尖峰神经网络的脑启发架构

IF 3.4 3区 医学 Q1 ENGINEERING, MULTIDISCIPLINARY
Fengzhen Tang, Junhuai Zhang, Chi Zhang, Lianqing Liu
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引用次数: 0

摘要

尖峰神经网络(SNN)使用动作电位(尖峰)来表示和传输信息,与传统的人工神经网络相比,在生物学上更加可信。然而,现有的大多数尖峰神经网络都需要一个单独的预处理步骤,将实值输入转换为尖峰,然后输入网络进行处理。分割的尖峰编码过程可能会造成信息丢失,导致性能下降。然而,生物神经元系统并不执行单独的预处理步骤。此外,神经系统可能没有单一的途径来响应和处理外部刺激,而是允许多个回路感知同一刺激。受生物神经系统这些优势方面的启发,我们提出了一种具有并行结构的自适应编码尖峰神经网络。该网络通过卷积运算将输入编码过程整合到尖峰神经网络架构中,从而使网络能够接受实值输入,并自动将其转换为尖峰信号进行进一步处理。同时,受生物神经系统以串行和并行方式处理信息的启发,所提出的网络包含两个相同的并行分支。在多个图像分类任务上的实验结果表明,所提出的网络可以获得具有竞争力的性能,这表明所提出的架构是有效的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Brain-Inspired Architecture for Spiking Neural Networks.

Spiking neural networks (SNNs), using action potentials (spikes) to represent and transmit information, are more biologically plausible than traditional artificial neural networks. However, most of the existing SNNs require a separate preprocessing step to convert the real-valued input into spikes that are then input to the network for processing. The dissected spike-coding process may result in information loss, leading to degenerated performance. However, the biological neuron system does not perform a separate preprocessing step. Moreover, the nervous system may not have a single pathway with which to respond and process external stimuli but allows multiple circuits to perceive the same stimulus. Inspired by these advantageous aspects of the biological neural system, we propose a self-adaptive encoding spike neural network with parallel architecture. The proposed network integrates the input-encoding process into the spiking neural network architecture via convolutional operations such that the network can accept the real-valued input and automatically transform it into spikes for further processing. Meanwhile, the proposed network contains two identical parallel branches, inspired by the biological nervous system that processes information in both serial and parallel. The experimental results on multiple image classification tasks reveal that the proposed network can obtain competitive performance, suggesting the effectiveness of the proposed architecture.

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来源期刊
Biomimetics
Biomimetics Biochemistry, Genetics and Molecular Biology-Biotechnology
CiteScore
3.50
自引率
11.10%
发文量
189
审稿时长
11 weeks
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