TY - GEN
T1 - Opposite transfer functions and backpropagation through time
AU - Ventresca, Mario
AU - Tizhoosh, Hamid R.
PY - 2007
Y1 - 2007
N2 - Backpropagation through time is a very popular discrete-time recurrent neural network training algorithm. However, the computational time associated with the learning process to achieve high accuracy is high. While many approaches have been proposed that alter the learning algorithm, this paper presents a computationally inexpensive method based on the concept of opposite transfer functions to improve learning in the backpropagation through time algorithm. Specifically, we will show an improvement in the accuracy, stability as well as an acceleration in learning time. We will utilize three common benchmarks to provide experimental evidence of the improvements.
AB - Backpropagation through time is a very popular discrete-time recurrent neural network training algorithm. However, the computational time associated with the learning process to achieve high accuracy is high. While many approaches have been proposed that alter the learning algorithm, this paper presents a computationally inexpensive method based on the concept of opposite transfer functions to improve learning in the backpropagation through time algorithm. Specifically, we will show an improvement in the accuracy, stability as well as an acceleration in learning time. We will utilize three common benchmarks to provide experimental evidence of the improvements.
KW - Backpropagation through time
KW - Opposite transfer functions
KW - Opposition-based learning
UR - http://www.scopus.com/inward/record.url?scp=34548819318&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=34548819318&partnerID=8YFLogxK
U2 - 10.1109/FOCI.2007.371529
DO - 10.1109/FOCI.2007.371529
M3 - Conference contribution
AN - SCOPUS:34548819318
SN - 1424407036
SN - 9781424407033
T3 - Proceedings of the 2007 IEEE Symposium on Foundations of Computational Intelligence, FOCI 2007
SP - 570
EP - 577
BT - Proceedings of the 2007 IEEE Symposium on Foundations of Computational Intelligence, FOCI 2007
T2 - 2007 IEEE Symposium on Foundations of Computational Intelligence, FOCI 2007
Y2 - 1 April 2007 through 5 April 2007
ER -