The sound gallery---an interactive A-life artwork
Creative evolutionary systems
Run-Time Reconfigurable Systems for Digital Signal Processing Applications: A Survey
Journal of VLSI Signal Processing Systems
Run-time reconfigurable systems for digital signal processing applications: a survey
Journal of VLSI Signal Processing Systems
Proceedings of the 10th annual conference companion on Genetic and evolutionary computation
Review: Neuromolecularware and its application to pattern recognition
Expert Systems with Applications: An International Journal
Proceedings of the 11th Annual Conference Companion on Genetic and Evolutionary Computation Conference: Late Breaking Papers
Evolution of self-diagnosing hardware
ICES'03 Proceedings of the 5th international conference on Evolvable systems: from biology to hardware
Proceedings of the 12th annual conference companion on Genetic and evolutionary computation
GECCO 2011 tutorial: cartesian genetic programming
Proceedings of the 13th annual conference companion on Genetic and evolutionary computation
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
GECCO 2012 tutorial: cartesian genetic programming
Proceedings of the 14th annual conference companion on Genetic and evolutionary computation
GECCO 2013 tutorial: cartesian genetic programming
Proceedings of the 15th annual conference companion on Genetic and evolutionary computation
Hi-index | 0.01 |
A small gate array is evolved extrinsically to carry out a low pass filtering task defined over fifteen different frequencies. The circuit is evolved by assessing its response digitised sine waves. Two different fitness functions are contrasted. One is based on computing the sum of the absolute differences between the actual response and that desired, the other is defined by examining characteristics of the Discrete Fourier Transform of the output. The gate arrays possess some linear properties, which means that they are capable of filtering composite signals which have not been encountered in training. This includes signals with noise added and with frequencies which are not in the training set.