Avcibas, Memon, Sankur, Sayood's A Progressive Lossless Near-Lossless Image Compression PDF

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Even if matched structurally, the semantic variations on graphs were tremendous: operational semantics of the nodes, what edges represent, etc. An interesting innovation in this area was the attempt to move all non-determinism (in operations, timing) to the graph model hierarchy in the Stanford Intermediate Format (SIF) graph. In a SIF graph, loops and conditions were represented as separate graph bodies, where a body corresponded to each conditional invocation of a branch. Thus, operationally the uncertainty due to control flow (or synchronization operations) was captured as the uncertainty in calling a graph.

13, 277–292, 1994. 28 R. Gupta and F. Brewer 27. R. Walker and D. Thomas, Behavioral transformation for algorithmic level IC design, IEEE Trans. Comput. , 1115–1128, 1989. 28. Z. Iqbal, M. Potkonjak, S. Dey, and A. Parker, Critical path optimization using retiming and algebraic speed-up, Design Automation Conference, 1993. 29. S. , A tree-based scheduling algorithm for control dominated circuits, Design Automation Conference, 1993. 30. W. Wolf, A. -Y. Huang, R. Manno, and E. Wu, The Princeton University behavioral synthesis system, Design Automation Conference, 1992.

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A Progressive Lossless Near-Lossless Image Compression Algorithm by Avcibas, Memon, Sankur, Sayood


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