Abubakar, M.Y. and Tang Jung, L. (2018) Synthesis of Reversible Logic Using Enhanced Genetic Programming Approach. In: UNSPECIFIED.
Full text not available from this repository.Abstract
A new enhanced reversible logic circuit synthesis method was developed using reversible gates that include NOT, CNOT (Feynman), Toffoli, Fredkin, Swap, and Peres gates. The synthesis method was done using newly developed genetic programming. Usually previous synthesis methods that uses genetic algorithms or other similar evolutionary algorithms suffers a problem known as blotting which is a sudden uncontrolled growth of an individual (circuit), which may render the synthesis inefficient because of memory utilization, making the algorithm difficult to continue running and eventually stack in a local minima, there for an optimized reversible circuit may not be generated. In this method the algorithm used was blot free, the blotting was carefully controlled by fixing a suitable length and size of the individuals in the population. Following this approach, the cost of generating circuits was greatly reduced giving the algorithm to reach the end of the last designated generation to give out optimal or near optimal results. The results of the circuits generated using this method were compared with some of the results already in the literature, and in many cases, our results appeared to be better in terms of gate count and quantum cost metrics. © 2018 IEEE.
Item Type: | Conference or Workshop Item (UNSPECIFIED) |
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Additional Information: | cited By 1; Conference of 4th International Conference on Computer and Information Sciences, ICCOINS 2018 ; Conference Date: 13 August 2018 Through 14 August 2018; Conference Code:141665 |
Uncontrolled Keywords: | Computer circuits; Genetic algorithms; Genetic programming; Logic circuits; Logic gates, Local minimums; Memory utilization; Quantum circuit; Reversible circuits; Reversible gates; Reversible Logic; Reversible logic circuits; Synthesis method, Logic Synthesis |
Depositing User: | Mr Ahmad Suhairi UTP |
Date Deposited: | 09 Nov 2023 16:36 |
Last Modified: | 09 Nov 2023 16:36 |
URI: | https://khub.utp.edu.my/scholars/id/eprint/9843 |