资源列表
[muchong.com]PSO-BP
- 粒子群算法优化bp神经网络进行时间序列的预测，通过优化神经网络中的参数达到更好的预测效果(Particle swarm optimization (PSO) optimizes the BP neural network to predict the time series, and optimizes the parameters of the neural network to achieve better prediction results)
wavelet&DL
- 这是有关小波和深度学习进行融合和解释的一些文章，我把文章题目和摘要在word文档中列了出来，里面有对应的文章的链接，可以点开题目打开对应的文章。(This is the wavelet and deep learning of some articles fusion and interpretation, I put the titles and abstracts of the articles listed in the word document, which has a corresp
ksvdbox
- K-SVD算法用于稀疏表达,基于OMP算法。(The algorithm is apply for sparse representation)
ompbox
- K-SVD算法用于稀疏表达，基于OMP算法。(The algorithm is apply for the sparse representation.)
network Simon Haykin
- 神经网络与机器学习，第三版： 神经网络是计算智能和机器学习的重要分支，在诸多领域都取得了很大的成功。在众多神经网络著作中，影响最为广泛的是这本书。(Neural networks and machine learning: Third Edition: neural network is an important branch of computational intelligence and machine learning, and has achieved great success in
EKF
- EKF的实现,基于导航数据实现的扩展卡尔曼滤波。参数已经调好了，可以直接用(the implementation of EKF)
GoogleNet_MATLAB-master
- GoogleNet 卷积神经网络 图片分类 分类精度高 网络结构深(GoogleNet convolution neural network image classification, high classification accuracy, network structure is deep)
kxianbaojing
- MT4外汇平台使用，可以自己设置K线点数报警(MT4 foreign exchange platform, you can set their own K-line points alarm)
neural-networks-and-deep-learning-master
- 用不同的方法实现了神经网络（没有用第三方库，就是用numpy等实现的，对于初学者来说是不错的深入了解神经网络的素材）(Using different methods to achieve the neural network (not using third square libraries, that is, using numpy and so on, for beginners is a good understanding of the neural network material))
DeepLearningImageClassificationExample
- 使用2012Imagenet数据大赛深度学习网络为架构的卷积神经网络，可进行多类数据分类任务(Using the 2012Imagenet Data Contest Deep Learning Network for Architectural Convolution Neural Networks, Multiple Class Data Classification Tasks)
weighted_median_filter_approx
- 加权引导滤波的一般实现方式，内有代码注释(A general implementation of weighted bootstrap filtering with code annotations)
基于遗传神经网络的图像分割
- 利用神经网络进行图像分割，对于初学者有很好的使用价值。(Image segmentation using neural networks)