S.S. Lawson

414 citations
43 papers · 307 indexed · h-index 9

Impact in

Papers in

S.S. Lawson

37 papers receiving 277 citations

Peers

S.S. Lawson
Comparison fields: 5 of 38
  • Signal Processing 239
  • Computer Vision and Pattern Recognition 127
  • Computational Mechanics 108
  • Computational Theory and Mathematics 39
  • Electrical and Electronic Engineering 117
Replace V. Krishnan with:
V. Krishnan United States
B. Nowrouzian Canada
D.J. Shpak Canada
Heinz G. Göckler Germany
Guozhu Long United States
D. Esteban United States
L. Gazsi Germany
Tim Hentschel Germany
G. Bonnerot France
K.K. Pang Australia
S.S. Lawson relative to V. Krishnan United States V. Krishnan's profile →
Citations per field
00.5×1.7×
V. Krishnan · 1×
Citations per year

Countries citing papers authored by S.S. Lawson

Since Specialization
Citations

This map shows the geographic impact of S.S. Lawson's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by S.S. Lawson with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites S.S. Lawson more than expected).

Fields of papers citing papers by S.S. Lawson

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by S.S. Lawson. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by S.S. Lawson. The network helps show where S.S. Lawson may publish in the future.

Co-authors

The 5 scholars most cited alongside S.S. Lawson, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with S.S. Lawson Line = papers co-authored together S.S. Lawson links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20240
2 20047
3 20021
4 20021
5 20022
6 20020
7 200233
8 200117
9 20010
10 19991
11 19992
12 19935
13 19922
14 199113
15
Application of bit-level systolic arrays to pipelined architectures for wave digital filters
19903
16
Design of 2-D PCAS digital filters based around restrictive and highly restrictive coefficient sets
19901
17
Design of wave digital filters with prescribed magnitude and phase requirements
19891
18 19892
19 19860
20 19811

About S.S. Lawson

S.S. Lawson is a scholar working on Signal Processing, Computational Mechanics, Computer Vision and Pattern Recognition, Computational Theory and Mathematics and Hardware and Architecture, having authored 43 papers that have together received 307 indexed citations. Recurring topics across this work include Digital Filter Design and Implementation (33 papers), Advanced Adaptive Filtering Techniques (15 papers), Advanced Data Compression Techniques (10 papers), Numerical Methods and Algorithms (9 papers), Image and Signal Denoising Methods (8 papers), Analog and Mixed-Signal Circuit Design (8 papers), Photonic and Optical Devices (4 papers) and Embedded Systems Design Techniques (3 papers). The work is most often cited by research in Signal Processing (239 citations), Computer Vision and Pattern Recognition (127 citations), Computational Mechanics (108 citations), Computational Theory and Mathematics (39 citations) and Electrical and Electronic Engineering (117 citations). S.S. Lawson has collaborated with scholars based in United Kingdom, Australia and Canada. Frequent co-authors include Saturnino Maldonado-Bascón, Fernando Cruz–Roldán, S. Summerfield, Diane Donovan and James Lefevre. Their work appears in journals such as Electronics Letters, Electronics & Communications Engineering Journal, IEEE Signal Processing Letters, IEEE Circuits and Devices Magazine and PLoS ONE.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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