用于算术运算的脉冲神经系统

Xiangxiang Zeng, Tao Song, L. Pan, Xingyi Zhang
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引用次数: 4

摘要

最近,Guti ' errez-Naranjo和Leporati考虑在一类新的受生物启发的计算设备上执行基本的算术运算——脉冲神经P系统(简称SN P系统)。然而,在他们的研究中使用的二进制编码机制看起来像电子电路中的编码方法,而不是尖峰神经元的风格(在通常的SN - P系统中,信息被编码为尖峰之间的时间间隔)。本文将三个SN - P系统分别构造为加法器、减法器和乘法器。在这些装置中,一个数字被输入到系统中,作为输入神经元接收到两个尖峰之间的时间间隔,计算的结果是输出神经元尖峰时刻之间的时间。
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Spiking Neural P Systems for Arithmetic Operations
Recently, Guti´errez-Naranjo and Leporati considered performing basic arithmetic operations on a new class of bioinspired computing devices -- spiking neural P systems (for short, SN P systems). However, the binary encoding mechanism used in their research looks like the encoding approach in electronic circuits, instead of the style of spiking neurons (in usual SN P systems, information are encoded as the time interval between spikes). In this work, three SN P systems are constructed as adder, subtracter and multiplier, respectively. In these devices, a number is inputted to the system as the interval of time elapsed between two spikes received by input neuron, the result of a computation is the time between the moments when the output neuron spikes.
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