Bell Communications Research, Inc.

Victor K Wei

Ramarathnam R Venkatesan

Jawad A Salehi

Sivaramakrishnan Rajagopalan

Fan R Chung

Mary G O'Connor

Martin Kerner

Dennis N Grinberg

Methodology and concomitant circuitry for compacting an incoming data stream into an outgoing compacted data stream utilize a plurality of memories or lists. The incoming data stream is partitioned into a sequence of tokens. A primary memory stores each token, with the most recently appearing token occupying the top rank in the list. A secondary memory stores the location in the primary memory of each of a subset of tokens. The compacted data stream is generated as a coded representation of the token itself, the position of the token in the primary memory, or the position in secondary memory of the location of the token in primary memory. A tertiary list may also be employed to generate a coded representation of the position in the tertiary list of the secondary list. Searching of the lists is effected with a hashing function. Updating of the lists utilizes tree splaying.

Data compression

Methodology and concomitant circuitry for compacting an incoming data stream into an outgoing compacted data stream utilize a multiple, doubly-linked list and an associated class promotion data structure. The incoming data stream is partitioned into a sequence of symbols. A memory associated with the data structure stores each symbol, information regarding the recency rank of each symbol as it arrives in sequence as well as class information and pointer information for each symbol. For each symbol, the memory is checked to determine if the symbol is new or repeated. If the symbol is repeated, only the recency rank is used to form that part of the outgoing data stream associated with the new symbol. If the symbol is new, identification information is added to the symbol and both the identification information are emitted as part of the compacted stream. Memory update operations are then effected to change class, recency rank and pointer information. The decoding methodology and circuitry performs the inverse to the compacting operations using the class promotion data structure.

Methodology, and associated circuitry, for encoding and decoding signals utilize optimizing orthogonal code techniques that effect autonomy of communications and simplified signal processing, thereby improving reliability. Encoder (121) processes an incoming data stream by associating an optimizing orthogonal code with each binary one in the input stream and then by transmitting a series of rate-increased pulses over a path during intervals determined by the code for each of the binary ones. Decoder (131) is generally arranged as a correlation detector in that the decoder only responds to the particular optimizing orthogonal code for which it is configured. Sensors in energy transfer relation to the path are positioned at detection points on the path in correspondence to an assigned code. The outputs of the sensors are processed to produce a rate-decreased detected signal at the rate of the input stream whenever a rate-increased stream corresponding to the decoder configuration is propagating along the path.

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Morristown, NJ, United States of America

Victor K Wei