M.A. Keane

Automated synthesis of computational circuits using genetic programming

Analog electrical circuits that perform mathematical functions (e.g., cube root, square) are called computational circuits. Computational circuits are of special practical importance when the small number of required mathematical functions does not warrant converting an analog signal into a digital signal, performing the mathematical function in the digital domain, and then converting the result back to the analog domain. The design of computational circuits is difficult even for mundane mathematical functions and often relies on the clever exploitation of some aspect of the underlying device physics of the components. Moreover, implementation of each different mathematical function typically requires an entirely different clever insight. This paper demonstrates that computational circuits can be designed without such problem-specific insights using a single uniform approach involving genetic programming. Both the circuit topology and the sizing of all circuit components are created by genetic programming. This uniform approach to the automated synthesis of computational circuits is illustrated by evolving circuits that perform the cube root function (for which no circuit was found in the published literature) as well as for the square root, square, and cube functions.

Synthesis of topology and sizing of analog electrical circuits by means of genetic programming

Abstract The design (synthesis) of an analog electrical circuit entails the creation of both the topology and sizing (numerical values) of all of the circuits components. There has previously been no general automated technique for automatically creating the design for an analog electrical circuit from a high-level statement of the circuits desired behavior. This paper shows how genetic programming can be used to automate the design of eight prototypical analog circuits, including a lowpass filter, a highpass filter, a bandstop filter, a tri-state frequency discriminator circuit, a frequency-measuring circuit, a 60 dB amplifier, a computational circuit for the square root function, and a time-optimal robot controller circuit.

Evolving computer programs using rapidly reconfigurable field-programmable gate arrays and genetic programming

This paper describes how the massive parallelism of the rapidly reconfigurable Xilinx XC6216 FPGA (in conjunction with Virtual Computings H.O.T. Works board) can be exploited to accelerate the time-consuming fitness measurement task of genetic algorithms and genetic programming. This acceleration is accomplished by embodying each individual of the evolving population into hardware in order to perform the fitness measurement task. A 16-step sorting network for seven items was evolved that has two fewer steps than the sorting network described in the 1962 OConnor and Nelson patent on sorting networks (and the same number of steps as a 7-sorter that was devised by Floyd and Knuth subsequent to the patent and that is now known to be minimal). Other minimal sorters have been evolved.

Evolving sorting networks using genetic programming and the rapidly reconfigurable Xilinx 6216 field-programmable gate array

This paper describes how the massive parallelism of the rapidly reconfigurable Xilinx XC6216 FPCA (in conjunction with Virtual Computing Corporations HOT Works board) can be exploited to accelerate the computationally burdensome fitness measurement task of genetic algorithms and genetic programming. This acceleration is accomplished by embodying each individual of the evolving population into hardware in order to perform this time-consuming fitness measurement task. A 16-step sorting network for seven items was evolved that has two fewer steps than the sorting network described in the 1962 OConnor and Nelson patent on sorting networks (and the same number of steps as a 7-sorter that was devised by Floyd and Knuth (1973) subsequent to the patent and that is now known to be minimal).

Evolution using genetic programming of a low-distortion, 96 decibel operational amplifier

The field of engineering design offers a practical yardstick for evaluating automated techniques because the design process is usually viewed as requiring human intelligence and because design is a major activity of practicing engineers. In the design process, the design requirements specify what needs to be done. A satisfactory design tells us how to do it. In the field of electrical engineering, the design process typically involves the creation of an electrical circuit that satisfies user-specified design goals. Considerable progress has been made in automating the design of certain categories of purely digital circuits; however, the design of analog circuits and mixed analog-digital circuitshas not proved to be as amenable to automation (Rutenbar 1993). In discussing the analog dilemma, O. Aaserud and I. Ring Nielsen (1995) (not to be confused with Ivan Riis Nielsen cited later) observe, Analog designers are few and far between. In contrast to digital design, most of the analog circuits are still handcrafted by the experts or so-called zahs of analog design. The design process is characterized by a combination of experience and intuition and requires a thorough knowledge of the process characteristics and the detailed specifications of the actual product. Analog circuit design is known to be a knowledge-intensive, multiphase, iterative task, which usually stretches over a significant period of time and is performed by designers with a large portfolio of skills. It is therefore considered by many to be a form of art rather than a science. Of course, engineers employ human reasoning abilities and intelligence in designing complex structures. In contrast, nature employs an entirely different approach to design. In nature, complex structures are designed by means of evolution and natural selection. This suggests the possibility of applying the techniques of evolutionary computation in order to automate the design of complex structures. Genetic algorithms have been applied to the problem of circuit synthesis. A CMOS operational amplifier (op amp) circuit was designed using a modified version of the genetic algorithm (Kruiskamp and Leenaerts 1995); however, the topology of each op amp was one of 24 pre-selected topologies based on the conventional human-designed stages of an op amp. Thompson (1996) used a genetic algorithm to evolve a frequency discriminator on a Xilinx 6216 reconfigurable digital gate array operating in analog mode. Holland (1975) described how an analog of the naturally-occurring evolutionary process can be applied to solving scientific and engineering problems using what is now called the

Evolutionary Design of Analog Electrical Circuits Using Genetic Programming

The design (synthesis) of analog electrical circuits entails the creation of both the topology and sizing (numerical values) of all of the circuit’s components. There has previously been no general automated technique for automatically designing an analog electrical circuit from a high-level statement of the circuit’s desired behavior. This paper shows how genetic programming can be used to automate the design of both the topology and sizing of a suite of five prototypical analog circuits, including a lowpass filter, a tri-state frequency discriminator circuit, a 60 dB amplifier, a computational circuit for the square root, and a time-optimal robot controller circuit. All five of these genetically evolved circuits constitute instances of an evolutionary computation technique solving a problem that is usually thought to require human intelligence.

Design of a High-Gain Operational Amplifier and Other Circuits by Means of Genetic Programming

This paper demonstrates that a design for a low-distortion high-gain 96 decibel (64,860 -to-1) operational amplifier (including both circuit topology and component sizing) can be evolved using genetic programming.

Automatic synthesis using genetic programming of both the topology and sizing for five post-2000 patented analog and mixed analog-digital circuits

Recent work has demonstrated that genetic programming can automatically create both the topology (graphical structure) and sizing (numerical component values) for analog electrical circuits merely by specifying the circuits high level behavior (e.g., its desired or observed output, given its input). This automatic synthesis of analog circuits is accomplished using only tools for the analysis of circuits (e.g., a circuit simulator) and without relying on any human know-how concerning the synthesis of circuits. This paper applies genetic programming to the automatic synthesis of five analog and mixed analog-digital circuits that duplicate the functionality of circuits patented after January 1, 2000. The five automatically created circuits read on some (but not all) of the elements of various claims of the patents involved (and therefore do not infringe). The described method can be used as an automated invention machine either to produce potentially patentable new circuits or to engineer around existing patents.

On the theory of designing circuits using genetic programming and a minimum of domain knowledge

The problem of analog circuit design is a difficult problem that is generally viewed as requiring human intelligence to solve. Considerable progress has been made in automating the design of certain categories of purely digital circuits; however, the design of analog electrical circuits and mixed analog-digital circuits has not proved to be as amenable to automation. When critical analog circuits are required for a project, skilled and highly trained experts are necessary. Previous work on applying genetic programming to the design of analog circuits has proved to be successful at evolving a wide variety of circuits, including filters, amplifiers and computational circuits; however, these previous approaches have required the specification of an appropriate embryonic circuit. This paper explores a method to eliminate even this small amount of problem-specific knowledge, and, in addition, proves that the representation used is capable of producing all circuits.