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A neural-network-based system for testing speakers

Content Provider	IEEE Xplore Digital Library
Author	Er, M.J. Ooi, T.H. Toh, C.T. Toh, F.S.
Copyright Year	1994
Description	Author affiliation: Sch. of Electr. & Electron. Eng., Nanyang Technol. Inst., Singapore (Er, M.J.; Ooi, T.H.; Toh, C.T.; Toh, F.S.)
Abstract	The paper presents a high performance neural network based system for testing speakers. A multilayer neural network system with a backpropagation learning algorithm is employed. It consists of 53 input nodes, one hidden layer with 10 nodes and 1 output node. The normalized total harmonics distortion (THD) values of the speakers at different frequencies are fed to the input of the system. The average training time is 40 minutes (on a 486DX 50 MHz PC) for a training size of 100 patterns. The neural network based system is able to achieve a remarkable accuracy of 95%.
Starting Page	907
Ending Page	912
File Size	359768
Page Count	6
File Format	PDF
ISBN	0780318625
DOI	10.1109/TENCON.1994.369179
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1994-08-22
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	System testing Frequency response Neural networks Inspection Erbium Audio recording Fatigue Stress Fault tolerance Working environment noise
Content Type	Text
Resource Type	Article

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