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自适应共振理论网络 用来进行模式分类联想记忆效果很好，误差率极低，能正确识别-Adaptive Resonance Theory networks used for pattern classification associative memory with good results, the error rate is very low, able to correctly identify
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adaptive resonance theory 2
人工神经网络-two adaptive resonance theory of artificial neural networks
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介绍了自适应共振理论ART模型的工作原理和算法流程。-introduced ART Adaptive Resonance Theory model of principle, and the algorithm.
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自适应共振理论（ART)。-Adaptive Resonance Theory (ART).
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Adaptive Resonance Theory Brain Modeling 人工智能人工神经网络源码-Adaptive Resonance Theory Brain Modeling artificial neural network artificial intelligence source
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自适应共振理论（ART）-Adaptive Resonance Theory (ART)
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清华大学的神经网络的课件！主要讲了感知器，对传网，自适应共振理论！-Tsinghua University, the neural network software! The main speaker of the perceptron on the Biography network, adaptive resonance theory!
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Adaptive Resonance Theory Brain Modeling 人工智能人工神经网络源码-Adaptive Resonance Theory Brain Modeling artificial neural network artificial intelligence source
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Adaptive resonance theory
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adaptive resonance theory 2
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Adaptive Resonance Theory (ART) Neural Network
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c语言的自组织神经网络源程序，已测试通过（自适应共振理论模型）-c language, self-organizing neural network source code, have been tested (adaptive resonance theory model)
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Art1-FuzzyArt-Artmap-FuzzyArtmap
具体使用例子参看《Adaptive Resonance Theory Microchips》附录A-Art1-FuzzyArt-Artmap-FuzzyArtmap
from the book:Adaptive Resonance Theory Microchips
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source code adaptive resonance theory Nural network in matlab for classification
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a presentation about Fuzzy ART algorithm and Failure mode and effects analysis
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Adaptive Resonance Theory neural network
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人工智能自适应共振理论的运用，脑模型的稳定性，可塑性示范-The use of adaptive resonance theory artificial intelligence, brain model of stability, plasticity model
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ART神经网络源码.自适应共振理论ART(Adaptive Resonance Theory)模型是美国Boston大学的S．Grossberg和A．Carpenet在1976年提出的。ART是一种自组织神经网络结构，是无教师的学习网络。当在神经网络和环境有交互作用时，对环境信息的编码会自发地在神经网中产生，则认为神经网络在进行自组织活动。ART就是这样一种能自组织地产生对环境认识编码的神经网络理论模型。-The code of ART neural network
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Adaptive Resonance Theory Microchips
collection documents
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an introdction to ADAPTIVE RESONANCE THEORY
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