Applications of Evolutionary Algorithms in the Design Automation of Analog Integrated Circuits

Tlelo-Cuau, E.; Guerra-Gom, I.; Duarte-Vil, M. A.; Frag, Luis G. de La; Flores-Bec, G.; Reyes-Salg, G.; Reyes-Garc, C. A.; Rodríguez, Gilberto Domínguez

doi:10.3923/jas.2010.1859.1872

Cited by 47 publications

(19 citation statements)

References 59 publications

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“…This can be able to reflect eh potential performance of a circuit and reduce the risk of deleting a circuit with a good developing potential. Tlelo-Cuautle et al (2010) presented the art of applying evolutionary algorithms for the synthesis and sizing of analog Integrated Circuits. A survey of people working in this field and major advances and discoveries are summarized and finally several open research problems are listed to improve the electronic design automation tools for analog integrated circuits by applying evolutionary algorithms.…”

Section: Circuit Design Flowmentioning

confidence: 99%

An Optimized Device Sizing of Analog Circuits using Particle Swarm Optimization

Arturo¹

2012

Journal of Computer Science

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Problem statement: Day by day more and more products rely on analog circuits to improve the speed and reduce the power consumption(Products rely on analog circuits to improve the speed and reduce the power consumption day by day more and more.). For the VLSI implementation analog circuit design plays an important role. This analog circuit synthesis might be the most challenging and time-consumed task, because it does not only consist of topology and layout synthesis but also of component sizing. Approach: A Particle Swarm Optimization (PSO) technique for the optimal design of analog circuits. Analog signal processing finds many applications and widely uses OpAmp based amplifiers, mixers, comparators. and filters. Results: A two-stage opamp (Miller Operational Trans-conductance Amplifier (OTA)) is considered for the synthesis that satisfies certain design specifications. Performance has been evaluated with the Simulation Program with Integrated Circuit Emphasis (SPICE) circuit simulator until optimal sizes of the transistors are found. Conclusion: The output of the simulation for the two-stage opamp shows that the PSO technique is an accurate and promising approach in determining the device sizes in an analog circuit.

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Section: Circuit Design Flowmentioning

confidence: 99%

An Optimized Device Sizing of Analog Circuits using Particle Swarm Optimization

Arturo¹

2012

Journal of Computer Science

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“…The synthesis begins by selecting the device to be created, then the BGEs from Sect. 2 are manipulated by a genetic process [28]. The main steps are:…”

Section: Automatic Synthesis Of Mixed-mode Circuit Topologiesmentioning

confidence: 99%

“…In this work, we introduce the automatic synthesis of mixed-mode active devices, such as current conveyors and CFOAs, using a simple genetic algorithm [26,28]. That way, in Sect.…”

mentioning

confidence: 99%

Binary Genetic Encoding for the Synthesis of Mixed-Mode Circuit Topologies

Duarte-Villaseñor

Tlelo‐Cuautle

Fraga

2011

Circuits Syst Signal Process

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A binary genetic encoding (BGE) representation for the automatic synthesis of mixed-mode circuit topologies, is introduced. First, the genetic encoding of unity-gain cells (UGCs), such as voltage (VF) and current followers (CF), and voltage (VM) and current mirrors (CM), is presented. New BGEs for the VM and CM are introduced. Second, the UGC's chromosomes are combined to synthesize mixed-mode circuit-topologies, namely current conveyors and current-feedback operational amplifiers (CFOA). Five strategies for the combination or superimposing of UGCs are introduced. The proposed BGE has been implemented in MATLAB TM , and links SPICE to evaluate the populations with different integrated circuit technologies. Some new synthesized circuit topologies are shown along with their chromosome description.

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“…Fortunately, today's computer technology and circuit theory make the use of unconventional methods in analog circuit design possible. The genetic algorithm (GA) is used as a search algorithm in different analog circuit design problems successfully [1][2][3][4][5]. Though the GA is inspired by natural evolution, it is hard to mimic all dynamics of natural evolution in the GA. One of these dynamics is speciation.…”

Section: Introductionmentioning

confidence: 99%

Speciation-based genetic algorithm in analog circuit design

Karci¹,

Tohumoğlu²,

Nacaroğlu³

2016

Turk J Elec Eng & Comp Sci

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This paper presents a speciation procedure that improves the local search capability of the genetic algorithm in analog circuit design. There is no need for additional circuit simulation in order to apply this procedure. The procedure is tested in Gaussian, sigmoid, cube, and square circuit design problems. Two sets of 125 simulations with the same seed values are performed for each problem using both the proposed procedure and the canonical genetic algorithm. The simulation results show that the method is statistically better than the canonical genetic algorithm, which suffers from bad locality. The effects of the population size and speciation threshold coefficient on the performance of the speciation algorithm are investigated. Confidence intervals of the simulation results are calculated. The results show that the speciation procedure improves the quality of solutions with at least 99% confidence, and the effectiveness of the method, which is statistically determined, increases in small populations.

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Applications of Evolutionary Algorithms in the Design Automation of Analog Integrated Circuits

Cited by 47 publications

References 59 publications

An Optimized Device Sizing of Analog Circuits using Particle Swarm Optimization

An Optimized Device Sizing of Analog Circuits using Particle Swarm Optimization

Binary Genetic Encoding for the Synthesis of Mixed-Mode Circuit Topologies

Speciation-based genetic algorithm in analog circuit design

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