TY - CHAP
T1 - Morphological neural networks with dendrite computation
T2 - A geometrical approach
AU - Barrón, Ricardo
AU - Sossa, Humberto
AU - Cortés, Héctor
PY - 2003
Y1 - 2003
N2 - Morphological neural networks consider that the information entering a neuron is affected additively by a conductivity factor called synaptic weight. They also suppose that the input channels account with a saturation level mathematically modeled by a MAX or MIN operator. This, from a physiological point of view, appears closer to reality than the classical neural model, where the synaptic weight interacts with the input signal by means of a product; the input channel forms an average of the input signals. In this work we introduce some geometrical aspects of dendrite processing that easily allow visualizing the classification regions, providing also an intuitive perspective of the production and training of the net.
AB - Morphological neural networks consider that the information entering a neuron is affected additively by a conductivity factor called synaptic weight. They also suppose that the input channels account with a saturation level mathematically modeled by a MAX or MIN operator. This, from a physiological point of view, appears closer to reality than the classical neural model, where the synaptic weight interacts with the input signal by means of a product; the input channel forms an average of the input signals. In this work we introduce some geometrical aspects of dendrite processing that easily allow visualizing the classification regions, providing also an intuitive perspective of the production and training of the net.
UR - http://www.scopus.com/inward/record.url?scp=35248886717&partnerID=8YFLogxK
U2 - 10.1007/978-3-540-24586-5_72
DO - 10.1007/978-3-540-24586-5_72
M3 - Capítulo
AN - SCOPUS:35248886717
SN - 354020590X
SN - 9783540205906
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 588
EP - 595
BT - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
A2 - Sanfeliu, Alberto
A2 - Ruiz-Shulcloper, Jose
PB - Springer Verlag
ER -