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

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. © 2012 yo-hsien lin and jong-chen chen.