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在类蛋白微球体聚集体中的学习。

Learning in ensembles of proteinoid microspheres.

作者信息

Mougkogiannis Panagiotis, Adamatzky Andrew

机构信息

Unconventional Computing Laboratory, UWE, Bristol, UK.

出版信息

R Soc Open Sci. 2023 Oct 11;10(10):230936. doi: 10.1098/rsos.230936. eCollection 2023 Oct.

Abstract

Proteinoids are thermal proteins which form microspheres in water in the presence of salt. Ensembles of proteinoid microspheres exhibit passive nonlinear electrical properties and active neuron-like spiking of electrical potential. We propose that various neuromorphic computing architectures can be prototyped from the proteinoid microspheres. A key feature of a neuromorphic system is a learning. Through the use of optical and resistance measurements, we study mechanisms of learning in ensembles of proteinoid microspheres. We analyse 16 types of proteinoids study and their intrinsic morphology and electrical properties. We demonstrate that proteinoids can learn, memorize and habituate, making them a promising candidate for novel computing.

摘要

类蛋白是热蛋白,在有盐存在的情况下于水中形成微球体。类蛋白微球体集合体表现出被动非线性电学特性以及类似神经元的主动电位尖峰。我们提出,可以从类蛋白微球体构建各种神经形态计算架构的原型。神经形态系统的一个关键特征是学习。通过使用光学和电阻测量,我们研究类蛋白微球体集合体中的学习机制。我们分析了16种类蛋白的研究及其内在形态和电学特性。我们证明类蛋白能够学习、记忆和习惯化,使其成为新型计算的有前途的候选者。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1094/10565364/5cee4c01b773/rsos230936f01.jpg

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