Abstract
In biological neural networks, neurons transmit chemical signals through synapses, and there are multiple ion channels during transmission. Moreover, synapses are divided into inhibitory synapses and excitatory synapses. The firing mechanism of previous spiking neural P (SNP) systems and their variants is basically the same as excitatory synapses, but the function of inhibitory synapses is rarely reflected in these systems. In order to more fully simulate the characteristics of neurons communicating through synapses, this paper proposes a dynamic threshold neural P system with inhibitory rules and multiple channels (DTNP-MCIR systems). DTNP-MCIR systems represent a distributed parallel computing model. We prove that DTNP-MCIR systems are Turing universal as number generating/accepting devices. In addition, we design a small universal DTNP-MCIR system with 73 neurons as function computing devices.
Highlights
Membrane computing (MC) is a type of system with the characteristic of distributed parallel computing, usually called P systems or membrane systems
In order to improve the computational efficiency of DTNP systems, we introduce multiple channels and inhibitory rules
N2 DTNP − MCIRnm denotes the families of all sets N2 (Π) accepted by DTNP-MCIR systems having calculation result is defined as the time interval between the first two spikes emitted by the output at most m neurons at most n arules each neuron
Summary
Membrane computing (MC) is a type of system with the characteristic of distributed parallel computing, usually called P systems or membrane systems. MC is obtained by researching the structure and functioning of biological cells as well as the communication and cooperation of cells in tissues, organs, and biological neural networks [1,2]. P systems are mainly divided into three categories, namely cell-like P systems, tissue-like P systems, and neural-like P systems. In the past two decades, many P-system variants have been studied and applied to real-world problems, and most of them have been proven to be universal number generating/accepting devices and functional computing devices [3,4]
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