What is he best known for?
The fields of study he is best known for:
- Quantum mechanics
- Statistics
- Algorithm
Shu Lin mostly deals with Block code, Algorithm, Linear code, Concatenated error correction code and Discrete mathematics.
Shu Lin interconnects Convolutional code and Probability theory in the investigation of issues within Block code.
His Algorithm study combines topics in areas such as Theoretical computer science and Hybrid automatic repeat request.
His study on Space–time trellis code is often connected to Parity as part of broader study in Linear code.
His Concatenated error correction code research integrates issues from Low-density parity-check code and Turbo code.
His Discrete mathematics study integrates concerns from other disciplines, such as Combinatorics, Reed–Solomon error correction, Expander code, Luby transform code and Reed–Muller code.
His most cited work include:
- Error control coding : fundamentals and applications (3769 citations)
- Error Control Coding (1674 citations)
- Low-density parity-check codes based on finite geometries: a rediscovery and new results (1241 citations)
What are the main themes of his work throughout his whole career to date?
His primary areas of study are Algorithm, Block code, Low-density parity-check code, Linear code and Concatenated error correction code.
His research links Theoretical computer science with Algorithm.
His Block code research incorporates elements of Discrete mathematics and BCH code.
His study explores the link between Low-density parity-check code and topics such as Cyclic code that cross with problems in Polynomial code.
His work is dedicated to discovering how Linear code, Convolutional code are connected with Trellis and other disciplines.
His Concatenated error correction code study incorporates themes from Forward error correction, Turbo code and Concatenation.
He most often published in these fields:
- Algorithm (37.64%)
- Block code (36.11%)
- Low-density parity-check code (35.67%)
What were the highlights of his more recent work (between 2016-2021)?
- Low-density parity-check code (35.67%)
- Algorithm (37.64%)
- Decoding methods (27.13%)
In recent papers he was focusing on the following fields of study:
His scientific interests lie mostly in Low-density parity-check code, Algorithm, Decoding methods, Magnetic field and Discrete mathematics.
His Low-density parity-check code research includes elements of Girth, Concatenated error correction code, Reed–Solomon error correction and Parity bit.
The study incorporates disciplines such as Forward error correction, Turbo code and Linear code in addition to Concatenated error correction code.
Linear code is a subfield of Block code that Shu Lin explores.
Shu Lin works in the field of Algorithm, focusing on Error detection and correction in particular.
As part of one scientific family, Shu Lin deals mainly with the area of Decoding methods, narrowing it down to issues related to the Coding, and often Binary number and Fourier transform.
Between 2016 and 2021, his most popular works were:
- Design of LDPC Codes: A Survey and New Results (90 citations)
- Two-Level Hierarchical Model-Based Predictive Control for Large-Scale Urban Traffic Networks (46 citations)
- Mass correction to chiral vortical effect and chiral separation effect (29 citations)
In his most recent research, the most cited papers focused on:
- Quantum mechanics
- Statistics
- Computer network
His primary areas of investigation include Low-density parity-check code, Discrete mathematics, Magnetic field, Quantum electrodynamics and Reed–Solomon error correction.
Low-density parity-check code is a primary field of his research addressed under Algorithm.
His Discrete mathematics research includes themes of Algebraic method, Algebraic number, Superposition principle, Unification and Information theory.
The Magnetic field study combines topics in areas such as Condensed matter physics, Electrical resistivity and conductivity, Conductivity and Electric field.
His Reed–Solomon error correction research incorporates themes from Girth, Structure, Sparse matrix and Erasure.
His study on Block code is mostly dedicated to connecting different topics, such as Turbo code.
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