Automated analog circuit design using two-layer genetic programming

Analog circuits are very important in many high-speed applications such as communications. Since the size of analog circuit is becoming larger and more complex, the design is becoming more and more difficult. This paper proposes a two-layer evolutionary scheme based on genetic programming (GP), which uses a divide-and-conquer approach to evolve the analog circuits. Corresponding to the two-layer GP, a new representation of circuit has been proposed here and it is more helpful to generate expectant circuit graphs. This algorithm can evolve the circuits with dynamical size, circuit topology, and component values. The experimental results on the designs of the voltage amplifier and the low-pass filter show that this algorithm is efficient.

[1]  Paul J. Layzell,et al.  Explorations in design space: unconventional electronics design through artificial evolution , 1999, IEEE Trans. Evol. Comput..

[2]  John R. Koza,et al.  Genetic Programming III - Darwinian Invention and Problem Solving , 1999, Evolutionary Computation.

[3]  Domine Leenaerts,et al.  Darwin: Analogue circuit synthesis based on genetic algorithms , 1995, Int. J. Circuit Theory Appl..

[4]  Jason D. Lohn,et al.  A circuit representation technique for automated circuit design , 1999, IEEE Trans. Evol. Comput..

[5]  Georges Gielen,et al.  Symbolic analysis for automated design of analog integrated circuits , 1991, The Kluwer international series in engineering and computer science.

[6]  Sameer H. Al-Sakran,et al.  Cross-domain features of runs of genetic programming used to evolve designs for analog circuits, optical lens systems, controllers, antennas, mechanical systems, and quantum computing circuits , 2005, 2005 NASA/DoD Conference on Evolvable Hardware (EH'05).

[7]  Rob A. Rutenbar,et al.  Synthesis of high-performance analog circuits in ASTRX/OBLX , 1996, IEEE Trans. Comput. Aided Des. Integr. Circuits Syst..

[8]  C. Van Reeuwijk,et al.  A design strategy for the synthesis of high-performance instrumentation amplifiers , 1996 .

[9]  Jim Tørresen,et al.  A Divide-and-Conquer Approach to Evolvable Hardware , 1998, ICES.

[10]  John R. Koza,et al.  Automated synthesis of analog electrical circuits by means of genetic programming , 1997, IEEE Trans. Evol. Comput..

[11]  Gerald Jay Sussman,et al.  Heuristic techniques in computer-aided circuit analysis , 1975 .

[12]  Frédéric Gruau.  Artificial Cellular Development in Optimization and Compilation , 1995, Towards Evolvable Hardware.

[13]  Rob A. Rutenbar,et al.  A Prototype Framework for Knowledge-Based Analog Circuit Synthesis , 1987, DAC 1987.

[14]  John R. Koza,et al.  Automatic synthesis using genetic programming of both the topology and sizing for five post-2000 patented analog and mixed analog-digital circuits , 2003, Southwest Symposium on Mixed-Signal Design, 2003..

[15]  John R. Koza,et al.  Genetic programming - on the programming of computers by means of natural selection , 1993, Complex adaptive systems.

[16]  John R. Koza,et al.  Genetic Programming III: Darwinian Invention & Problem Solving , 1999 .

[17]  V. Quarles,et al.  Department of Electrical Engineering and Computer Science , 1994 .

[18]  J.D. Lohn,et al.  Evolvable hardware using evolutionary computation to design and optimize hardware systems , 2006, IEEE Computational Intelligence Magazine.

[19]  P. Nordin.  Genetic Programming III - Darwinian Invention and Problem Solving , 1999 .