TY - JOUR
T1 - Pattern recognition and classification using weightless neural networks (WNN) and steinbuch lernmatrix
AU - Argüelles C., Amadeo J.
AU - De Díaz Leon S, J. L.
AU - Yáñez M., Cornelio
AU - Camacho N., Oscar
PY - 2005
Y1 - 2005
N2 - This proposal presents a novel use of Weightless Neural Networks (WNN) and Steinbuch Lernmatrix for pattern recognition and classification. High speed of learning, easy of implementation and flexibility given by WNN, combined with the learning capacity, recovery efficiency, noise immunity and fast processing shown by Steinbuch Lernmatrix are key factors considered on the pattern recognition exposed by the suggested model. For experimental purposes, the fundamental pattern sets are built and provided to the model under the learning phase. The additive, subtractive and mixed noises are applied to fundamental patterns to check out the response of the model during the recovery phase. Field Programmable Gate arrays are used in the implementation of such model, since it allows custom user-defined models to be embedded in a reconfigurable hardware platform, and provides block memories and dedicated multipliers suitable for the model.
AB - This proposal presents a novel use of Weightless Neural Networks (WNN) and Steinbuch Lernmatrix for pattern recognition and classification. High speed of learning, easy of implementation and flexibility given by WNN, combined with the learning capacity, recovery efficiency, noise immunity and fast processing shown by Steinbuch Lernmatrix are key factors considered on the pattern recognition exposed by the suggested model. For experimental purposes, the fundamental pattern sets are built and provided to the model under the learning phase. The additive, subtractive and mixed noises are applied to fundamental patterns to check out the response of the model during the recovery phase. Field Programmable Gate arrays are used in the implementation of such model, since it allows custom user-defined models to be embedded in a reconfigurable hardware platform, and provides block memories and dedicated multipliers suitable for the model.
KW - Field Programmable Gate Arrays
KW - Pattern Recognition
KW - Steinbuch Lernmatrix
KW - Weightless Neural Network
UR - http://www.scopus.com/inward/record.url?scp=30844445378&partnerID=8YFLogxK
U2 - 10.1117/12.621783
DO - 10.1117/12.621783
M3 - Artículo de la conferencia
AN - SCOPUS:30844445378
SN - 0277-786X
VL - 5916
SP - 1
EP - 8
JO - Proceedings of SPIE - The International Society for Optical Engineering
JF - Proceedings of SPIE - The International Society for Optical Engineering
M1 - 59160P
T2 - Mathematical Methods in Pattern and Image Analysis
Y2 - 3 August 2005 through 4 August 2005
ER -