P. Kohn
Impact in
- Signal Processing top 2%
- Speech and Audio Processing
- Music and Audio Processing
- Blind Source Separation Techniques
- Artificial Intelligence top 5%
- Speech Recognition and Synthesis
- Neural Networks and Applications
- Natural Language Processing Techniques
Papers in
-
- Speech Recognition and Synthesis 5
- Neural Networks and Applications 4
- Natural Language Processing Techniques 1
-
- Speech and Audio Processing 5
- Blind Source Separation Techniques 4
- Co-authors
- Hynek Heřmanský (4 shared papers)Aruna Bayya (3 shared papers)N. Morgan (6 shared papers)Nelson Morgan (6 shared papers)James D. Beck (6 shared papers)Eric Allman (2 shared papers)Jeff Bilmes (2 shared papers)Chuck Wooters (3 shared papers)
- Journals
- Journal of Parallel and Distributed Computing (1 paper)UC Berkeley (1 paper)Neural Information Processing Systems (1 paper)
- Partner nations
- United States
In The Last Decade
P. Kohn
12 papers receiving 338 citations
Peers
Comparison fields: 5 of 36
- Signal Processing 316
- Artificial Intelligence 331
- Computer Vision and Pattern Recognition 56
- Hardware and Architecture 18
- Experimental and Cognitive Psychology 33
Countries citing papers authored by P. Kohn
This map shows the geographic impact of P. Kohn'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 P. Kohn with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites P. Kohn more than expected).
Fields of papers citing papers by P. Kohn
This network shows the impact of papers produced by P. Kohn. 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 P. Kohn. The network helps show where P. Kohn may publish in the future.
Co-authors
The 25 scholars most cited alongside P. Kohn, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 1992 | 175 | |
| 2 | 1991 | 95 | |
| 3 | 1992 | 47 | |
| 4 | 2002 | 25 | |
| 5 | 1991 | 20 | |
| 6 | 1993 | 18 | |
| 7 | 2002 | 9 | |
| 8 | 1991 | 5 | |
| 9 | Software for ANN training on a Ring Array Processor | 1991 | 4 |
| 10 | CNS-1 Architecture Specification | 1993 | 3 |
| 11 | 2003 | 1 | |
| 12 | 2003 | 1 |
About P. Kohn
P. Kohn is a scholar working on Artificial Intelligence, Signal Processing, Hardware and Architecture, Computational Theory and Mathematics and Computer Networks and Communications, having authored 12 papers that have together received 403 indexed citations. Recurring topics across this work include Speech and Audio Processing (5 papers), Speech Recognition and Synthesis (5 papers), Neural Networks and Applications (4 papers), Blind Source Separation Techniques (4 papers), Parallel Computing and Optimization Techniques (2 papers), Numerical Methods and Algorithms (2 papers), Natural Language Processing Techniques (1 paper) and Low-power high-performance VLSI design (1 paper). The work is most often cited by research in Signal Processing (316 citations), Artificial Intelligence (331 citations), Computer Vision and Pattern Recognition (56 citations), Hardware and Architecture (18 citations) and Experimental and Cognitive Psychology (33 citations). P. Kohn has collaborated with scholars based in United States. Frequent co-authors include Hynek Heřmanský, Aruna Bayya, N. Morgan, Nelson Morgan, James D. Beck, Eric Allman, Jeff Bilmes, Chuck Wooters, H. Bourlard and Hervé Bourlard. Their work appears in journals such as Journal of Parallel and Distributed Computing, UC Berkeley and Neural Information Processing Systems.
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.