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An Effective Associative Memory for Pattern Recognition

机译:用于模式识别的有效关联记忆

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Neuron models of associative memory provide a new and prospective technology for reliable data storage and patterns recognition. However, even when the patterns are uncorrelated, the efficiency of most known models of associative memory is low. We developed a new version of associative memory with record characteristics of its storage capacity and noise immunity, which, in addition, is effective when recognizing correlated patterns.
机译:关联记忆的神经元模型为可靠的数据存储和模式识别提供了一种新的和前瞻性技术。然而,即使当模式不相关时,大多数已知型号的关联存储器的效率也很低。我们开发了一个新版本的关联记忆,具有其存储容量和噪声抗扰度的记录特征,此外,在识别相关模式时是有效的。

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