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- W3204693558 abstract "A new fast vector quantization along with a novel fast heuristic optimization algorithm has been proposed in this paper that efficiently boosts the process of finding the global optimum region in the search region. Stochastic variables are used in this algorithm to excel the speed of exploration and exploitation and at the same time making the whole process of vector quantization (VQ) computationally efficient. The search domain gradually shrinks to make algorithm effective and efficient. On comparing the simulation results of VQ based on particle swarm optimization (PSO), quantum particle swarm optimization (QPSO) and firefly algorithm (FFA) using some well- known benchmark functions has validated the efficiency of the algorithm. In finding the global optimum point, the proposed algorithm decreases the computing time 44 % relative to others. Vector quantization based image compression is a NP-hard problem has been successfully and efficiently solved in this proposed work." @default.
- W3204693558 created "2021-10-11" @default.
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- W3204693558 date "2021-01-01" @default.
- W3204693558 modified "2023-09-28" @default.
- W3204693558 title "Boosting vector quantization technique using fast directional shrinking search optimization (DSSO) algorithm" @default.
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- W3204693558 doi "https://doi.org/10.1063/5.0066710" @default.
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