Universal distributed sensing via random projections
Proceedings of the 5th international conference on Information processing in sensor networks
High-rate quantization and transform coding with side information at the decoder
Signal Processing - Special section: Distributed source coding
Layered Wyner-Ziv video coding for transmission over unreliable channels
Signal Processing - Special section: Distributed source coding
Distributed coding of highly correlated image sequences with motion-compensated temporal wavelets
EURASIP Journal on Applied Signal Processing
Distortion-rate bounds for distributed estimation using wireless sensor networks
EURASIP Journal on Advances in Signal Processing
Rate-constrained collaborative noise reduction for wireless hearing aids
IEEE Transactions on Signal Processing
IEEE Transactions on Information Theory
IEEE Transactions on Information Theory
ISIT'09 Proceedings of the 2009 IEEE international conference on Symposium on Information Theory - Volume 1
Decomposable principal component analysis
IEEE Transactions on Signal Processing
Distributed compression for MIMO coordinated networks with a backhaul constraint
IEEE Transactions on Wireless Communications
Compress-and-forward cooperative MIMO relaying with full channel state information
IEEE Transactions on Signal Processing
Information Sciences: an International Journal
IEEE Transactions on Signal Processing
Transform-based distributed data gathering
IEEE Transactions on Signal Processing
Recursive implementation of the distributed Karhunen-Loève transform
IEEE Transactions on Signal Processing
Practical data compression in wireless sensor networks: A survey
Journal of Network and Computer Applications
Distributed Video Coding: an overview of basics, research issues and solutions
International Journal of Ad Hoc and Ubiquitous Computing
Distributed static linear Gaussian models using consensus
Neural Networks
Compression in wireless sensor networks: A survey and comparative evaluation
ACM Transactions on Sensor Networks (TOSN)
Low-complexity 8-point DCT approximations based on integer functions
Signal Processing
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The Karhunen-Loeve transform (KLT) is a key element of many signal processing and communication tasks. Many recent applications involve distributed signal processing, where it is not generally possible to apply the KLT to the entire signal; rather, the KLT must be approximated in a distributed fashion. This paper investigates such distributed approaches to the KLT, where several distributed terminals observe disjoint subsets of a random vector. We introduce several versions of the distributed KLT. First, a local KLT is introduced, which is the optimal solution for a given terminal, assuming all else is fixed. This local KLT is different and in general improves upon the marginal KLT which simply ignores other terminals. Both optimal approximation and compression using this local KLT are derived. Two important special cases are studied in detail, namely, the partial observation KLT which has access to a subset of variables, but aims at reconstructing them all, and the conditional KLT which has access to side information at the decoder. We focus on the jointly Gaussian case, with known correlation structure, and on approximation and compression problems. Then, the distributed KLT is addressed by considering local KLTs in turn at the various terminals, leading to an iterative algorithm which is locally convergent, sometimes reaching a global optimum, depending on the overall correlation structure. For compression, it is shown that the classical distributed source coding techniques admit a natural transform coding interpretation, the transform being the distributed KLT. Examples throughout illustrate the performance of the proposed distributed KLT. This distributed transform has potential applications in sensor networks, distributed image databases, hyper-spectral imagery, and data fusion