MO-TRIBES for the optimal design of analog filters

The authors present the use of swarm intelligence in the analog design field. MO-TRIBES, which is an adaptive user-parameter less version of the multi-objective particle swarm optimization technique, is applied for the optimal design of a versatile building block, namely a CMOS current conveyor transconductance amplifier (CCTA). The optimized CCTA is used for the design of a universal filter. Good reached results are highlighted via SPICE simulations, and are compared to the theoretical ones. The use of such adaptive optimization algorithm is of great interest in the analog circuit design, as it is highlighted in this chapter. DOI: 10.4018/978-1-4666-2666-9.ch003

[1]  Patrick Siarry,et al.  Circuit performance optimization and model fitting based on simulated annealing , 1992 .

[2]  Abhijit Chatterjee,et al.  Simulation-in-the-loop analog circuit sizing method using adaptive model-based simulated annealing , 2004 .

[3]  Sudhanshu Maheshwari,et al.  Single MO-CCCCTA-Based Electronically Tunable Current/Trans-Impedance-Mode Biquad Universal Filter , 2011, Circuits Syst..

[4]  Maurice Clerc,et al.  Performance evaluation of TRIBES, an adaptive particle swarm optimization algorithm , 2009, Swarm Intelligence.

[5]  A. Rodríguez-Vázquez,et al.  Global design of analog cells using statistical optimization techniques , 1994 .

[6]  Sudhanshu Maheshwari,et al.  An Electronically Tunable SIMO Biquad Filter Using CCCCTA , 2009, IC3.

[7]  J. B. Grimbleby,et al.  Automatic analogue circuit synthesis using genetic algorithms , 2000 .

[8]  M Reyes Sierra,et al.  Multi-Objective Particle Swarm Optimizers: A Survey of the State-of-the-Art , 2006 .

[9]  Lester Ingber,et al.  Adaptive simulated annealing (ASA): Lessons learned , 2000, ArXiv.

[10]  Mourad Loulou,et al.  Analog circuit design optimization through the particle swarm optimization technique , 2010 .

[11]  Oliver Vornberger,et al.  An Adaptive Parallel Genetic Algorithm for VLSI-Layout Optimization , 1996, PPSN.

[12]  Jong-hyun Ryu,et al.  Pareto front approximation with adaptive weighted sum method in multiobjective simulation optimization , 2009, Proceedings of the 2009 Winter Simulation Conference (WSC).

[13]  Yiming Li,et al.  A simulation-based evolutionary approach to LNA circuit design optimization , 2009, Appl. Math. Comput..

[14]  Ian O'Connor,et al.  Automated synthesis of current-memory cells , 2000, IEEE Trans. Comput. Aided Des. Integr. Circuits Syst..

[15]  Georges G. E. Gielen,et al.  Optimizing current conveyors by evolutionary algorithms including differential evolution , 2009, 2009 16th IEEE International Conference on Electronics, Circuits and Systems - (ICECS 2009).

[16]  Kurt Antreich,et al.  The sizing rules method for analog integrated circuit design , 2001, IEEE/ACM International Conference on Computer Aided Design. ICCAD 2001. IEEE/ACM Digest of Technical Papers (Cat. No.01CH37281).

[17]  John E. Dennis,et al.  Normal-Boundary Intersection: A New Method for Generating the Pareto Surface in Nonlinear Multicriteria Optimization Problems , 1998, SIAM J. Optim..

[18]  Charles Audet,et al.  Multiobjective Optimization Through a Series of Single-Objective Formulations , 2008, SIAM J. Optim..

[19]  Maurice Clerc,et al.  The particle swarm - explosion, stability, and convergence in a multidimensional complex space , 2002, IEEE Trans. Evol. Comput..

[20]  Nuno Horta,et al.  Analog Circuits and Systems Optimization based on Evolutionary Computation Techniques , 2010, Studies in Computational Intelligence.

[21]  Mohammed Ismail,et al.  Statistical constrained optimization of analog MOS circuits using empirical performance models , 1994, Proceedings of IEEE International Symposium on Circuits and Systems - ISCAS '94.

[22]  Giuseppe Nicosia,et al.  Nominal-Yield-Area Tradeoff in Automatic Synthesis of Analog Circuits: A Genetic Programming Approach Using Immune-Inspired Operators , 2009, 2009 NASA/ESA Conference on Adaptive Hardware and Systems.

[23]  James Kennedy,et al.  Particle swarm optimization , 2002, Proceedings of ICNN'95 - International Conference on Neural Networks.

[24]  Maurice Clerc,et al.  Initialization and Displacement of the Particles in TRIBES, a Parameter-Free Particle Swarm Optimization Algorithm , 2008, Adaptive and Multilevel Metaheuristics.

[25]  Enrico Zio,et al.  System design optimization by genetic algorithms , 2000, Annual Reliability and Maintainability Symposium. 2000 Proceedings. International Symposium on Product Quality and Integrity (Cat. No.00CH37055).

[26]  R. H. Dinger.  Engineering design optimization with genetic algorithms , 1998, Northcon/98. Conference Proceedings (Cat. No.98CH36264).

[27]  Nuno Horta,et al.  Analog circuits optimization based on evolutionary computation techniques , 2010, Integr..

[28]  David W. Corne,et al.  Properties of an adaptive archiving algorithm for storing nondominated vectors , 2003, IEEE Trans. Evol. Comput..

[29]  P. Siarry,et al.  Electronic component model minimization based on log simulated annealing , 1994 .

[30]  Hak-Keung Lam,et al.  Hybrid Particle Swarm Optimization With Wavelet Mutation and Its Industrial Applications , 2008, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[31]  Esteban Tlelo-Cuautle,et al.  Evolutionary Algorithms in the Optimal Sizing of Analog Circuits , 2011, Intelligent Computational Optimization in Engineering.

[32]  Andrew R. Conn,et al.  Optimization of custom MOS circuits by transistor sizing , 1996, ICCAD 1996.

[33]  Mourad Loulou,et al.  A novel heuristic for multi-objective optimization of analog circuit performances , 2009 .

[34]  Maurice Clerc,et al.  MO-TRIBES, an adaptive multiobjective particle swarm optimization algorithm , 2011, Comput. Optim. Appl..

[35]  P. Suganthan.  Particle swarm optimiser with neighbourhood operator , 1999, Proceedings of the 1999 Congress on Evolutionary Computation-CEC99 (Cat. No. 99TH8406).

[36]  Francisco V. Fernández,et al.  Applications of evolutionary computation techniques to analog, mixed-signal and RF circuit design - an overview , 2009, 2009 16th IEEE International Conference on Electronics, Circuits and Systems - (ICECS 2009).