LEARNING DYNAMICS AND STABILITY IN NETWORKS WITH FUZZY SYNAPSES

K. GOPALSAMY

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LEARNING DYNAMICS AND STABILITY IN NETWORKS WITH FUZZY SYNAPSES

机译：具有模糊突触的网络中的学习动力学和稳定性

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A new model of Hopfield-type neural network of neurons with crisp somatic activations which have some fuzzy synaptic modifications is formulated which incorporates a Hebbian-type unsupervised learning algorithm. A set of sufficient conditions are derived for the existence of a globally exponentially stable steady state; the exponential convergence of the learning algorithm is also considered. Our model will reduce to one of fuzzy neural networks considered by others when the learning component is absent; when the fuzzy synapses are absent, our model will reduce to the well known Hopfield-type network

机译：提出了一种新的具有模糊突触修饰的具有脆性体细胞激活的神经元Hopfield型神经网络模型，该模型结合了Hebbian型无监督学习算法。对于全局指数稳定状态的存在，导出了一组充分条件。还考虑了学习算法的指数收敛性。当缺少学习组件时，我们的模型将简化为其他人考虑的模糊神经网络之一;当不存在模糊突触时，我们的模型将简化为众所周知的Hopfield型网络

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《Dynamic Systems and Applications》 |2006年第4期|共14页
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K. GOPALSAMY;
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正文语种 eng
中图分类理论力学（一般力学）;
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专利

1. LEARNING DYNAMICS AND STABILITY IN NETWORKS WITH FUZZY SYNAPSES [J] . K. GOPALSAMY Dynamic Systems and Applications . 2006,第3a4期

机译：具有模糊突触的网络中的学习动力学和稳定性
2. A Reinforcement Learning Framework for Spiking Networks with Dynamic Synapses [J] . Karim El-Laifhy Martin Bogdan Computational intelligence and neuroscience . 2011,第Regularaaaa期

机译：具有动态突触的尖峰网络的强化学习框架
3. A Reinforcement Learning Framework for Spiking Networks with Dynamic Synapses [J] . KarimEl-Laithy, MartinBogdan Computational intelligence and neuroscience . 2011,第3期

机译：具有动态突触的尖峰网络的强化学习框架
4. Trust Region Nonlinear Optimization Learning Method for Dynamic Synapse Neural Networks [C] . Hassan H. Namarvar, Theodore W. Berger International Conference on Neural Networks . 2003

机译：信赖区域动态突触神经网络的非线性优化学习方法
5. Learning in Dynamic Synapse Neural Networks. [D] . Yousefi, Ali. 2014

机译：在动态突触神经网络中学习。
6. A Reinforcement Learning Framework for Spiking Networks with Dynamic Synapses [O] . Karim El-Laithy, Martin Bogdan 2011

机译：具有动态突触的尖峰网络的强化学习框架
7. Special Issue "Fuzzy/Neural Network Applications to Dynamics and Control of Mechanical Systems". Stability Analysis of Fuzzy Control System by 3D Space Display. [O] . Mikio MAEDA, Eiji FUKUMIYA 1992

机译：特别问题“模糊/神经网络应用于动态和控制机械系统”。 3D空间显示模糊控制系统的稳定性分析。
8. Learning control of inverted pendulum system by neural network driven fuzzy reasoning: The learning function of NN-driven fuzzy reasoning under changes of reasoning environment [R] . Hayashi, Isao, Nomura, Hiroyoshi, Wakami, Noboru 1991

机译：基于神经网络驱动模糊推理的倒立摆系统学习控制：推理环境变化下NN驱动模糊推理的学习功能

LEARNING DYNAMICS AND STABILITY IN NETWORKS WITH FUZZY SYNAPSES

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