This paper describes a genetic algorithm (GA) that evolves optimized sets of coefficients for one-dimensional signal reconstruction under lossy conditions due to quantization. Beg...
Abstract. We present and discuss the results of an experimental analysis in the design of Boolean networks by means of genetic algorithms. A population of networks is evolved with ...
Andrea Roli, Cristian Arcaroli, Marco Lazzarini, S...
While support vector machines (SVMs) have shown great promise in supervised classification problems, researchers have had to rely on expert domain knowledge when choosing the SVM&...
We present a new approach that is able to produce an increased fault tolerance in bio-inspired electronic circuits. To this end, we designed hardwarefriendly genetic regulatory net...
In this paper, we show how genetic programming (GP) can be used to evolve system-size-independent quantum algorithms, and present a human-competitive Quantum Fourier Transform (QF...