M. Morf

6.4k citations
134 papers · 4.3k indexed · h-index 31

M. Morf

121 papers receiving 3.8k citations

Peers

M. Morf
Comparison fields: 5 of 134
  • Signal Processing 1.5k
  • Computational Mathematics 47
  • Computational Theory and Mathematics 1.0k
  • Computational Mechanics 1.1k
  • Control and Systems Engineering 1.2k
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E.I. Jury United States
N.K. Bose United States
James R. Bunch United States
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Citations per field
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Citations per year

Countries citing papers authored by M. Morf

Since Specialization
Citations

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

Fields of papers citing papers by M. Morf

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

The 25 scholars most cited alongside M. Morf, 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 M. Morf Line = papers co-authored together M. Morf links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20184
2 200514
3 20021
4 20004
5 19853
6 19843
7 19847
8 19832
9 198196
10 1979297
11 1979149
12 197975
13
Tutorial Survey of Algorithms for Locating and Identifying Spatially Distributed Sources and Receivers,
19781
14
Fast Algorithms for Speech Modeling.
197821
15 197875
16
New Results in 2-D Systems Theory. Part III. Recursive Realization and Estimation Algorithms for 2-D Systems.
19774
17
Recent Results in Least-Squares Estimation Theory
19771
18 19774
19 19765
20 19729

About M. Morf

M. Morf is a scholar working on Signal Processing, Computational Theory and Mathematics, Computational Mathematics, General Psychology and Control and Systems Engineering, having authored 134 papers that have together received 4.3k indexed citations. Recurring topics across this work include Control Systems and Identification (24 papers), Matrix Theory and Algorithms (17 papers), Advanced Adaptive Filtering Techniques (17 papers), Target Tracking and Data Fusion in Sensor Networks (17 papers), Numerical Methods and Algorithms (15 papers), Blind Source Separation Techniques (14 papers), Direction-of-Arrival Estimation Techniques (11 papers) and Image and Signal Denoising Methods (10 papers). The work is most often cited by research in Signal Processing (1.5k citations), Computational Mathematics (47 citations), Computational Theory and Mathematics (1.0k citations), Computational Mechanics (1.1k citations) and Control and Systems Engineering (1.2k citations). M. Morf has collaborated with scholars based in United States, Canada and Sweden. Frequent co-authors include T. Kailath, Sun‐Yuan Kung, B. Friedlander, A. Vieira, D. Lee, Lennart Ljung, Bernard C. Levy, B. Dickinson, D.D. Falconer and G. Sidhu. Their work appears in journals such as IEEE Transactions on Automatic Control, Proceedings of the IEEE, Linear Algebra and its Applications, Journal of Consulting and Clinical Psychology and Automatica.

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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