TY - GEN
T1 - Acceleration of back propagation through initial weight pre-training with delta rule
AU - Li, Gang
AU - Alnuweiri, Hussein
AU - Wu, Yuejian
AU - Li, Hongbing
PY - 1993
Y1 - 1993
N2 - A new training strategy for Back Propagation (BP) neural networks, named Delta Pre-Training (DPT), is proposed. The core of the new training strategy is based on pre-training the initial weights for BP networks using the Delta rule, instead of using random values. After pre-training, the normal BP training procedure is carried out to complete network training. With the DPT, the convergence rate for training BP networks can be significantly improved. With regards to on-chip learning in VLSI implementations, only a little additional circuitry is required for the pre-training phase with the DPT. Simulation results using the proposed training method show its superiority over previous methods.
AB - A new training strategy for Back Propagation (BP) neural networks, named Delta Pre-Training (DPT), is proposed. The core of the new training strategy is based on pre-training the initial weights for BP networks using the Delta rule, instead of using random values. After pre-training, the normal BP training procedure is carried out to complete network training. With the DPT, the convergence rate for training BP networks can be significantly improved. With regards to on-chip learning in VLSI implementations, only a little additional circuitry is required for the pre-training phase with the DPT. Simulation results using the proposed training method show its superiority over previous methods.
UR - http://www.scopus.com/inward/record.url?scp=84943245391&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:84943245391
SN - 0780312007
T3 - 1993 IEEE International Conference on Neural Networks
SP - 580
EP - 585
BT - 1993 IEEE International Conference on Neural Networks
A2 - Anon, null
PB - Publ by IEEE
T2 - 1993 IEEE International Conference on Neural Networks
Y2 - 28 March 1993 through 1 April 1993
ER -