Handbook of image processing operators
Handbook of image processing operators
Human iris detection using fast cooperative modular neural nets and image decomposition
Machine Graphics & Vision International Journal
Complex-Valued Neural Networks: Theories and Applications (Series on Innovative Intelligence, 5)
Complex-Valued Neural Networks: Theories and Applications (Series on Innovative Intelligence, 5)
New fast normalized neural networks for pattern detection
Image and Vision Computing
Complex-valued multistate neural associative memory
IEEE Transactions on Neural Networks
Fast information processing over business networks
AIC'09 Proceedings of the 9th WSEAS international conference on Applied informatics and communications
Fast human motion tracking by using high speed neural
SSIP '09/MIV'09 Proceedings of the 9th WSEAS international conference on signal, speech and image processing, and 9th WSEAS international conference on Multimedia, internet & video technologies
A new expert system for pediatric respiratory diseases by using neural networks
AICT'11 Proceedings of the 2nd international conference on Applied informatics and computing theory
A new fast neural network model
ACACOS'12 Proceedings of the 11th WSEAS international conference on Applied Computer and Applied Computational Science
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This paper presents a new approach to speed up the operation of time delay neural networks for detecting a record in databases. The entire data are collected together in a long vector and then tested as a one input pattern. The proposed fast time delay neural networks (FTDNNs) use cross correlation in the frequency domain between the tested data and the input weights of neural networks. It is proved mathematically and practically that the number of computation steps required for the presented time delay neural networks is less than that needed by conventional time delay neural networks (CTDNNs). Simulation results using MATLAB confirm the theoretical computations.