A hardware design of neuromolecular network with enhanced evolvability: a bioinspired approach

Authors:
Yo-Hsien Lin;Jong-Chen Chen
Affiliations:
Department of Information Management, Yuanpei University, Hsinchu, Taiwan;Department of Information Management, National Yunlin University of Science and Technology, Yunlin, Taiwan
Venue:
Journal of Electrical and Computer Engineering - Special issue on Networks-on-Chip: Architectures, Design Methodologies, and Case Studies
Year:
2012

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Abstract

Silicon-based computer systems have powerful computational capability. However, they are easy to malfunction because of a slight program error. Organisms have better adaptability than computer systems in dealing with environmental changes or noise. A close structure-function relation inherent in biological structures is an important feature for providing great malleability to environmental changes. An evolvable neuromolecular hardware motivated by some biological evidence, which integrates inter-and intraneuronal information processing, was proposed. The hardware was further applied to the pattern-recognition domain. The circuit was tested with Quartus II system, a digital circuit simulation tool. The experimental result showed that the artificial neuromolecularware exhibited a close structure-function relationship, possessed several evolvability-enhancing features combined to facilitate evolutionary learning, and was capable of functioning continuously in the face of noise.