G.D. Cain

659 citations
60 papers · 484 · h-index 11

Impact in

Papers in

G.D. Cain

48 papers receiving 440 citations

Peers

G.D. Cain
Comparison fields: 5 of 56
  • Signal Processing 313
  • Computational Mechanics 235
  • Computer Vision and Pattern Recognition 123
  • Statistical and Nonlinear Physics 68
  • Computational Theory and Mathematics 56
Replace A. Deczky with:
A. Deczky Canada
M. Kawamata Japan
Hans Wilhelm Schüßler Germany
Junghsi Lee Taiwan
Hussein Baher United States
B.A. Shenoi United States
Masahide Abe Japan
M.N.S. Swamy Canada
K. M. Tsui Hong Kong
H.H. Loomis United States
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Citations per field
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Citations per year

Countries citing papers authored by G.D. Cain

Since Specialization
Citations

This map shows the geographic impact of G.D. Cain'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 G.D. Cain with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites G.D. Cain more than expected).

Fields of papers citing papers by G.D. Cain

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by G.D. Cain. 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 G.D. Cain. The network helps show where G.D. Cain may publish in the future.

Co-authors

The 21 scholars most cited alongside G.D. Cain, 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 G.D. Cain Line = papers co-authored together G.D. Cain links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 60 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1992121
2 200246
3 200141
4 200229
5 200220
6 199616
7 198414
8 199114
9 199513
10 200213
11 200212
12 200510
13 199610
14 20029
15 19839
16 19728
17 19916
18 20026
19 19776
20 20016

About G.D. Cain

G.D. Cain is a scholar working on Signal Processing, Computational Mechanics, Computer Vision and Pattern Recognition, Electrical and Electronic Engineering and Biomedical Engineering, having authored 60 papers that have together received 484 indexed citations. Recurring topics across this work include Digital Filter Design and Implementation (33 papers), Advanced Adaptive Filtering Techniques (27 papers), Image and Signal Denoising Methods (17 papers), Analog and Mixed-Signal Circuit Design (11 papers), Model Reduction and Neural Networks (8 papers), Advancements in PLL and VCO Technologies (6 papers), Speech and Audio Processing (5 papers) and Blind Source Separation Techniques (4 papers). The work is most often cited by research in Signal Processing (313 citations), Computational Mechanics (235 citations), Computer Vision and Pattern Recognition (123 citations), Statistical and Nonlinear Physics (68 citations) and Computational Theory and Mathematics (56 citations). G.D. Cain has collaborated with scholars based in United Kingdom, Poland and Australia. Frequent co-authors include İzzet Kale, Andrzej Tarczynski, E. Hermanowicz, R.C.S. Morling, T.I. Laakso, G. Neri, T. Salmon, Giovanni Neri, T. Saramäki and Handong Sun. Their work appears in journals such as Electronics Letters, IEEE Transactions on Instrumentation and Measurement, IEEE Transactions on Signal Processing, IEEE Journal on Selected Areas in Communications and IEEE Signal Processing Magazine.

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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