Automated synthesis of analog electrical circuits by means of genetic programming | IEEE Journals & Magazine | IEEE Xplore

Automated synthesis of analog electrical circuits by means of genetic programming


Abstract:

Analog circuit synthesis entails the creation of both the topology and the sizing (numerical values) of all of the circuit's components. This paper presents a single unif...Show More

Abstract:

Analog circuit synthesis entails the creation of both the topology and the sizing (numerical values) of all of the circuit's components. This paper presents a single uniform approach using genetic programming for the automatic synthesis of both the topology and sizing of a suite of eight different prototypical analog circuits, including a low-pass filter, a crossover filter, a source identification circuit, an amplifier, a computational circuit, a time-optimal controller circuit, a temperature-sensing circuit, and a voltage reference circuit. The problem-specific information required for each of the eight problems is minimal and consists of the number of inputs and outputs of the desired circuit, the types of available components, and a fitness measure that restates the high-level statement of the circuit's desired behavior as a measurable mathematical quantity. The eight genetically evolved circuits constitute an instance of an evolutionary computation technique producing results on a task that is usually thought of as requiring human intelligence.
Published in: IEEE Transactions on Evolutionary Computation ( Volume: 1, Issue: 2, July 1997)
Page(s): 109 - 128
Date of Publication: 06 August 2002

ISSN Information:

Computer Science Department, University of Stanford, Stanford, CA, USA
Stanford University, Stanford, CA, US
Computer Science Division, University of California, Berkeley, CA, USA
Martin Keane, Inc., Chicago, IL, USA
Enabling Technology, Inc., Palo Alto, CA, USA

Computer Science Department, University of Stanford, Stanford, CA, USA
Stanford University, Stanford, CA, US
Computer Science Division, University of California, Berkeley, CA, USA
Martin Keane, Inc., Chicago, IL, USA
Enabling Technology, Inc., Palo Alto, CA, USA

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