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SOM neural network design – A new Simulink library based approach targeting FPGA implementation

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  • Tisan, A.
  • Cirstea, M.

Abstract

The paper presents a method for FPGA implementation of Self-Organizing Map (SOM) artificial neural networks with on-chip learning algorithm. The method aims to build up a specific neural network using generic blocks designed in the MathWorks Simulink environment. The main characteristics of this original solution are: on-chip learning algorithm implementation, high reconfiguration capability and operation under real time constraints. An extended analysis has been carried out on the hardware resources used to implement the whole SOM network, as well as each individual component block.

Suggested Citation

  • Tisan, A. & Cirstea, M., 2013. "SOM neural network design – A new Simulink library based approach targeting FPGA implementation," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 91(C), pages 134-149.
    • Handle: RePEc:eee:matcom:v:91:y:2013:i:c:p:134-149
    DOI: 10.1016/j.matcom.2012.05.006
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    References listed on IDEAS

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    1. Larsson, Jonas, 2010. "Monte Carlo implementation of financial simulation on Cell/B.E. multi-core processor," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 81(3), pages 578-587.
    2. Bruti-Liberati, Nicola & Martini, Filippo & Piccardi, Massimo & Platen, Eckhard, 2008. "A hardware generator of multi-point distributed random numbers for Monte Carlo simulation," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 77(1), pages 45-56.
    3. Ricci, Francesco & Le-Huy, Hoang, 2003. "Modeling and simulation of FPGA-based variable-speed drives using Simulink," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 63(3), pages 183-195.
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    Cited by:

    1. Pedro Ponce & Brian Anthony & Aniruddha Suhas Deshpande & Arturo Molina, 2023. "A Low-Cost Microcontroller-Based Normal and Abnormal Conditions Classification Model for Induction Motors Using Self-Organizing Feature Maps (SOFM)," Energies, MDPI, vol. 16(21), pages 1-24, October.

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