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Transactions: WSEAS TRANSACTIONS ON SIGNAL PROCESSING
Transactions ID Number: 32-627
Full Name: Hazem El-Bakry
Position: Assistant Professor
Age: ON
Sex: Male
Address: P.O.Box: 76, Masnoura
Country: EGYPT
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E-mail address: helbakry50@yahoo.com
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Title of the Paper: Fast Word Detection in a Speech Using New High Speed Time Delay Neural Networks
Authors as they appear in the Paper: Hazem M. El-Bakry, Nikos Mastorakis
Email addresses of all the authors: helbakry50@yahoo.com
Number of paper pages: 10
Abstract: This paper presents a new approach to speed up the operation of time delay neural networks for fast detecting a word in a speech. 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.
Keywords: Fast Time Delay Neural Networks, Cross Correlation, Frequency Domain, Word Detection in a speech
EXTENSION of the file: .doc
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