What is he best known for?
The fields of study he is best known for:
- Algorithm
- Statistics
- Mathematical analysis
The scientist’s investigation covers issues in Low-density parity-check code, Discrete mathematics, Algorithm, Decoding methods and Turbo code.
The concepts of his Low-density parity-check code study are interwoven with issues in Graph, Factor graph, Graph theory, Serial concatenated convolutional codes and Search algorithm.
His studies in Discrete mathematics integrate themes in fields like Tanner graph, Binary symmetric channel and Combinatorics.
His work in the fields of Algorithm, such as Iterative method, overlaps with other areas such as Quadratic equation.
His work on Sequential decoding and Belief propagation as part of his general Decoding methods study is frequently connected to Context, thereby bridging the divide between different branches of science.
His Turbo code research is multidisciplinary, incorporating elements of Linear code, Block code, Concatenated error correction code and Error detection and correction.
His most cited work include:
- On implementation of min-sum algorithm and its modifications for decoding low-density Parity-check (LDPC) codes (219 citations)
- On construction of rate-compatible low-density Parity-check codes (195 citations)
- Improved progressive-edge-growth (PEG) construction of irregular LDPC codes (164 citations)
What are the main themes of his work throughout his whole career to date?
Amir H. Banihashemi mostly deals with Low-density parity-check code, Algorithm, Decoding methods, Discrete mathematics and Theoretical computer science.
His biological study spans a wide range of topics, including Turbo code, Concatenated error correction code and Search algorithm.
His research in Algorithm intersects with topics in Communication channel, Bit error rate and Code.
He interconnects Computational complexity theory and Additive white Gaussian noise in the investigation of issues within Decoding methods.
His Discrete mathematics research includes elements of Degree, Combinatorics and Upper and lower bounds.
Amir H. Banihashemi combines subjects such as Algorithm design, Linear network coding and Puncturing with his study of Theoretical computer science.
He most often published in these fields:
- Low-density parity-check code (65.28%)
- Algorithm (53.70%)
- Decoding methods (36.57%)
What were the highlights of his more recent work (between 2015-2021)?
- Low-density parity-check code (65.28%)
- Discrete mathematics (30.09%)
- Bipartite graph (10.19%)
In recent papers he was focusing on the following fields of study:
His scientific interests lie mostly in Low-density parity-check code, Discrete mathematics, Bipartite graph, Error floor and Combinatorics.
To a larger extent, Amir H. Banihashemi studies Decoding methods with the aim of understanding Low-density parity-check code.
His Discrete mathematics research is multidisciplinary, incorporating perspectives in Expected value, Upper and lower bounds and Linear code.
The study incorporates disciplines such as Adjacency matrix, Computational complexity theory and Degree distribution in addition to Bipartite graph.
His research integrates issues of Expander code, Reed–Muller code, Block code, Hamming code and Turbo code in his study of Combinatorics.
His research in the fields of Compressed sensing overlaps with other disciplines such as Noise measurement.
Between 2015 and 2021, his most popular works were:
- New Characterization and Efficient Exhaustive Search Algorithm for Leafless Elementary Trapping Sets of Variable-Regular LDPC Codes (48 citations)
- Efficient Search of Girth-Optimal QC-LDPC Codes (44 citations)
- Symmetrical Constructions for Regular Girth-8 QC-LDPC Codes (32 citations)
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