A Hardware Design of Neuromolecular Network with Enhanced Evolvability : A Bioinspired Approach

Abstract EN

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.