Bell, T. C. (1986) Better OPM/L text compression. IEEE Trans. Commun., COM-34, 1176--1182. Home/Search Document Not in Database Summary Related Articles Check |
This paper is cited in the following contexts:
Data Compression Using a Sort-Based Context Similarity Measure - Yokoo (1997) (Correct)
....for i = 1 in the data string has a unique previous context as the MSC to its context Cont x (i ) In our sample implementation we use a binary search tree to store context symbol pairs in M # order of contexts. This is quite similar to the method for storing strings in lexicographic order [14], which was proposed as an implementation of the Ziv Lempel data compression method. As is easily seen, symmetric order (or in order) in the tree corresponds to the M # order of contexts. We link the nodes in the tree by a doubly linked list in symmetric order. Two pointers which follow the ....
....e.g. 17] on the other hand, searches the already processed text x[1 . 9] for the longest match with the incoming string. In this case, the longest match x[10 . 14] is coded by the pointer pair of the previous position 7 and the match length 5 (see Figure 5) In some other versions, e.g. [14], the match position is better represented as the offset, or the relative displacement, which indicates how far back to look into the text to find the longest match. In addition, the offset may be encoded by a sophisticated code, e.g. a Huffman code, in order to represent more frequent offsets in ....
Bell, T. C. (1986) Better OPM/L text compression. IEEE Trans. Commun., COM-34, 1176--1182.
Efficient Optimal Recompression - Klein (1997) (Correct)
....One of the problems of LZ77 is how to locate previous occurrences of substrings in the text. The simple method of scanning the whole text backwards for each processed character might be prohibitively slow. Many alternatives have been suggested, including, among others, the use of binary trees [5], hashing [6, 7] and Patricia trees [8] The question of how to parse the original text into a sequence of substrings is a problem common to all dictionarybased compression techniques. An optimal technique for a static dictionary is mentioned in [9] Storer and Szymanski [10] give an optimal ....
....window of fixed size preceding the current location. A simple recompression heuristic is therefore to increase N , which increases the probability of finding a good earlier match. However, the compression performance is not necessarily improved, since #log 2 N# bits are used to encode d. In [5, 8, 16], the previous occurrences of the current substring are searched for by means of hashing: the current two (or three) characters are hashed to a location in a hash table, which contains a pointer to the previous occurrence of a couple (or triplet) of characters that hashed to the same location. ....
Bell, T. C. (1986) Better OPM/L text compression. IEEE Trans. Commun., COM-34, 1176--1182.
A VLSI Systolic Array Architecture for Lempel-Ziv-Based.. - Bongjin Jung Wayne (1994) (1 citation) (Correct)
....table entries replacing the oldest entries among the table. This can be done simply by left shifting symbols in the encoding buffer by C l 1. Figure 1 shows the compression procedure of the Lempel Ziv algorithm. Several modifications have been made to further improve the compression performance [2][8] 3. A PARALLEL LZ ALGORITHM A straightforward sequential implementation of LempelZiv data compression takes O(N M ) time to process a string of M symbols. As the amount of data to be communicated has exploded in the past few years, a sequential implementation quickly becomes inadequate to ....
T. Bell, "Better OPM/L Text Compression," IEEE Trans. Communication COM-34, 12 pp. 1176-1182, December 1986.
A Guaranteed Compression Scheme for Repetitive DNA Sequences - Rivals (1996) (3 citations) (Correct)
....not manage to compress the sequence. It could then output the original sequence preceded with a additional bit to announce this special case. Not all encoding schemes allows that, Cfact does not. Selected compression schemes. The compressors in competition are: Cfact ; LZSS, a LZ77 scheme from [Bel86]; LZW15, a LZWelch scheme with 15 bits dictionary index (cf. Wel84] Arith1 and Arith2, two arithmetic encoders used with finite context models of order 1 and 2. All but Cfact are adapted from [Nel91] We contacted the authors of [GT93] to compare with their algorithm, but it is no more ....
Thimoty C. Bell. Better OPM/L text compression. IEEE Trans. Communications, COM34 (12):1176--1182, December 1986.
Improvements of Speed and Performance of Data Compression Based.. - Sadakane (1997) (Correct)
....x (i) Cont x (k) Either Cont x (j) or Cont x (k) is the MSC. We define MSC x (i) as Cont x (j) if Sim x (i; j) Sim x (i; k) and as Cont x (k) if Sim x (i; j) Sim x (i; k) The lexicographically next and previous contexts of a context can be easily calculated by traversing the binary tree [3], but these operations are used frequently, therefore two additional pointers, next and prev, are used in the binary tree. All contexts are inserted in doubly linked list in lexicographical order by using next and prev. Inserting a context in the binary tree and the doubly linked list is constant ....
T. C. Bell. Better OPM/L text compression. IEEE Trans. on Commun., COM-34(12):1176--1182, December 1986.
Efficient Optimal Recompression - Klein (1996) (Correct)
No context found.
Bell T.C. (1986), Better OPM/L text compression, IEEE Trans. on Communications COM--34 1176-- 1182.
The Effects of Cascading Popular Text Compression Techniques - Semon (1993) (Correct)
No context found.
Bell, T.C., "Better OPM/L text compression," IEEE Trans. Comm., COM-34, 12, pp.1176-1182, Dec. 1986.
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