R. Venkataramani

1.1k citations
22 papers · 645 indexed · h-index 9

R. Venkataramani

22 papers receiving 615 citations

Peers

R. Venkataramani
Comparison fields: 5 of 48
  • Signal Processing 224
  • Computational Mechanics 287
  • Computer Vision and Pattern Recognition 204
  • Computer Networks and Communications 202
  • Applied Mathematics 71
Replace Sina Jafarpour with:
Sina Jafarpour United States
Andrzej Tarczynski United Kingdom
Mihailo Stojnic United States
Nguyen T. Thao United States
Yuan-Pei Lin Taiwan
K.M.M. Prabhu India
R. David Koilpillai India
See-May Phoong Taiwan
Guangwu Xu United States
W. Kozek Austria
R. Venkataramani relative to Sina Jafarpour United States Sina Jafarpour's profile →
Citations per field
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Citations per year

Countries citing papers authored by R. Venkataramani

Since Specialization
Citations

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

Fields of papers citing papers by R. Venkataramani

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by R. Venkataramani. 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 R. Venkataramani. The network helps show where R. Venkataramani may publish in the future.

Co-authorship network

The 18 scholars most cited alongside R. Venkataramani, 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 R. Venkataramani Line = papers co-authored together R. Venkataramani links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20207
2 20103
3 20084
4 20081
5 20071
6 20072
7 20061
8 20061
9 20062
10 20043
11 200382
12 200315
13 2003111
14 200331
15 20026
16 200225
17 20028
18 2001119
19
Sub -Nyquist Multicoset and MIMO Sampling: Perfect Reconstruction, Performance Analysis, and Necessary Density Conditions
20014
20 2000181

About R. Venkataramani

R. Venkataramani is a scholar working on Applied Mathematics, Signal Processing, Computer Networks and Communications, Computational Mechanics and Computational Theory and Mathematics, having authored 22 papers that have together received 645 indexed citations. Recurring topics across this work include Sparse and Compressive Sensing Techniques (7 papers), Advanced Wireless Communication Techniques (6 papers), Mathematical Analysis and Transform Methods (5 papers), Cellular Automata and Applications (5 papers), Blind Source Separation Techniques (5 papers), Image and Signal Denoising Methods (4 papers), Wireless Communication Security Techniques (3 papers) and Wireless Communication Networks Research (3 papers). The work is most often cited by research in Signal Processing (224 citations), Computational Mechanics (287 citations), Computer Vision and Pattern Recognition (204 citations), Computer Networks and Communications (202 citations) and Applied Mathematics (71 citations). R. Venkataramani has collaborated with scholars based in United States and Taiwan. Frequent co-authors include Yoram Bresler, Gerhard Kramer, Vivek K Goyal, Vahid Tarokh, M. Fatih Erden, Kan Li, A. Kavcic, Tim Rausch, J. W. Dykes and Edward C. Gage. Their work appears in journals such as IEEE Transactions on Information Theory, IEEE Transactions on Signal Processing, IEEE Transactions on Magnetics and 2006 IEEE International Conference on Communications.

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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