What is he best known for?
The fields of study he is best known for:
- Algorithm
- Statistics
- Programming language
His main research concerns Algorithm, Decoding methods, Communication channel, Low-density parity-check code and Theoretical computer science.
The Algorithm study combines topics in areas such as Encoder and Code.
Paul H. Siegel combines subjects such as Message passing, Parity bit, Linear programming, Coset and Redundancy with his study of Decoding methods.
His Communication channel research is multidisciplinary, incorporating elements of Noise, Coding and Detector.
His Low-density parity-check code research is multidisciplinary, relying on both Sequential decoding and Channel capacity.
He focuses mostly in the field of Turbo code, narrowing it down to topics relating to Linear code and, in certain cases, Discrete mathematics.
His most cited work include:
- Characterizing flash memory: anomalies, observations, and applications (395 citations)
- Performance analysis and code optimization of low density parity-check codes on Rayleigh fading channels (339 citations)
- Capacity-approaching bandwidth-efficient coded modulation schemes based on low-density parity-check codes (270 citations)
What are the main themes of his work throughout his whole career to date?
His scientific interests lie mostly in Algorithm, Decoding methods, Communication channel, Discrete mathematics and Low-density parity-check code.
His Algorithm research includes themes of Theoretical computer science, Coding and Code.
His Decoding methods course of study focuses on Erasure and Erasure code.
His Communication channel research incorporates themes from Viterbi algorithm and Detector.
His studies deal with areas such as Upper and lower bounds, Hamming code and Combinatorics as well as Discrete mathematics.
His Concatenated error correction code research includes elements of Additive white Gaussian noise and Linear code.
He most often published in these fields:
- Algorithm (58.66%)
- Decoding methods (31.27%)
- Communication channel (25.32%)
What were the highlights of his more recent work (between 2014-2021)?
- Algorithm (58.66%)
- Decoding methods (31.27%)
- Communication channel (25.32%)
In recent papers he was focusing on the following fields of study:
Algorithm, Decoding methods, Communication channel, Coding and Code are his primary areas of study.
His Algorithm study combines topics from a wide range of disciplines, such as Detector, Bit error rate, Upper and lower bounds, Flash memory and Computer data storage.
His Decoding methods study combines topics in areas such as NAND gate, Type, Binary number and Erasure.
Paul H. Siegel studies Channel capacity which is a part of Communication channel.
His research in Code intersects with topics in Discrete mathematics, Code rate and Set.
His research investigates the connection with Low-density parity-check code and areas like Sequential decoding which intersect with concerns in Concatenated error correction code.
Between 2014 and 2021, his most popular works were:
- Binary Linear Locally Repairable Codes (47 citations)
- Cyclic linear binary locally repairable codes (43 citations)
- Linear locally repairable codes with availability (42 citations)
In his most recent research, the most cited papers focused on:
- Algorithm
- Programming language
- Statistics
Paul H. Siegel focuses on Algorithm, Discrete mathematics, Decoding methods, Code and Linear code.
Paul H. Siegel does research in Algorithm, focusing on Trellis specifically.
His Decoding methods study incorporates themes from Kernel, Time complexity, Type, Data loss and Binary number.
His research integrates issues of Upper and lower bounds, Computer hardware, Random walk and Encoding in his study of Code.
His work in Linear code addresses issues such as Hamming code, which are connected to fields such as Cyclic code.
His Low-density parity-check code study integrates concerns from other disciplines, such as Serial concatenated convolutional codes and Theoretical computer science.
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