Bioinspired Associative Memories

R. Vázquez, Juan Humberto Sossa Azuela
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引用次数: 2

Abstract

An associative memory AM is a special kind of neural network that allows recalling one output pattern given an input pattern as a key that might be altered by some kind of noise (additive, subtractive or mixed). Most of these models have several constraints that limit their applicability in complex problems such as face recognition (FR) and 3D object recognition (3DOR). Despite of the power of these approaches, they cannot reach their full power without applying new mechanisms based on current and future study of biological neural networks. In this direction, we would like to present a brief summary concerning a new associative model based on some neurobiological aspects of human brain. In addition, we would like to describe how this dynamic associative memory (DAM), combined with some aspects of infant vision system, could be applied to solve some of the most important problems of pattern recognition: FR and 3DOR.
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生物启发联想记忆
联想记忆AM是一种特殊的神经网络,它允许在给定输入模式的情况下回忆一个输出模式,作为可能被某种噪声(加性、减法或混合)改变的键。这些模型大多存在一些局限性,限制了它们在人脸识别(FR)和三维物体识别(3DOR)等复杂问题中的适用性。尽管这些方法具有强大的功能,但如果不应用基于当前和未来生物神经网络研究的新机制,它们就无法发挥其全部功能。在这个方向上,我们想提出一个基于人脑某些神经生物学方面的新联想模型的简要总结。此外,我们想描述这种动态联想记忆(DAM)如何结合婴儿视觉系统的某些方面,可以应用于解决模式识别的一些最重要的问题:FR和3DOR。
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