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  1. Ana Sayfa
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Yazar "Karakuzu, Cihan" seçeneğine göre listele

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    FPGA implementation of neuro-fuzzy system with improved PSO learning
    (PERGAMON-ELSEVIER SCIENCE LTD, 2016) Karakuzu, Cihan; Karakaya, Fuat; Cavuslu, Mehmet Ali
    This paper presents the first hardware implementation of neuro-fuzzy system (NFS) with its metaheuristic learning ability on field programmable gate array (FPGA). Metaheuristic learning of NFS for all of its parameters is accomplished by using the improved particle swarm optimization (iPSO). As a second novelty, a new functional approach, which does not require any memory and multiplier usage, is proposed for the Gaussian membership functions of NFS. NFS and its learning using iPSO are implemented on Xilinx Virtex5 xc5vlx110-3ff1153 and efficiency of the proposed implementation tested on two dynamic system identification problems and licence plate detection problem as a practical application. Results indicate that proposed NFS implementation and membership function approximation is as effective as the other approaches available in the literature but requires less hardware resources. (C) 2016 Elsevier Ltd. All rights reserved.
  • Küçük Resim Yok
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    Neural identification of dynamic systems on FPGA with improved PSO learning
    (ELSEVIER SCIENCE BV, 2012) Cavuslu, Mehmet Ali; Karakuzu, Cihan; Karakaya, Fuat
    This work introduces hardware implementation of artificial neural networks (ANNs) with learning ability on field programmable gate array (FPGA) for dynamic system identification. The learning phase is accomplished by using the improved particle swarm optimization (PSO). The improved PSO is obtained by modifying the velocity update function. Adding an extra term to the velocity update function reduced the possibility of stucking in a local minimum. The results indicates that ANN, trained using improved PSO algorithm, converges faster and produces more accurate results with a little extra hardware utilization cost. (C) 2012 Elsevier B.V. All rights reserved.

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