6 research outputs found

    Open-ended evolution to discover analogue circuits for beyond conventional applications

    Get PDF
    This is the author's accepted manuscript. The final publication is available at Springer via http://dx.doi.org/10.1007/s10710-012-9163-8. Copyright @ Springer 2012.Analogue circuits synthesised by means of open-ended evolutionary algorithms often have unconventional designs. However, these circuits are typically highly compact, and the general nature of the evolutionary search methodology allows such designs to be used in many applications. Previous work on the evolutionary design of analogue circuits has focused on circuits that lie well within analogue application domain. In contrast, our paper considers the evolution of analogue circuits that are usually synthesised in digital logic. We have developed four computational circuits, two voltage distributor circuits and a time interval metre circuit. The approach, despite its simplicity, succeeds over the design tasks owing to the employment of substructure reuse and incremental evolution. Our findings expand the range of applications that are considered suitable for evolutionary electronics

    Evolutionary design of analog electrical circuits using genetic programming

    No full text
    Abstract. The design (synthesis) of analog electrical circuits entails the creation of both the topology and sizing (numerical values) of all of the circuit's components. There has previously been no general automated technique for automatically designing an analog electrical circuit from a high-level statement of the circuit's desired behavior. This paper shows how genetic programming can be used to automate the design of both the topology and sizing of a suite of five prototypical analog circuits, including a lowpass filter, a tri-state frequency discriminator circuit, a 60 dB amplifier, a computational circuit for the square root, and a timeoptimal robot controller circuit. All five of these genetically evolved circuits constitute instances of an evolutionary computation technique solving a problem that is usually thought to require human intelligence. 1
    corecore