基于多抽象层次感知的新型计算细胞凋亡-神经发生模型

A. Zaher, F. Aboul-Makarem, Y. Kadah
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引用次数: 1

摘要

人工神经网络提供了一种类似于人类智能的控制论模型,在同一神经网络上进行并行处理、泛化和记忆叠加。从神经发生时代开始,研究模型就期望控制新神经元的规则依赖于旧的成熟电路。其他研究模型表明,如果物种暴露于可变信息内容的环境中,则存在与新神经元相关的灾难性干扰。在这项工作中,所开发的模型为一种新的注意敏感神经网络提供了理论框架,同时也提供了一个实验框架,揭示了如果新神经元在人脑中经历某些结构过程,则可以防止新神经元的添加产生灾难性干扰现象。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Novel Computational Apoptosis-Neurogenesis Model for Multi-Abstraction Level Perception
Artificial neural network provides a cybernetic model that is similar to human intelligence in terms of parallel processing, generalization and memory stacking on the same neural network. From the era of neurogenesis, research models expect the rules that govern new neuron to depend on old mature circuitry. Other research models show the existence of catastrophic interference associated with new neurons if species is exposed to variable information content environment. In this work, the model developed provides a theoretical framework for a novel attention sensitive neural network as well as an experimental framework revealing the addition of new neuron can be prevented from catastrophic interference phenomena if it undergoes certain structural processes in human brain.
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