Daniel T. Kaplan
Impact in
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- Chaos control and synchronization
- Signal Processing top 10%
- Blind Source Separation Techniques
Papers in
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- Chaos control and synchronization 6
- Quantum chaos and dynamical systems 1
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- Complex Systems and Time Series Analysis 5
- Co-authors
- Leon Glass (1 shared paper)Thomas Schreiber (2 shared papers)M. Eiselt (1 shared paper)M.I. Furman (1 shared paper)Steve Pincus (1 shared paper)Hal Caswell (1 shared paper)Mercedes Pascual (1 shared paper)Michael G. Neubert (1 shared paper)
- Journals
- Physica D Nonlinear Phenomena (3 papers)Chaos An Interdisciplinary Journal of Nonlinear Science (1 paper)Bulletin of the Atomic Scientists (1 paper)American Mathematical Monthly (2 papers)Journal of Electrocardiology (1 paper)
- Partner nations
- CanadaGermanyUnited States
In The Last Decade
Daniel T. Kaplan
10 papers receiving 349 citations
Peers
Comparison fields: 5 of 72
- Statistical and Nonlinear Physics 145
- Signal Processing 72
- Economics and Econometrics 136
- Cognitive Neuroscience 90
- Cardiology and Cardiovascular Medicine 106
Countries citing papers authored by Daniel T. Kaplan
This map shows the geographic impact of Daniel T. Kaplan'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 Daniel T. Kaplan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel T. Kaplan more than expected).
Fields of papers citing papers by Daniel T. Kaplan
This network shows the impact of papers produced by Daniel T. Kaplan. 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 Daniel T. Kaplan. The network helps show where Daniel T. Kaplan may publish in the future.
Co-authors
The 10 scholars most cited alongside Daniel T. Kaplan, 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 | 1994 | 125 | |
| 2 | 1993 | 96 | |
| 3 | 1996 | 63 | |
| 4 | 1996 | 33 | |
| 5 | 1998 | 19 | |
| 6 | 2002 | 12 | |
| 7 | 1996 | 12 | |
| 8 | 1991 | 5 | |
| 9 | Google's PageRank and Beyond: The Science of Search Engine Rankings by Amy N. Langville; Carl D. Meyer. | 2008 | 2 |
| 10 | 1983 | 2 | |
| 11 | Review of "Google's PageRank and Beyond: The Science of Search Engine Rankings'' | 2008 | 1 |
About Daniel T. Kaplan
Daniel T. Kaplan is a scholar working on Statistical and Nonlinear Physics, Economics and Econometrics, Cardiology and Cardiovascular Medicine, Signal Processing and Computer Networks and Communications, having authored 11 papers that have together received 370 indexed citations. Recurring topics across this work include Chaos control and synchronization (6 papers), Complex Systems and Time Series Analysis (5 papers), Genetic diversity and population structure (1 paper), Analog and Mixed-Signal Circuit Design (1 paper), Time Series Analysis and Forecasting (1 paper), Quantum chaos and dynamical systems (1 paper), Marine and coastal ecosystems (1 paper) and Neural Networks and Applications (1 paper). The work is most often cited by research in Statistical and Nonlinear Physics (145 citations), Signal Processing (72 citations), Economics and Econometrics (136 citations), Cognitive Neuroscience (90 citations) and Cardiology and Cardiovascular Medicine (106 citations). Daniel T. Kaplan has collaborated with scholars based in Canada, Germany and United States. Frequent co-authors include Leon Glass, Thomas Schreiber, M. Eiselt, M.I. Furman, Steve Pincus, Hal Caswell, Mercedes Pascual, Michael G. Neubert, Stephen P. Ellner and Timothy Sauer. Their work appears in journals such as Physica D Nonlinear Phenomena, Chaos An Interdisciplinary Journal of Nonlinear Science, Bulletin of the Atomic Scientists, American Mathematical Monthly and Journal of Electrocardiology.
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.