T.J. Moir

83 papers receiving 588 citations

Peers

T.J. Moir
Comparison fields: 5 of 84
  • Signal Processing 325
  • Developmental Biology 30
  • Computational Mechanics 167
  • Control and Systems Engineering 123
  • Artificial Intelligence 166
Replace T.V. Sreenivas with:
T.V. Sreenivas India
Yuma Koizumi Japan
José A. Apolinário Brazil
Ben Milner United Kingdom
Makoto Kumon Japan
M.R. Portnoff United States
Shuo-Yiin Chang United States
Athanasios Mouchtaris Greece
Marco Crocco Italy
T.J. Moir relative to T.V. Sreenivas India T.V. Sreenivas's profile →
Citations per field
00.5×
T.V. Sreenivas · 1×
Citations per year

Countries citing papers authored by T.J. Moir

Since Specialization
Citations

This map shows the geographic impact of T.J. Moir'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 T.J. Moir with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites T.J. Moir more than expected).

Fields of papers citing papers by T.J. Moir

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by T.J. Moir. 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 T.J. Moir. The network helps show where T.J. Moir may publish in the future.

Co-authors

The 13 scholars most cited alongside T.J. Moir, 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 T.J. Moir Line = papers co-authored together T.J. Moir links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 90 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201673
2 198448
3 201848
4 201735
5 198627
6 201522
7 201521
8 198618
9 200316
10 201815
11 199514
12 201513
13 200213
14 200113
15 200812
16 201512
17 201012
18 201410
19 19869
20 19879

About T.J. Moir

T.J. Moir is a scholar working on Signal Processing, Computational Mechanics, Control and Systems Engineering, Artificial Intelligence and Electrical and Electronic Engineering, having authored 90 papers that have together received 626 indexed citations. Recurring topics across this work include Speech and Audio Processing (48 papers), Advanced Adaptive Filtering Techniques (44 papers), Blind Source Separation Techniques (27 papers), Music and Audio Processing (16 papers), Control Systems and Identification (11 papers), Acoustic Wave Phenomena Research (7 papers), Advanced Control Systems Optimization (5 papers) and Advancements in PLL and VCO Technologies (5 papers). The work is most often cited by research in Signal Processing (325 citations), Developmental Biology (30 citations), Computational Mechanics (167 citations), Control and Systems Engineering (123 citations) and Artificial Intelligence (166 citations). T.J. Moir has collaborated with scholars based in New Zealand, United Kingdom and United States. Frequent co-authors include Roneel V. Sharan, M.J. Grimble, J. F. Barrett, Guido Lemos de Souza Filho, Gwo-Jia Jong, Mahsa Mohaghegh, Abdolhossein Sarrafzadeh, Te‐Jen Su, Jaehoon Jeong and Andrew J. Anderson. Their work appears in journals such as Electronics Letters, International Journal of Control, International Journal of Adaptive Control and Signal Processing, Neurocomputing and IEEE Transactions on Industrial Electronics.

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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