Abstract
Linear prediction has been extensively researched and a significant number of techniques have been proposed to enhance its effectiveness, among them switching linear predictors. In this paper, we propose a general framework for designing a family of adaptive switching linear predictors. In addition, we will utilize the proposed framework to construct a concrete implementation based on set partitions and relational operators. © Springer-Verlag Berlin Heidelberg 2005.
Cite
CITATION STYLE
Itani, A., & Das, M. (2005). Adaptive switching linear predictor for lossless image compression. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3804 LNCS, pp. 718–722). https://doi.org/10.1007/11595755_91
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