Neural network based lossless coding schemes for telemetry data

Citation

Logeswaran, R. and Eswaran, C. (1999) Neural network based lossless coding schemes for telemetry data. In: IEEE 1999 International Geoscience and Remote Sensing Symposium, 1999. IGARSS '99 Proceedings. IEEE Xplore, 2057 -2059. ISBN 0-7803-5207-6

[img] Text
00775030.pdf - Published Version
Restricted to Repository staff only

Download (341kB)

Abstract

This paper proposes new coding schemes based on neural networks for the compression of telemetry data. It is shown that neural network predictors can be used successfully in a two-stage lossless compression scheme. Single-layer perceptron, multi-layer perceptron and recurrent network models are investigated for this purpose. The proposed neural network based coding schemes are tested using different telemetry data files. For the encoder in the second stage, arithmetic and Huffman coding are employed. It is found that the performance of neural network based schemes is comparable and in some cases better than that of the methods using linear predictors such as FIR and lattice filters

Item Type: Book Section
Subjects: T Technology > T Technology (General)
Divisions: Faculty of Engineering (FOE)
Depositing User: Ms Suzilawati Abu Samah
Date Deposited: 08 Jan 2014 04:11
Last Modified: 08 Jan 2014 04:11
URII: http://shdl.mmu.edu.my/id/eprint/4746

Downloads

Downloads per month over past year

View ItemEdit (login required)