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RBF Neural Network with Linearly Approximated Functions on FPGA

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F07%3A03132899" target="_blank" >RIV/68407700:21230/07:03132899 - isvavai.cz</a>

  • Result on the web

  • DOI - Digital Object Identifier

Alternative languages

  • Result language

    angličtina

  • Original language name

    RBF Neural Network with Linearly Approximated Functions on FPGA

  • Original language description

    This article is focused on implementation of the Radial Basis Function (RBF) neural network by using linearly approximated functions. Presented approach is suitable for hardware implementations on FPGA that may accelerate simulation of neural networks ofthis type. Linearly approximated functions are based on shift and addition operations without necessity of multipliers and look-up tables for implementing activation functions. Further, we present results of our pilot implementation on FPGA consisting of arithmetic blocks for neural calculations, memory blocks for prototype storage, and controllers. We provide a number of parameters like maximum clock frequency or number of function blocks that characterize the resulting synthesized FPGA design.

  • Czech name

    RBF neuronová síť s linearně aproximovanými funkcemi na FPGA

  • Czech description

    Tento článek je zaměřen na implementaci neuronové sítě typu RBF za použití lineárně aproximovaných funkcí. Prezentovaný přístup je vhodný pro hardwarovou implementaci na čipu FPGA. Lin. approx. funkce jsou implementovány pomocí operací sečti a posuv beznutnosti násobení či tabulek pro násobení. V článku jsou uvedena měření zdrojů FPGA pro různé instance RBF sítě.

Classification

  • Type

    D - Article in proceedings

  • CEP classification

    IN - Informatics

  • OECD FORD branch

Result continuities

  • Project

  • Continuities

    Z - Vyzkumny zamer (s odkazem do CEZ)

Others

  • Publication year

    2007

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Article name in the collection

    Proceedings of the 6th EUROSIM Congress on Modelling and Simulation

  • ISBN

    978-3-901608-32-2

  • ISSN

  • e-ISSN

  • Number of pages

    6

  • Pages from-to

  • Publisher name

    ARGESIM

  • Place of publication

    Vienna

  • Event location

    Ljubljana

  • Event date

    Sep 9, 2007

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article