J.A. Bucklew

75 papers receiving 2.2k citations

Peers

J.A. Bucklew
Comparison fields: 5 of 121
  • Statistics and Probability 335
  • Management Science and Operations Research 477
  • Signal Processing 360
  • Computer Networks and Communications 594
  • Computer Vision and Pattern Recognition 458
Replace Pierre Priouret with:
Pierre Priouret France
Reiner Horst Germany
Jean‐Baptiste Hiriart‐Urruty France
G. George Yin United States
Robert E. Odeh Canada
H. S. Witsenhausen United States
Adrian S. Lewis United States
Reha Tütüncü United States
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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-authorship network

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
#Work
1 20146
2 20141
3 201234
4 20075
5 2004309
6 200318
7 200161
8 19945
9 19949
10 199268
11 199014
12 19896
13 198920
14 198822
15 19883
16 19871
17 198313
18 19830
19 198137
20 197920

About J.A. Bucklew

J.A. Bucklew is a scholar working on Signal Processing, Statistics and Probability, Computer Vision and Pattern Recognition, Artificial Intelligence and Computer Networks and Communications, 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 (477 citations), Signal Processing (360 citations), Computer Networks and Communications (594 citations) and Computer Vision and Pattern Recognition (458 citations). J.A. Bucklew has collaborated with scholars based in United States, Kuwait and Australia. 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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