J.A. Bucklew

75 papers receiving 2.2k citations

Peers

J.A. Bucklew
Comparison fields: 5 of 119
  • Statistics and Probability 335
  • Management Science and Operations Research 479
  • Signal Processing 361
  • Computer Networks and Communications 594
  • Computer Vision and Pattern Recognition 462
Replace Pierre Priouret with:
Pierre Priouret France
Reiner Horst Germany
Michel Métivier France
Jean‐Baptiste Hiriart‐Urruty France
Bruce Hajek United States
Robert E. Odeh Canada
H. S. Witsenhausen United States
Reha Tütüncü United States
Adrian S. Lewis United States
J. Frédéric Bonnans France
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Citations per year

Countries citing papers authored by J.A. Bucklew

Since Specialization
Citations

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

Fields of papers citing papers by J.A. Bucklew

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 23 scholars most cited alongside J.A. Bucklew, 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 J.A. Bucklew Line = papers co-authored together J.A. Bucklew links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 80 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Large Deviation Techniques in Decision, Simulation, and Estimation
1990397
2 2004312
3 2000248
4 1990172
5 1982137
6 200585
7 199083
8 199373
9 199268
10 200161
11 200659
12 200838
13 198137
14 201235
15 197931
16 199630
17 198428
18 198024
19 197923
20 198822

About J.A. Bucklew

J.A. Bucklew is a scholar working on Signal Processing, Artificial Intelligence, Computer Vision and Pattern Recognition, Computer Networks and Communications and Computational Mechanics, having authored 80 papers that have together received 2.4k indexed citations. Recurring topics across this work include Advanced Data Compression Techniques (16 papers), Blind Source Separation Techniques (13 papers), Image and Signal Denoising Methods (12 papers), Advanced Adaptive Filtering Techniques (11 papers), Digital Filter Design and Implementation (10 papers), Distributed Sensor Networks and Detection Algorithms (10 papers), Statistical Methods and Inference (9 papers) and Bayesian Methods and Mixture Models (8 papers). The work is most often cited by research in Statistics and Probability (335 citations), Management Science and Operations Research (479 citations), Signal Processing (361 citations), Computer Networks and Communications (594 citations) and Computer Vision and Pattern Recognition (462 citations). J.A. Bucklew has collaborated with scholars based in United States, Kuwait and Germany. Frequent co-authors include D.J. Sebald, J.S. Sadowsky, Neal C. Gallagher, William A. Sethares, G.L. Wise, Michael Rabbat, Giovanni Parmigiani, Peter Ney, Robert D. Nowak and Thomas G. Kurtz. Their work appears in journals such as IEEE Transactions on Information Theory, IEEE Transactions on Signal Processing, IEEE Transactions on Communications, Journal of the Optical Society of America A and Journal of Applied Probability.

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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