Publication

The distributed Karhunen-Loeve transform

Martin Vetterli, Michael Christoph Gastpar, Pier Luigi Dragotti
2003
Reports

Abstract

The Karhunen-Loeve transform (KLT) is a key element of many signal processing tasks, including approximation, compression, and classification. Many recent applications involve {\em distributed} signal processing where it is not generally possible to apply the KLT to the signal; rather, the KLT must be approximated in a distributed fashion. This paper investigates such distributed approximations to the KLT. First, we present explicit solutions to special cases, including a partial KLT (where only a subset of the sources is observed), a conditional KLT (where some sources act as side information), and the combination of these two special cases. These results are used to derive an algorithm that finds the best distributed approximation to the KLT. Applications of our results to sensor networks and to distributed databases are discussed

Official source

https://infoscience.epfl.ch/entities/publication/0f15b431-82e6-42b7-a792-0f0b97092617

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Martin Vetterli, Michael Christoph Gastpar, Pier Luigi Dragotti
2003
Reports

Abstract

Official source

https://infoscience.epfl.ch/entities/publication/0f15b431-82e6-42b7-a792-0f0b97092617

About this result

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Signal processing

Signal processing is an electrical engineering subfield that focuses on analyzing, modifying and synthesizing signals, such as sound, , potential fields, seismic signals, altimetry processing, and scientific measurements. Signal processing techniques are used to optimize transmissions, digital storage efficiency, correcting distorted signals, subjective video quality and to also detect or pinpoint components of interest in a measured signal. According to Alan V. Oppenheim and Ronald W.

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