Signals, systems, and transforms
Signals, systems, and transforms
Genetic programming: on the programming of computers by means of natural selection
Genetic programming: on the programming of computers by means of natural selection
Power minimization in IC design: principles and applications
ACM Transactions on Design Automation of Electronic Systems (TODAES)
Evolutionary algorithms in theory and practice: evolution strategies, evolutionary programming, genetic algorithms
Evolutionary algorithms for VLSI CAD
Evolutionary algorithms for VLSI CAD
Communications of the ACM
Analysis of unconventional evolved electronics
Communications of the ACM
Digital Filters and Signal Processing
Digital Filters and Signal Processing
Architectures for Digital Signal Processing
Architectures for Digital Signal Processing
Proceedings of the European Conference on Genetic Programming
Explorations in design space: unconventional electronics designthrough artificial evolution
IEEE Transactions on Evolutionary Computation
Image Filter Design with Evolvable Hardware
Proceedings of the Applications of Evolutionary Computing on EvoWorkshops 2002: EvoCOP, EvoIASP, EvoSTIM/EvoPLAN
Improving FSM evolution with progressive fitness functions
Proceedings of the 14th ACM Great Lakes symposium on VLSI
An evolvable hardware system in Xilinx Virtex II Pro FPGA
International Journal of Innovative Computing and Applications
Automatic HDL generation for ASIC designs
SMO'06 Proceedings of the 6th WSEAS International Conference on Simulation, Modelling and Optimization
On Evolutionary Synthesis of Linear Transforms in FPGA
ICES '08 Proceedings of the 8th international conference on Evolvable Systems: From Biology to Hardware
GAME-HDL: implementation of evolutionary algorithms using hardware description languages
EvoWorkshops'03 Proceedings of the 2003 international conference on Applications of evolutionary computing
On the practical limits of the evolutionary digital filter design at the gate level
EuroGP'06 Proceedings of the 2006 international conference on Applications of Evolutionary Computing
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An evolutionary algorithm is used to design a finite impulse response digital filter with reduced power consumption. The proposed design approach combines genetic optimization and simulation methodology, to evaluate a multi-objective fitness function which includes both the suitability of the filter transfer function and the transition activity of digital blocks. The proper choice of fitness function and selection criteria allows the genetic algorithm to perform a better search within the design space, thus exploring possible solutions which are not considered in the conventional structured design methodology. Although the evolutionary process is not guaranteed to generate a filter fully compliant to specifications in every run, experimental evidence shows that, when specifications are met, evolved filters are much better than classical designs both in terms of power consumption and in terms of area, while maintaining the same performance.