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Description: 单神经元自适应pid算法matlab原程序-Single neuron adaptive pid algorithm matlab original procedure
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Size: 1024 |
Author: zml |
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Description: 这是有个基于matlab的单一感知器神经元应用的实例-This is a matlab-based single perceptron neuron Examples of applications
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Size: 1024 |
Author: lanlan |
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Description: Simulation describing the electrophysiological behavior of a biological neuron (nerve cell). Two sets of membrane kinetics are included: Hodgkin-Huxley and Schwarz for unmyelinated and myelinated axons.
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Size: 1510400 |
Author: ROGER |
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Description: 基于BP神经网络的PID控制,包括单神经元控制,二次型最优化等几种方法的比较!-Based on BP neural network PID control, including the single neuron control, such as quadratic optimization several methods of comparison!
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Size: 4096 |
Author: liyan |
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Description: 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
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Size: 41984 |
Author: stephen |
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Description: 基于RBF神经网络辨识的单神经元PID模型参考自适应控制-RBF neural network-based identification of single neuron PID model reference adaptive control
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Size: 1024 |
Author: 周凯 |
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Description: 本文讨论了神经网络PID控制策略，提出了一种单神经元自适应PID控制器，给出了控制模型，探讨了单神经元自适应PID控制学习算法，通过修改神经元控制器连接加权系数 ，构成了自适应PID控制器。利用神经网络的自学习能力进行PID控制参数的在线整定，并使用了MATLAB软件进行了仿真研究。比较传统PID控制器与单神经元自适应PID控制器两者的仿真结果表明，神经网络PID控制器参数调节简单，具有很高的精度和很强的适应性，可以获得满意的控制效果。-This paper discusses the nerve network PID control strategy and a single neural and adaptive PID controller is presented, and it s model is given here. The algorithm of PID controller is explored by revising the weighted coefficient . Make use of the study ability of the nerve network to turing the PID control parameter, and proceeds the simulation research using matlab software. From the simulation results, it is can be shown that Neural Network PID controller have the higher accuracy and stronger adaptability, and can get satisfied control result.
Key Words: PID；single Neuron；self-adaptive
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Size: 7168 |
Author: 大同小异 |
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Description: This is Neuron Network Solution E-Book it s explain about how Neuron Network work and have example
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Size: 3392512 |
Author: artchan |
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Description: 混沌神经网络模型，包括二个和三个混沌神经元组成的网络-Chaotic neural network model, including two and three chaotic neuron network
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Size: 2048 |
Author: 廖洪运 |
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Description: 基于RBF神经网络辨识的单神经元PID模型参考自适应控制-RBF neural network-based identification of single neuron PID model reference adaptive control
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Size: 1024 |
Author: pony |
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Description: Based on the information processing functionalities of spiking neurons, a spiking neural network model is proposed to extract features from a visual image. The network is constructed with a conductance-based integrate-and-fire neuron model and a set of specific receptive fields. The properties of the network are detailed in this paper. Simulation results show that the network is able to perform image feature extraction within a time interval of 100 ms. This processing time is consistent with the human visual system. The demonstrations show how the network can extract right-angle contours in a visual image. Based on this principle, many other image features can be extracted by analogy. The parallel processing mechanism of this network model is very promising for a hardware implementation based on VLSI or FPGA technology.
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Size: 288768 |
Author: sacoura31 |
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Description: This program simulates a 3 or 4-layer Neural Network, and can be used to
simulate an arbitrary, complex, or non-linear function that would be
difficult to implement by traditional methods. The Back Propagation
method is used "teach" the network the desired function.
Adjacent layers of the net are fully interconnected that is, every
neuron in layer 1 is connected to every neuron in layer 2, and every
neuron in layer 2 is connected to every neuron in layer 3 (1->2, 2->3).
With a 4-layer net, there is further interconnection: 1->2, 1->3, 2->3,
2->4, 3->4.
- This program simulates a 3 or 4-layer Neural Network, and can be used to
simulate an arbitrary, complex, or non-linear function that would be
difficult to implement by traditional methods. The Back Propagation
method is used "teach" the network the desired function.
Adjacent layers of the net are fully interconnected that is, every
neuron in layer 1 is connected to every neuron in layer 2, and every
neuron in layer 2 is connected to every neuron in layer 3 (1->2, 2->3).
With a 4-layer net, there is further interconnection: 1->2, 1->3, 2->3,
2->4, 3->4.
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Size: 49152 |
Author: cso |
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Description: FPGA implementations neuron network
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Size: 3888128 |
Author: phongduong |
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Description: Neuron system spike train
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Size: 1024 |
Author: pingyu |
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Description: Neuron芯片的应用程序是用Neuron C编写的，文档详细介绍了Neuron C的编程技巧。 -Neuron Chip application is written in Neuron C, the document details the Neuron C programming skills.
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Size: 3090432 |
Author: 杨玉峰 |
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Description: 机器人模拟的仿真程序，还有一个神经网络模拟的程序。建立2层网络神经。-ROBOT SIMULATION PROGRAM, AND NETWORK NEURON
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Size: 22528 |
Author: xiongjianlin |
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Description: Implementation of neuron of MTP neural network.
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Size: 154624 |
Author: pablo |
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Description: 基于RBF神经网络辨识的单神经元PID模型参考自适应控制 -Based on RBF Neural Network Identification of single neuron PID model reference adaptive control based on RBF Neural Network Identification of single neuron PID model reference adaptive control
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Size: 5120 |
Author: wdmaster2003 |
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Description: This toolbox includes routines for using principal component analysis (PCA) and independent component analysis (ICA) to extract cellular signals from imaging data sets. A full description and validation of the method is provided in the paper, "Automated Analysis of Cellular Signals from Large-Scale Calcium Imaging Data," Neuron, 63:747 (2009): http://tinyurl.com/cellsort
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Size: 345088 |
Author: lin |
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Description: 神经网络在matlab中的使用说明书 也是新手上手的好东西-Neuron Network Architectures
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Size: 4379648 |
Author: lfc |
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