NDLI: Some new results in nonlinear predictive image coding using neural networks

Content Provider	IEEE Xplore Digital Library
Author	Li, H.
Copyright Year	1992
Description	Author affiliation: Dept. of Electr. Eng., Linkoping Univ., Sweden (Li, H.)
Abstract	The problem of nonlinear predictive image coding with multilayer perceptrons is considered. Some important aspects of coding, including the training of multilayer perceptrons, the adaptive scheme, and the robustness to the channel noise, are discussed in detail. Computer simulation results show that nonlinear predictors have better predictive performances than the linear DPCM. It is shown that the nonlinear predictor will produce smaller variance of predictive error than the linear predictor; that in the absence of the channel noise the nonlinear predictor can provide about a 3-dB improvement in signal-to-noise ratio over the linear one at the same transmission bit rate; and that, after being specially trained, the nonlinear predictor has a stronger robustness to the channel noise than the linear one.
Starting Page	411
Ending Page	420
File Size	288043
Page Count	10
File Format	PDF
ISBN	0780305574
DOI	10.1109/NNSP.1992.253671
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1992-08-31
Publisher Place	Denmark
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Intelligent networks Image coding Neural networks Multilayer perceptrons Multi-layer neural network Mean square error methods Channel coding Pulse modulation Noise robustness Nonhomogeneous media
Content Type	Text
Resource Type	Article

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