M. Nayeri

845 citations
45 papers · 606 · h-index 11

Impact in

Papers in

M. Nayeri

41 papers receiving 586 citations

Peers

M. Nayeri
Comparison fields: 5 of 63
  • Signal Processing 147
  • Statistics, Probability and Uncertainty 82
  • Bioengineering 62
  • Computational Mechanics 204
  • Control and Systems Engineering 214
Replace K.Y. Chan with:
K.Y. Chan Hong Kong
Tsung-Han Wu Taiwan
Eric S. Lagergren United States
Yan Xin Singapore
Jilin Yang China
Wendong Wang China
Ruili Wang China
Sergey V. Muravyov Russia
M. Nayeri relative to K.Y. Chan Hong Kong K.Y. Chan's profile →
Citations per field
00.5×9.1×
K.Y. Chan · 1×
Citations per year

Countries citing papers authored by M. Nayeri

Since Specialization
Citations

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

Fields of papers citing papers by M. Nayeri

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 45 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2020157
2 199397
3 198959
4 200958
5 199447
6 199024
7 199023
8 201121
9 201718
10 199812
11 201910
12 200210
13 19936
14
RELATIONSHIPS BETWEEN ERROR SURFACES AND NETWORK ARCHITECTURES IN ADAPTIVE FILTERS.
19875
15 19975
16
Improvements in Adaptive IIR Filtering Theory and Application
19885
17 20025
18 20234
19 19964
20 19973

About M. Nayeri

M. Nayeri is a scholar working on Computational Mechanics, Signal Processing, Computer Vision and Pattern Recognition, Control and Systems Engineering and Civil and Structural Engineering, having authored 45 papers that have together received 606 indexed citations. Recurring topics across this work include Advanced Adaptive Filtering Techniques (26 papers), Image and Signal Denoising Methods (13 papers), Control Systems and Identification (12 papers), Blind Source Separation Techniques (11 papers), Digital Filter Design and Implementation (7 papers), Structural Health Monitoring Techniques (4 papers), Neural Networks and Applications (4 papers) and Gas Sensing Nanomaterials and Sensors (4 papers). The work is most often cited by research in Signal Processing (147 citations), Statistics, Probability and Uncertainty (82 citations), Bioengineering (62 citations), Computational Mechanics (204 citations) and Control and Systems Engineering (214 citations). M. Nayeri has collaborated with scholars based in United States, Iran and Japan. Frequent co-authors include J.R. Deller, W.K. Jenkins, Mehdi Ghazanfari, Adel Alaeddini, Hong Fan, Radislav A. Potyrailo, Xiaxi Li, Guang Wu, C. C. Calvert and Daniel Sexton. Their work appears in journals such as International Journal of Adaptive Control and Signal Processing, Information Sciences, Applied Spectroscopy, Proceedings of the IEEE and IEEE Signal Processing Letters.

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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