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Record W2147622371 · doi:10.1109/isit.1993.748412

Inverterless Cauchy Cells for a Systolic Reed-Solomon Encoder

2005· article· en· W2147622371 on OpenAlexaff
M.A. Hasan, V.K. Bhargava

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicCoding theory and cryptography
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsEncoderFinite fieldArithmeticParallel computingComputer scienceDiscrete mathematicsMathematicsAlgorithm

Abstract

fetched live from OpenAlex

Summary Consider an (n, k) Reed-Solomon (RS) code of length n = q - 1 and redundancy r = n - IC over the finite field GF(q). The usual implementation of the RS encoder consists of an T stage feedback shift register [1]. In some very high speed applications, the presence of the accompanying global feedback path restricts the speed of the encoder. Recently, Seroussi has proposed an architecture for the RS encoder [a]. Unlike the usual implementation of the RS encoder, Seroussi’s architecture does not require any global feedback path. Furthermore, the architecture is of systolic type and has modular a structure- it consists of one pre-processing cell and T Cauchy cells [2]. This modularity feature of the encoder makes it suitable for hardware implementation. The circuit complexity of Seroussi’s RS encoder depends essentially on the Cauchy cells. Each Cauchy cell computes one parity symbol for the RS code and contains one parallel type divider for the finite field GF(q). Unfortunately, the realization of a divider is much more complicated than that of a multiplier 131. Let M denote the circuit complexity of a parallel type multiplier of GF(q), where q = pm, p is prime and m is a nonzero positive integer. Then the circuit complexity of a modular parallel divider is, in general, O(mM) and that of Seroussi’s RS encoder is O(rmM). In this paper, we extent Seroussi’s work. It is shown here that the Cauchy cell can be implemented without any divider. The proposed Cauchy cell also has a shorter logic path and yields an RS encoder which has a circuit complexity O(rM).

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.920
Threshold uncertainty score0.413

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.011
GPT teacher head0.224
Teacher spread0.213 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreMethods

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2005
Admission routes1
Has abstractyes

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