TY - GEN
T1 - Efficient pattern recognition using the frequency response of a spiking neuron
AU - Valadez-Godínez, Sergio
AU - González, Javier
AU - Sossa, Humberto
N1 - Publisher Copyright:
© Springer International Publishing AG 2017.
PY - 2017
Y1 - 2017
N2 - In previous works, a successful scheme using a single Spiking Neuron (SN) to solve complex problems in pattern recognition has been proposed. This consists in using the firing frequency response to classify a given input pattern, which is multiplied by a weight vector to produce a constant stimulation current. The weight vector is adjusted by an evolutionary strategy where the objective is to obtain an optimal frequency separation. The problem is that the SN has to be numerically simulated several times when the weight vector is being adjusted. In this work, we propose fitting the SN frequency response curve to a piecewise linear function to be used instead of the costly SN simulation. A high fitting degree was found, but, more importantly, the computational cost of the training and testing phases was drastically reduced.
AB - In previous works, a successful scheme using a single Spiking Neuron (SN) to solve complex problems in pattern recognition has been proposed. This consists in using the firing frequency response to classify a given input pattern, which is multiplied by a weight vector to produce a constant stimulation current. The weight vector is adjusted by an evolutionary strategy where the objective is to obtain an optimal frequency separation. The problem is that the SN has to be numerically simulated several times when the weight vector is being adjusted. In this work, we propose fitting the SN frequency response curve to a piecewise linear function to be used instead of the costly SN simulation. A high fitting degree was found, but, more importantly, the computational cost of the training and testing phases was drastically reduced.
KW - Computational cost
KW - Curve fitting
KW - Differential evolution
KW - Evolutionary strategy
KW - Firing Rate
KW - Frequency Response Curve
KW - Izhikevich
KW - Pattern recognition
KW - Piecewise linear function
KW - Spiking Neuron
UR - http://www.scopus.com/inward/record.url?scp=85021210639&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-59226-8_6
DO - 10.1007/978-3-319-59226-8_6
M3 - Contribución a la conferencia
SN - 9783319592251
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 53
EP - 62
BT - Pattern Recognition - 9th Mexican Conference, MCPR 2017, Proceedings
A2 - Carrasco-Ochoa, Jesus Ariel
A2 - Martinez-Trinidad, Jose Francisco
A2 - Olvera-Lopez, Jose Arturo
PB - Springer Verlag
T2 - 9th Mexican Conference on Pattern Recognition, MCPR 2017
Y2 - 21 June 2017 through 24 June 2017
ER -