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感知准则函数
- 感知准则函数,包括固定增量法和梯度下降法,都是模式识别中的基础算法.-perceptual function criteria, including fixed increment and the gradient method, which is pattern recognition algorithm based.
bp2
- 基于梯度下降的BP算法,可以调整学习率可动量因子.-based on the gradient descent algorithm BP, the learning rate can be adjusted momentum factor.
Seven-RBF_NN--code
- 七个RBF神经网络的源代码:基于梯度法、OLS 、聚类、k均值聚类、函数逼近的RBF 网设计算法，及预测模型 -Seven RBF neural network source code: gradient-based method, OLS, clustering, k-means clustering, function approximation of the RBF network design algorithms, and predictive models
RBF
- 基于梯度法编写的RBF神经网络程序，实现对输入数据的逼近-Gradient method based on the preparation process of the RBF neural network to achieve the approximation of the input data
bpnnet_154
- L-M算法。除了动量法(基于梯度下降的训练算法)外，学习率自适应调整策略是BP算法改进的另一种途径，它利用Levenberg-Marquardt优化方法，从而使得学习时间更短。其缺点是，对于复杂的问题，该方法需要很大的存储空间。 -L-M algorithm. In addition to momentum (based on the gradient descent algorithm for training), learning rate adaptive strategy is to i
ex3
- 基于BP神经网络识别字符. BP神经网络算法是把一组样本输入输出问题转化为一个非线性优化问题，并通过梯度算法利用迭代运算求解权值的一种学习方法。采用BP网络进行分类，并附加线性感知器来实现单字符的有效识别，算法简便，识别率高，可适用于多种高噪声环境中的印刷体字符识别。-BP neural network based character recognition. BP neural network algorithm is a set of sample input and output is
shenjingwangluo
- 基于神经网络的手势识别，神经网络的权重可以通过梯度下降法来学习，识别算法对上，下，合并，停止四种姿势进行识别，效果很好。-Gesture recognition based on neural network, neural network weights by gradient descent method to study, identify the algorithm to the upper and lower, merge, stop four kinds of gestures to
PSO_BP
- 基于粒子群和BP神经网络的混合优化策略算法。将改进PSO算法与BP神经网络结合，用PSO算法取代梯度下降法来优化神经网络的连接权值和阈值。程序简单易懂。-Based on Particle Swarm and the BP neural network algorithm for hybrid optimization strategy. Will improve the PSO algorithm and BP neural network, using PSO algorithm to re
BPnn
- 基于随机梯度下降法的两层sigmoid神经元的BP算法-Stochastic gradient descent method based on two layers of sigmoid neurons in the BP algorithm
HoGT
- 用于人体检测的经典HOG算法，基于梯度的直方图提取算法.-HOG Classic for human detection algorithm, based on the gradient of the histogram extraction algorithm.
RBF_2
- 此程序是神经网络中基于梯度的径向基函数算法，在MATLAB中实现。用一个2－n－1结构的RBF网对SISO系统进行建模，网络的两个输入为u(k-1)和y(k-1)，输出为 y(k)。令y(0)=0，按飞线性系统产生200个样本，其中前100个样本用于训练，后100个样本用于测试。-This procedure is based on the gradient neural network radial basis function algorithm is implemented in MATL
matlab4
- This paper presents a fuzzy topology-based method to facilitate the use of larger gradient kernels. The new method effectively limits the response area around the edge and prevents neighboring objects to affect each other. Synthetic images are used t
matlab55
- This paper presents a fuzzy topology-based method to facilitate the use of larger gradient kernels. The new method effectively limits the response area around the edge and prevents neighboring objects to affect each other. Synthetic images are used t
conjg
- 《神经网络与机器学习》书中的，根据共轭梯度法进行双月型数据的分类-" Neural Networks and Machine Learning" book, according to the conjugate gradient method for data classification based bimonthly
Simple-Clustering
- ICA Clustering In computer science, Imperialist Competitive Algorithm (ICA)[1] is a computational method that is used to solve optimization problems of different types. Like most of the methods in the area of evolutionary computation, ICA does n
s4
- 基于遗传算法的作业排序方法 利用梯度下降法求解线性判别函数-Job sorting method based on genetic algorithm using the gradient descent method for solving linear discriminant function
lapsvmp_v02
- 基于先决条件的共轭梯度LAPSVM，算法运算速度快，训练时间短，正确率与其他的相当-Based preconditions conjugate gradient LAPSVM, algorithms computing speed, training time is short, and the other quite correct rate
yuandaima
- 两种不同编码的黄金分割法 基于信息熵的免疫算法 最速下降法 梯度算法-Two different coding golden section method immune algorithm based on information entropy gradient algorithm steepest descent method
A-new-SVM-method-based-on-gradient
- 基于支持向量机选择确定决定分类最优分界面的支持向量样本，基于这些样本中各个变量在基坐标上投影进行变量选择-Selection based on support vector machine (SVM) to determine the optimal boundary decision classification support vector of the sample, based on the sample of each variable on the base coordinate p
DeepLearnToolbox_CNN_lzbV3.0
- CNN - 主程序 参考文献: [1] Notes on Convolutional Neural Networks. Jake Bouvrie. 2006 [2] Gradient-Based Learning Applied to Document Recognition. Yann LeCun. 1998 [3] https://github.com/rasmusbergpalm/DeepLearnToolbox 作者：陆振波 电子