Data compression is a term that refers to the reduction of data representation requirements either in storage and/or in transmission. A commonly used algorithm for compression is the Lempel-Ziv-Welch (LZW) method proposed by Terry A. Welch[l]. LZW is an adaptive, dictionary based, lossless algorithm. This provides for a general compression mechanism that is applicable to a broad range of inputs. Furthermore, the lossless nature of LZW implies that it is a reversible process which results in the original file/message being fully recoverable from compression. A variant of this algorithm is currently the foundation of the UNIX "compress" program. Additionally, LZW is one of the compression schemes defined in the TIFF standard, as well as in the CCITT V.42bis standard. One of the challenges in designing an efficient compression mechanism, such as LZW, which can be used in real time applications, is the speed of the search into the data dictionary. In this paper an Associative Processing implementation of the LZW algorithm is presented. This approach provides an efficient solution to this requirement. Additionally, it is shown that Associative Processing (ASP) allows for rapid and elegant development of the LZW algorithm that will generally outperform standard approaches in complexity, readability, and performance.
Library of Congress Subject Headings
Data compression (Computer science)
Department, Program, or Center
Computer Engineering (KGCOE)
Narang, Manish, "Lempel Ziv Welch data compression using associative processing as an enabling technology for real time application" (1998). Thesis. Rochester Institute of Technology. Accessed from
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