, this code successfully applied to handwriting recognition check many European countries
[codes]NIN
- 是2014年的cnn上的一个变化的网络，将卷积层与池化层之间的线性关系变成1×1的卷积层的非线性关系，名为network in network-Is a change in the 2014 cnn on the network layer of the linear convolution and pooled into a non-linear relationship between the layers 11, convolution layer, called the network