Search - neural network approximation

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[Other] WNN_algorithm1 DL : 0: 小波神经网络程序，收敛性比BP神经网络好，可用于分类，函数逼近等-wavelet neural network program, convergence than BP neural network, and can be used for classification, function approximation etc.
Update : 2025-04-04 Size : 6kb Publisher : 师花
[AI-NN-PR] Adaptive DL : 0: The adaptive Neural Network Library is a collection of blocks that implement several Adaptive Neural Networks featuring different adaptation algorithms.~..~ There are 11 blocks that implement basically these 5 kinds of neural networks: 1) Adaptive Linear Network (ADALINE) 2) Multilayer Layer Perceptron with Extended Backpropagation algorithm (EBPA) 3) Radial Basis Functions (RBF) Networks 4) RBF Networks with Extended Minimal Resource Allocating algorithm (EMRAN) 5) RBF and Piecewise Linear Networks with Dynamic Cell Structure (DCS) algorithm A simulink example regarding the approximation of a scalar nonlinear function of 4 variables is included-The adaptive Neural Network Library is a collection of blocks that implement several Adaptive Neural Networks featuring different adaptation algorithms .~..~ There are 11 blocks that implement basically these five kinds of neural networks : a) Adaptive Linear Network (ADALINE) 2) Multilayer Layer 102206 with Extended Backpropagation algorithm (EBPA) 3) Radial Basis Functions (RBF) Networks, 4) RBF Networks with Extended Minimal Resource Allocating algorithm (EMRAN) 5) and RBF Networks with Piecewise Linear Dynamic Cell Structure (DCS) algorithm A Simulink example regarding the approximation of a scalar nonlinear function of four variables is included
Update : 2025-04-04 Size : 194kb Publisher : 叶建槐
[AI-NN-PR] RBFApproach DL : 0: 基于遗传算法优化的RBF网络逼近程序，可以参考！希望能对大家有所帮助 -based on genetic algorithm optimization RBF network approximation procedures, they can refer to. The hope is to help everyone
Update : 2025-04-04 Size : 3kb Publisher : luchen
[matlab] bpnnet.m DL : 0: 应用bp神经网络实现了函数逼近,并用matlab程序实现了整个过程-Bp neural network applications realize the function approximation, and the procedures used matlab realize the whole process
Update : 2025-04-04 Size : 1kb Publisher : kingkof
[AI-NN-PR] ANN DL : 0: 这是介绍神经网络的入门材料，里面包括MATLAB原程序来解决曲线拟合问题和函数的逼近-This is to introduce the neural network entry materials, which include the original MATLAB program to solve the problem of curve fitting and function approximation
Update : 2025-04-04 Size : 198kb Publisher : wlx
[matlab] anfis DL : 1: 用模糊神经网络逼近二维非线性函数，Matlab文件，附有说明文件。-Using fuzzy neural network approximation of two-dimensional nonlinear function, Matlab files, accompanied by documentation.
Update : 2025-04-04 Size : 454kb Publisher : 邵巍
[AI-NN-PR] bp DL : 0: 神经网络bp算法源代码，各个部分的包括函数逼近，函数定义等的功能-Bp neural network algorithm source code, the various parts, including function approximation, function definition function
Update : 2025-04-04 Size : 16kb Publisher : ye
[File Format] WNN_PID DL : 0: 提出了一种基于小波神经网络整定的PID 控制方法。由于小波变换具有良好的时频局部特性,神经网络具有强大的非线性映射能力,自学习、自适应等优势,采用规范正交的小波函数作为神经网络的基函数构成小波神经网络,该网络兼有小波函数的紧支性、波动性以及神经网络的非线性映射能力,自学习、自适应能力等优点,渗碳炉控制实验结果表明,用该方法整定的PID 控制系统收敛速度快,逼近精度高,鲁棒性好-Based on wavelet neural network-tuning of PID control methods. Since the wavelet transform has good time-frequency localization properties, neural network has strong ability of nonlinear mapping, self-learning, adaptive and other advantages, the use of standardized orthogonal wavelet function as a neural network constitutes a wavelet basis function neural network, the network a combination of compactly supported wavelet function, and volatility as well as the neural network nonlinear mapping ability, self-learning, adaptive capacity, etc., carburizing furnace control experimental results show that using this method of tuning PID control system for fast convergence approximation of high accuracy, good robustness
Update : 2025-04-04 Size : 188kb Publisher : guole
[AI-NN-PR] PI_SIGMA_neural_network DL : 0: Pi-sigma神经网络用于非线性对象的逼近-Pi-sigma neural network approximation for nonlinear object
Update : 2025-04-04 Size : 1kb Publisher : shui
[AI-NN-PR] ran DL : 0: 资源分配神经网络解决Mackey-Glass时间序列预测函数逼近问题-Neural network to solve the allocation of resources Mackey-Glass time series prediction function approximation problem
Update : 2025-04-04 Size : 1kb Publisher : 吴强
[matlab] wnn DL : 0: 小波神经网络的源程序: 1.构造的非线性函数: 位于nninit_test.m 2.直接用WNN逼近非线性:Wnn_test.m, (内部调用小波函数) 3.遗传算法优化后逼近 :GA_Wnn_test.m (内部调用遗传算法的,初始化,适应度,解码函数)-genetic algorithm optimization WNN source : 1. Construction of the nonlinear function : nninit_test.m at 2. WNN directly with nonlinear approximation : Wnn_test.m. (internal called wavelet function) 3. Genetic Algorithm optimization approach : GA_Wnn_test.m (internal called genetic algorithms, initialize, fitness and decoding functions) -Wavelet neural network source code: 1. Construction of the nonlinear function: at nninit_test.m 2. Wnn the direct use of nonlinear approximation: Wnn_test.m, (internal call wavelet function) 3. Genetic algorithm optimized approximation: GA_Wnn_test. m (internal call genetic algorithms, initialization, fitness, decoding function)-genetic algorithm optimization WNN source: 1. Construction of the nonlinear function: nninit_test.m at 2. WNN directly with nonlinear approximation: Wnn_test.m. ( internal called wavelet function) 3. Genetic Algorithm optimization approach: GA_Wnn_test.m (internal called genetic algorithms, initialize, fitness and decoding functions)
Update : 2025-04-04 Size : 1kb Publisher : lanhucx
[AI-NN-PR] IncrementalRandomNeurons DL : 0: 本人编写的incremental 随机神经元网络算法，该算法最大的特点是可以保证approximation特性，而且速度快效果不错，可以作为学术上的比较和分析。目前只适合benchmark的regression问题。具体效果可参考 G.-B. Huang, L. Chen and C.-K. Siew, “Universal Approximation Using Incremental Constructive Feedforward Networks with Random Hidden Nodes”, IEEE Transactions on Neural Networks, vol. 17, no. 4, pp. 879-892, 2006. -I prepared by incremental random neural network algorithm, which is characterized by the largest approximation properties can be guaranteed, and fast good results can be used as an academic comparison and analysis. The current benchmark is only suitable for the regression problem. Specific effects may refer G.-B. Huang, L. Chen and C.-K. Siew,
Update : 2025-04-04 Size : 2kb Publisher : chenlei
[AI-NN-PR] NeuroNetSample DL : 0: 我以前写的一个的神经网络学习函数逼近和分类的例子，商用级的。-I have previously written a study of the neural network function approximation and classification of examples, business class.
Update : 2025-04-04 Size : 1.98mb Publisher : Kevin Guo
[matlab] 11 DL : 0: 神经网络实例集。包括以下几个程序单层线性神经网络实例、感知器神经元解决较复杂输入向量的分类问题、基于感知器神经网络处理复杂的分类问题、数值分析程序matlab-GUI、用BP网络完成函数的逼近源程序、自组织特征映射应用实例-Examples of neural network sets. Procedures include the following examples of single-layer linear neural network, perceptron neuron input vector to solve more complex classification problems, based on the perceptron neural network to deal with complex classification problems, numerical analysis matlab-GUI, using BP network function source approximation, self-organizing feature map application
Update : 2025-04-04 Size : 41kb Publisher : stephen
[AI-NN-PR] GAP-RBF DL : 0: 模糊神经网络逼近与分类，模糊规则提取，快速增长与删减网络。-Fuzzy neural network approximation and classification, fuzzy rule extraction, with the deletion of the rapid growth of the network.
Update : 2025-04-04 Size : 3kb Publisher : 王宁
[AI-NN-PR] OS-ELM DL : 0: 模糊神经网络实现函数逼近与分类，实现模糊规则的提取。-Fuzzy neural network function approximation and classification, to achieve the extraction of fuzzy rules.
Update : 2025-04-04 Size : 6kb Publisher : 王宁
[AI-NN-PR] ELM_DE DL : 0: 模糊神经网络实现函数逼近与分类，实现模糊规则的提取。-Fuzzy neural network function approximation and classification, to achieve the extraction of fuzzy rules.
Update : 2025-04-04 Size : 7kb Publisher : 王宁
[matlab] LP DL : 0: 基于径向基神经网络的算法逼近低通滤波器，用Matlab编程实现-Based on RBF Neural Network Approximation algorithm low-pass filter, using Matlab programming
Update : 2025-04-04 Size : 1kb Publisher :
[AI-NN-PR] chap8 DL : 1: 模糊RBF网络高级神经网络基于模糊RBF网络的逼近算法 Pi-Sigma神经网络-High fuzzy RBF network based on fuzzy RBF neural network approximation algorithm for network Pi-Sigma Neural Networks
Update : 2025-04-04 Size : 9kb Publisher : 方久春
[AI-NN-PR] Neural-network-hanshunihe DL : 0: 设计并训练一神经网络使之逼近下列函数，x，y取值范围（0，3），函数精度0.02。函数为三角函数-Design and training of a neural network approximation the following functions, x, y in the range (0,3), the function accuracy 0.02. Function trigonometric functions
Update : 2025-04-04 Size : 2.04mb Publisher : 楼宇舟

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