The Input Pattern Order Problem II: Evolution of Multiple-Output Circuits in Hardware

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Author(s)

Department/unit(s)

Publication details

Title of host publication2009 IEEE WORKSHOP ON EVOLVABLE AND ADAPTIVE HARDWARE: (WEAH)
DatePublished - 2009
Pages32-38
Number of pages7
PublisherIEEE
Place of PublicationNEW YORK
Original languageEnglish
ISBN (Print)978-1-4244-2755-0

Abstract

It has been shown in previous work that the design of the input pattern plays and important role in intrinsic evolvable hardware. The results have shown that randomising the input pattern during the course of evolution is mandatory in order to achieve valid circuits that work correctly under all conditions. Furthermore, it was found that randomising the input pattern order helps evolution to avoid local optima. Due to the fact that it becomes exponentially more difficult to successfully evolve circuits with increasing number of outputs, this paper addresses the importance of the input pattern order problem (IPOP) for the second time, with a focus on the intrinsic evolution of digital circuits with multiple outputs. In this paper, we investigate whether it is also possible to design the input pattern in a way to improve the performance of evolution when tackling multiple output problems. A different approach to IPOP is taken, where input pattern order is used as a method of balancing the distribution of the output values. The aim is to equalise the fitness value range by using weighted input vectors in order to obtain a smoother search landscape for multiple output circuits. The proposed method is tested on the intrinsic evolution of 4-bit AND, 4-bit parity, 2-bit full adder, and 2-bit multiplier. Furthermore, the results for the intrinsically evolved multipliers are compared with software simulations in order to determine whether there is a benefit for both intrinsic and extrinsic evolution.

Discover related content

Find related publications, people, projects, datasets and more using interactive charts.

View graph of relations