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A genetic programming-based circuit synthesis method is proposed that enables to globally optimize the number of gates in circuits that have already been synthesized using common methods such as ABC and SIS. The main contribution is a proposal for a new fitness function that enables to significantly reduce the fitness evaluation time in comparison to the state of the art. The fitness function performs...
In order to design cellular automata rules by means of evolutionary algorithms, high computational demands need to be met. This problem may be partially solved by parallelization. Since parallel supercomputers and server clusters are expensive and often overburdened, this paper proposes the evolution of cellular automata rules on small and inexpensive graphic processing units. The main objective of...
The paper deals with evolutionary design of impulse burst noise filters. As proposed filters utilize the filtering window of 5times5 pixels, the design method has to be able to manage 25 eight-bit inputs. The large number of inputs results in an evolutionary algorithm not able to produce reasonably working filters because of the so-called scalability problem of evolutionary circuit design. However,...
Polymorphic digital circuits contain ordinary and polymorphic gates. In the past, Cartesian genetic programming (CGP) has been applied to synthesize polymorphic circuits at the gate level. However, this approach is not scalable. Experimental results presented in this paper indicate that larger and more efficient polymorphic circuits can be designed by a combination of conventional design methods (such...
REconfigurable POlymorphic MOdule (REPOMO) will be a new reconfigurable chip intended for experimental applications of evolvable and polymorphic hardware. In this paper, we analyze various reconfiguration options for this platform with the aim of finding such a reconfiguration subsystem which maximizes the success rate of evolutionary circuit design conducted using REPOMO. An interesting outcome of...
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