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Description: 自适应(Adaptive)神经网络源程序
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 -Adaptive (Adaptive) The neural network source 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) 102206 with Multilayer Layer 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 Dynamic Networks with the Cell Structure (DCS) algorithm A Simulink example regarding the approximation of a scalar nonlinear function of four variables
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Size: 200530 |
Author: 周志连 |
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Description: 一个用MATLAB写的ART1神经网络原代码-a MATLAB write ART1 neural network original code!
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Size: 199097 |
Author: 余建波 |
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Description: 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
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Size: 198792 |
Author: 叶建槐 |
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Description: 落煤残存瓦斯量的确定是采掘工作面瓦斯涌出量预测的重要环节,它直接影响着采掘工作面瓦斯涌出量预测的精度,并与煤的变质程度、落煤粒度、原始瓦斯含量、暴露时间等影响因素呈非线性关系。人工神经网络具有表示任意非线性关系和学习的能力,是解决复杂非线性、不确定性和时变性问题的新思想和新方法。基于此,作者提出自适应神经网络的落煤残存瓦斯量预测模型,并结合不同矿井落煤残存瓦斯量的实际测定结果进行验证研究。结果表明,自适应调整权值的变步长BP神经网络模型预测精度高,收敛速度快 该预测模型的应用可为采掘工作面瓦斯涌出量的动态预测提供可靠的基础数据,为采掘工作面落煤残存瓦斯量的确定提出了一种全新的方法和思路。-charged residual coal gas is to determine the volume of mining gas emission rate forecast an important link, which directly affect mining gas emission rate forecast accuracy, and with coal metamorphism, loading coal particle size, the original gas content, exposure time and other factors nonlinear relationship. Artificial neural networks have expressed arbitrary nonlinear relationships and the ability to solve complex nonlinear, time-varying uncertainty and the new ideas and new approaches. Based on this, the author of adaptive neural network loading coal residual gas production forecast model, and a combination of different loading coal mine gas remnants of the actual test results of research. Results show that the adaptive value of the right to change step BP neural network model predict
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Size: 60416 |
Author: 王静 |
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Description: 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. ~ ~ ..
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Size: 34816 |
Author: 张洁 |
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Description: 自适应(Adaptive)神经网络源程序
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 -Adaptive (Adaptive) The neural network source 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) 102206 with Multilayer Layer 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 Dynamic Networks with the Cell Structure (DCS) algorithm A Simulink example regarding the approximation of a scalar nonlinear function of four variables
Platform: |
Size: 200704 |
Author: 周志连 |
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Description: 一个用MATLAB写的ART1神经网络原代码-a MATLAB write ART1 neural network original code!
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Size: 198656 |
Author: 余建波 |
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Description: 自适应PSD神经元控制,用于伺服电机的调速度,比单神经元有跟好的鲁帮性-adaptive neural control for the servo-motor speed, a single neuron with good Lu hand
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Size: 1024 |
Author: wang |
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Description: 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
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Size: 198656 |
Author: 叶建槐 |
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Description: 拿verilog编写的som(自适应神经网络算法)，用于障碍物检测，基于FPGA可综合实验，已经在altera的cylcone上实现-Canal verilog prepared som (adaptive neural network algorithm) for obstacle detection. Based on FPGA synthesis experiments, in altera achieve the cylcone
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Size: 5120 |
Author: 刘索山 |
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Description: 神经网络五层自适应BP算法，能在VC6.0下调试通过-five-story adaptive neural network algorithm BP, in debugging through VC6.0
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Size: 3072 |
Author: |
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Description: 神经网络方面自适应滤波算法的综述，希望大家有用-neural network algorithm for the adaptive filter on the hope that it may be useful
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Size: 94208 |
Author: 卢宇豪 |
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Description: The adaptive Neural Network Library is a collection of blocks that implement several Adaptive Neural Networks featuring different adaptation algorithms.
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Size: 210944 |
Author: 李立 |
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Description: 近几年来研究的多种PID控制程序，有灰色PID，神经网络自适应PID，模糊PID等等，！
-Research in recent years a variety of PID control procedures, has gray PID, Neural Network Adaptive PID, fuzzy PID, etc.!
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Size: 5120 |
Author: wjy |
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Description: 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
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Size: 192512 |
Author: guole |
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Description: 经典的模糊神经网路m程序，采用T-S模型，自适应反传算法-Classic m fuzzy neural network procedure for the TS model, adaptive back propagation algorithm
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Size: 562176 |
Author: lishichao |
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Description: Matlab与自适应神经网络模糊推理系统-Matlab neural network and adaptive fuzzy inference system
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Size: 9958400 |
Author: hjk |
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Description: 用于神经网络自适应算法的Matla盲源分离
-Adaptive algorithm for neural networks of the Matla Blind Source Separation
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Size: 1212416 |
Author: holy0615 |
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Description: 模糊自适应神经网络（ANFIS）建立模型，精度较高-Fuzzy adaptive neural network (ANFIS) model the high precision
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Size: 1024 |
Author: 杨静 |
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Description: Adaptive Neural-Fuzzy Approach for Object Detection
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Size: 1249280 |
Author: sengottaiyan |
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