Hardware Implementation of Feed forward Multilayer Neural Network Using the RFNNA Design Methodology
This paper proposes a novel hardware architecture for neural network that shall be named Reconfigurable Feedforward Neural Network Architecture (RFNNA) processor [1]. This neural network architecture aims to minimize the logic circuit as required by a fully parallel implementation. The Field-Program...
Saved in:
Main Authors: | Sun, Ivan Teh Fu, Zain Ali, Noohul Basheer, Hussin, Fawnizu Azmadi |
---|---|
Format: | Conference or Workshop Item |
Published: |
2004
|
Online Access: | http://eprints.utp.edu.my/12001/ |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Hardware Implementation of Feed forward Multilayer Neural Network Using the RFNNA Design Methodology
by: Sun, Ivan Teh Fu, et al.
Published: (2004) -
Hardware Implementation of an Optimized Processor Architecture for SOBEL Image Edge Detection Operator
by: M. Osman, Zahraa Elhassan, et al.
Published: (2010) -
SEOS: Hardware Implementation of Real-Time Operating System for Adaptability
by: Ong, Soon Ee, et al.
Published: (2013) -
Preprocessing And Pretraining Of Multilayer Feed Forward Neural Network
by: Asadi, Roya
Published: (2009) -
A methodology building for multilayer feed-forward neural network (MLFFNN): an application in biometry modelling
by: Adnan, Mohamad Nasarudin
Published: (2023)