A novel tree-based representation for evolving analog circuits and its application to memristor-based pulse generation circuit

Shi, Xinming1,2; Minku, Leandro L.2; Yao, Xin1,2

2022-07-01

10.1007/s10710-022-09436-w

Genetic Programming and Evolvable Machines   Impact Factor & Quartile

1389-2576

1573-7632

When applying evolutionary algorithms to circuit design automation, circuit representation is the first consideration. There have been several studies applying different circuit representations. However, they still have some problems, such as lack of design ability, which means the diversity of evolved circuits was limited by the circuit representation, and inefficient transformation from circuit representation into SPICE (Simulation Program with Integrated Circuit Emphasis) netlist. In this paper, a novel tree-based circuit representation for analog circuits is proposed, which is equipped with an intuitive and three-terminal devices friendly mapping rule between circuit representation and SPICE netlist, as well as a suitable crossover operator. Based on the proposed representation, a framework for automated analog circuit design using genetic programming is proposed to evolve both the circuit topology and device values. Three benchmark circuits are applied to evaluate the proposed approach, showing that the proposed method is feasible and evolves analog circuits with better fitness and number of components while using less fitness evaluations than existing approaches. Furthermore, considering physical scalability limits of conventional circuit elements and the increased interest in emerging technologies, a memristor-based pulse generation circuit is also evolved based on the proposed method. The feasibility of the evolved circuits is verified by circuit simulation successfully. The experiment results show that the evolved memristive circuit is more compact and has better energy efficiency compared with existing manually-designed circuits.

Automated analog circuit design Memristor Circuit representation Genetic programming Evolvable hardware

SCI ; EI

English

First ; Corresponding

Guangdong Provincial Key Laboratory[2020B121201001] ; Program for Guangdong Introducing Innovative and Enterpreneurial Teams[2017ZT07X386] ; Shenzhen Science and Technology Program[KQTD2016112514355531]

Computer Science

Computer Science, Artificial Intelligence ; Computer Science, Theory & Methods

WOS:000828420700001

SPRINGER

20223012405373

Analog circuits ; Automation ; Energy efficiency ; Genetic algorithms ; Genetic programming ; Integrated circuit manufacture ; SPICE ; Timing circuits

Energy Conservation:525.2 ; Electronic Circuits:713 ; Pulse Circuits:713.4 ; Semiconductor Devices and Integrated Circuits:714.2 ; Computer Programming:723.1 ; Computer Applications:723.5 ; Automatic Control Principles and Applications:731

Web of Science

1.Southern Univ Sci & Technol SUSTech, Dept Comp Sci & Engn, Guangdong Prov Key Lab Brain Inspired Intelligent, Shenzhen, Peoples R China
2.Univ Birmingham, Sch Comp Sci, Birmingham, W Midlands, England

Shi, Xinming,Minku, Leandro L.,Yao, Xin. A novel tree-based representation for evolving analog circuits and its application to memristor-based pulse generation circuit[J]. Genetic Programming and Evolvable Machines,2022.

Shi, Xinming,Minku, Leandro L.,&Yao, Xin.(2022).A novel tree-based representation for evolving analog circuits and its application to memristor-based pulse generation circuit.Genetic Programming and Evolvable Machines.

Shi, Xinming,et al."A novel tree-based representation for evolving analog circuits and its application to memristor-based pulse generation circuit".Genetic Programming and Evolvable Machines (2022).