On texture and image interpolation using Markov models
Image Communication
On the Approximation of Inner Products From Sampled Data
IEEE Transactions on Signal Processing
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The increasing amount of information transmitted over communication channels has to be handled efficiently to avoid congestion and delays in the network service. In this work, an algebraic approach to data coding and transmission is proposed. One of its basic assumptions is that in many situations the information could be decomposed into basic components or vectors, which represent a significant part of the data. To illustrate the capabilities of the proposed approach, a coding system based on vector quantization is investigated. This approach is based on the observation that in most systems, events of recent history of the stream can be used to represent future vectors of the data. Our conclusion is that the proposed algebraic approach could be efficient in presently used coding systems.