s: Jan. 1992 -- Dec. 1994 ffl CTI: Current Technology Index Jan./Feb. 1993 -- Jan./Feb. 1994 ffl DAI: Dissertation Abstracts International: Vol. 53 No. 1 -- Vol. 55 No. 4 (1994) ffl EEA: Electrical & Electronics Abstracts: Jan. 1991 -- Dec. 1994 ffl P: Index to Scientific & Technical Proceedings: Jan. 1986 -- Feb. 1995 (except Nov. 1994) ffl EI A: The Engineering Index Annual: 1987 -- 1992 ffl EI M: The Engineering Index Monthly: Jan. 1993 -- Dec. 1994 The following GA researchers have already kindly supplied their complete autobibliographies and/or proofread references to their papers: Dan Adler, Patrick Argos, Jarmo T. Alander, James E. Baker, Wolfgang Banzhaf, Ralf Bruns, I. L. Bukatova, Thomas Back, Yuval Davidor, Dipankar Dasgupta, Marco Dorigo, Bogdan Filipic, Terence C. Fogarty, David B. Fogel, Toshio Fukuda, Hugo de Garis, Robert C. Glen, David E. Goldberg, Martina Gorges-Schleuter, Jeffrey Horn, Aristides T. Hatjimihail, Mark J. Jakiela, Richard S. Judson, Akihiko Konaga...

The design (synthesis) of analog electrical circuits starts with a highlevel statement of the circuit's desired behavior and requires creating a circuit that satisfies the specified design goals. Analog circuit synthesis entails the creation of both the topology and the sizing (numerical values) of all of the circuit's components. The difficulty of the problem of analog circuit synthesis is well known and there is no previously known general automated technique for synthesizing an analog circuit from a high-level statement of the circuit's desired behavior. This paper presents a single uniform approach using genetic programming for the automatic synthesis of both the topology and sizing of a suite of eight different prototypical analog circuits, including a lowpass filter, a crossover (woofer and tweeter) filter, a source identification circuit, an amplifier, a computational circuit, a timeoptimal controller circuit, a temperature-sensing circuit, and a voltage reference circuit. The problem-specific information required for each of the eight problems is minimal and consists primarily of the number of inputs and outputs of the desired circuit, the types of available components, and a fitness measure that restates the highlevel

We present a method of evolving analog electronic circuits using a linear representation and a simple unfolding technique. While this representation excludes a large number of circuit topologies, it is capable of constructing many of the useful topologies seen in hand-designed circuits. Our system allows circuit size, circuit topology, and device values to be evolved. Using a parallel genetic algorithm we present initial results of our system as applied to two analog filter design problems.

We present a method of automatically generating circuit designs using evolutionary search and a set of circuit-constructing primitives arranged in a linear sequence. This representation has the desirable property that virtually all sets of circuit-constructing primitives result in valid circuit graphs. While this representation excludes certain circuit topologies, it is capable of generating a rich set of them including many of the useful topologies seen in hand-designed circuits. Our system allows circuit size (number of devices), circuit topology, and device values to be evolved. Using a parallel genetic algorithm and circuit simulation software, we present experimental results as applied to three analog filter and two amplifier design tasks. In all tasks, our system is able to generate circuits that achieve the target specifications. Although the evolved circuits exist as software models, detailed examinations of each suggest that they are electrically well behaved and thus suitable for physical implementation. The modest computational requirements suggest that the ability to evolve complex analog circuit representations in software is becoming more approachable on a single engineering workstation.

Traditionally digital filters are designed using the concept of a linear difference equation with the output response being a weighted sum of signal samples with usually floating point coefficients.

We present in this work the application of a set of different evolutionary methodologies in the problem of electronic filter design. The main objectives are to find out which constraints in the filter topologies, if any, must be observed along the evolutionary process and to study the problem of convergence to parsimonious circuits. The new area of Evolutionary Electronics is introduced, an evolutionary methodology based on variable length representation is presented and the results on the evolution of lowpass and band-pass filters are described. 1. Introduction This work focuses on the application of evolutionary systems in engineering design. Particularly, the application of evolutionary techniques in the area of electronic design and optimisation gave birth to a new and promising area of research, Evolutionary Electronics[12][5]. The aim of this area is the creation of new automation design techniques for electronic circuits, based on the Darwinian concepts of natural selection, r...

Reuse will become increasingly important as larger digital and analog circuits are created by the techniques of the field of evolvable hardware. This paper discusses the ways by which genetic programming can facilitate reuse and the associated advantages of using a developmental process.

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 timeoptimal 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.

The design (synthesis) of an analog electrical circuit 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 creating the design for 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 eight prototypical analog circuits, including a lowpass filter, a highpass filter, a bandstop filter, a tristate 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.

A mathematical formula containing one or more free variables is "general" in the sense that it represents the solution to all instances of a problem (instead of just the solution of a single instance of the problem). For example, the familiar formula for solving a quadratic equation contains free variables representing the coefficients of the to-be-solved equation.