What is he best known for?
The fields of study he is best known for:
- Algorithm
- Statistics
- Artificial intelligence
David Declercq spends much of his time researching Algorithm, Decoding methods, Low-density parity-check code, Error detection and correction and Theoretical computer science.
In general Algorithm study, his work on Error floor, BCJR algorithm and Code word often relates to the realm of Node, thereby connecting several areas of interest.
Stability criterion, Graph and Linear programming is closely connected to Communication channel in his research, which is encompassed under the umbrella topic of Decoding methods.
The various areas that David Declercq examines in his Low-density parity-check code study include Discrete mathematics, Belief propagation, Binary number and Concatenated error correction code.
His Concatenated error correction code research focuses on Turbo code and how it relates to Serial concatenated convolutional codes and Block code.
The concepts of his Error detection and correction study are interwoven with issues in Computational complexity theory and Binary code.
His most cited work include:
- Decoding Algorithms for Nonbinary LDPC Codes Over GF $(q)$ (634 citations)
- Design of regular (2,d/sub c/)-LDPC codes over GF(q) using their binary images (275 citations)
- Low-complexity decoding for non-binary LDPC codes in high order fields (160 citations)
What are the main themes of his work throughout his whole career to date?
His primary scientific interests are in Low-density parity-check code, Algorithm, Decoding methods, Theoretical computer science and Concatenated error correction code.
David Declercq has researched Low-density parity-check code in several fields, including Discrete mathematics, Block code, Binary number, Turbo code and Serial concatenated convolutional codes.
His studies deal with areas such as Tanner graph and Combinatorics as well as Discrete mathematics.
His Algorithm research is multidisciplinary, incorporating perspectives in Communication channel and Code.
His Decoding methods study typically links adjacent topics like Error detection and correction.
The concepts of his Concatenated error correction code study are interwoven with issues in Forward error correction and Linear code.
He most often published in these fields:
- Low-density parity-check code (66.53%)
- Algorithm (60.16%)
- Decoding methods (58.96%)
What were the highlights of his more recent work (between 2016-2021)?
- Decoding methods (58.96%)
- Low-density parity-check code (66.53%)
- Algorithm (60.16%)
In recent papers he was focusing on the following fields of study:
His main research concerns Decoding methods, Low-density parity-check code, Algorithm, Error detection and correction and Probabilistic logic.
His work on Soft-decision decoder and Tanner graph as part of general Decoding methods study is frequently linked to Alphabet, bridging the gap between disciplines.
The study incorporates disciplines such as Computation and Computer engineering in addition to Low-density parity-check code.
His Algorithm research integrates issues from Metric and Code.
His research in Error detection and correction intersects with topics in List decoding and Computer hardware.
His Probabilistic logic study combines topics in areas such as Frame, Computer network and Statistical model.
Between 2016 and 2021, his most popular works were:
- Dynamic-SCFlip Decoding of Polar Codes (51 citations)
- Analysis and Design of Cost-Effective, High-Throughput LDPC Decoders (23 citations)
- 3D facial expression recognition using kernel methods on Riemannian manifold (21 citations)
In his most recent research, the most cited papers focused on:
- Statistics
- Algorithm
- Artificial intelligence
David Declercq mostly deals with Decoding methods, Algorithm, Low-density parity-check code, Error detection and correction and Throughput.
His work deals with themes such as Computer hardware and Parallel computing, which intersect with Decoding methods.
His Parallel computing research includes themes of Field-programmable gate array, Surjective function and Soft-decision decoder.
David Declercq integrates several fields in his works, including Algorithm and Node.
He undertakes multidisciplinary studies into Low-density parity-check code and Hardware architecture in his work.
His studies in Error detection and correction integrate themes in fields like Forward error correction, Probabilistic logic, List decoding and Computer engineering.
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