Sayed Pouria Talebi

682 total citations
31 papers, 511 citations indexed

About

Sayed Pouria Talebi is a scholar working on Artificial Intelligence, Computational Mechanics and Computer Networks and Communications. According to data from OpenAlex, Sayed Pouria Talebi has authored 31 papers receiving a total of 511 indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Artificial Intelligence, 15 papers in Computational Mechanics and 10 papers in Computer Networks and Communications. Recurrent topics in Sayed Pouria Talebi's work include Advanced Adaptive Filtering Techniques (14 papers), Target Tracking and Data Fusion in Sensor Networks (12 papers) and Distributed Control Multi-Agent Systems (9 papers). Sayed Pouria Talebi is often cited by papers focused on Advanced Adaptive Filtering Techniques (14 papers), Target Tracking and Data Fusion in Sensor Networks (12 papers) and Distributed Control Multi-Agent Systems (9 papers). Sayed Pouria Talebi collaborates with scholars based in United Kingdom, Norway and Finland. Sayed Pouria Talebi's co-authors include Stefan Werner, Danilo P. Mandic, Sithan Kanna, Vinay Chakravarthi Gogineni, Naveen K. D. Venkategowda, Simon Godsill, Shengxi Li, Yili Xia, Visa Koivunen and Dongpo Xu and has published in prestigious journals such as IEEE Transactions on Automatic Control, IEEE Transactions on Signal Processing and IEEE Signal Processing Magazine.

In The Last Decade

Sayed Pouria Talebi

30 papers receiving 504 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Sayed Pouria Talebi United Kingdom 13 220 202 179 158 113 31 511
Mehdi Korki Australia 12 84 0.4× 192 1.0× 98 0.5× 159 1.0× 105 0.9× 43 451
Reza Abdolee United States 13 57 0.3× 222 1.1× 132 0.7× 173 1.1× 36 0.3× 43 423
Fawad Zaman Pakistan 14 63 0.3× 75 0.4× 82 0.5× 169 1.1× 51 0.5× 59 519
Liyan Qiao China 12 194 0.9× 139 0.7× 19 0.1× 130 0.8× 37 0.3× 95 521
Hakan Ali Çırpan Türkiye 17 139 0.6× 123 0.6× 380 2.1× 222 1.4× 24 0.2× 144 948
Symeon Chouvardas Greece 10 113 0.5× 267 1.3× 192 1.1× 147 0.9× 21 0.2× 22 441
Jesús Navarro-Moreno Spain 11 145 0.7× 135 0.7× 48 0.3× 160 1.0× 79 0.7× 53 363
B. Baykal Türkiye 11 107 0.5× 90 0.4× 99 0.6× 146 0.9× 37 0.3× 70 422
Luiz F. Q. Silveira Brazil 11 238 1.1× 54 0.3× 277 1.5× 214 1.4× 58 0.5× 47 533
Pyung Soo Kim South Korea 12 306 1.4× 87 0.4× 112 0.6× 53 0.3× 377 3.3× 49 641

Countries citing papers authored by Sayed Pouria Talebi

Since Specialization
Citations

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

Fields of papers citing papers by Sayed Pouria Talebi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Sayed Pouria Talebi. 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 Sayed Pouria Talebi. The network helps show where Sayed Pouria Talebi may publish in the future.

Co-authorship network of co-authors of Sayed Pouria Talebi

This figure shows the co-authorship network connecting the top 25 collaborators of Sayed Pouria Talebi. A scholar is included among the top collaborators of Sayed Pouria Talebi based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Sayed Pouria Talebi. Sayed Pouria Talebi is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Took, Clive Cheong, et al.. (2024). Augmented Statistics of Quaternion Random Variables: A lynchpin of quaternion learning machines. IEEE Signal Processing Magazine. 41(3). 72–87. 2 indexed citations
2.
Talebi, Sayed Pouria & Danilo P. Mandic. (2024). On the Dynamics of Multiagent Nonlinear Filtering and Learning. 1–6. 3 indexed citations
3.
Zhang, Min, Min Xiang, Zhi Zheng, Sayed Pouria Talebi, & Danilo P. Mandic. (2024). A class of widely linear quaternion blind equalisation algorithms. Signal Processing. 230. 109863–109863.
4.
Talebi, Sayed Pouria, Hossein Hassanpour Darvishi, Stefan Werner, & Pierluigi Salvo Rossi. (2022). Gradient-Descent Adaptive Filtering Using Gradient Adaptive Step-Size. 321–325. 1 indexed citations
5.
Talebi, Sayed Pouria, Stefan Werner, & Danilo P. Mandic. (2022). Fractional-Order Learning Systems. 2022 International Joint Conference on Neural Networks (IJCNN). 1–6. 1 indexed citations
6.
Venkategowda, Naveen K. D., et al.. (2022). Privacy-Preserving Distributed Kalman Filtering. IEEE Transactions on Signal Processing. 70. 3074–3089. 20 indexed citations
7.
Talebi, Sayed Pouria, Stefan Werner, Yih-Fang Huang, & Vijay Gupta. (2022). Distributed Algebraic Riccati Equations in Multi-Agent Systems. 2022 European Control Conference (ECC). 1810–1817. 2 indexed citations
8.
Gogineni, Vinay Chakravarthi, Sayed Pouria Talebi, & Stefan Werner. (2021). Performance of Clustered Multitask Diffusion LMS Suffering From Inter-Node Communication Delays. IEEE Transactions on Circuits & Systems II Express Briefs. 68(7). 2695–2699. 8 indexed citations
9.
Venkategowda, Naveen K. D., et al.. (2021). Securing the Distributed Kalman Filter Against Curious Agents. 1–7. 1 indexed citations
10.
Venkategowda, Naveen K. D., et al.. (2021). Distributed Kalman Filtering with Privacy against Honest-but-Curious Adversaries. 2021 55th Asilomar Conference on Signals, Systems, and Computers. 5 indexed citations
11.
Gogineni, Vinay Chakravarthi, Sayed Pouria Talebi, Stefan Werner, & Danilo P. Mandic. (2020). Fractional-Order Correntropy Filters for Tracking Dynamic Systems in α-Stable Environments. IEEE Transactions on Circuits & Systems II Express Briefs. 67(12). 3557–3561. 22 indexed citations
12.
Talebi, Sayed Pouria, Stefan Werner, & Visa Koivunen. (2018). Kalman Filtering and Clustering in Sensor Networks. 1. 4309–4313. 2 indexed citations
13.
Talebi, Sayed Pouria & Stefan Werner. (2018). Distributed Kalman Filtering: Consensus, Diffusion, and Mixed. 2018 IEEE Conference on Control Technology and Applications (CCTA). 1126–1132. 12 indexed citations
14.
Talebi, Sayed Pouria & Stefan Werner. (2018). Distributed Kalman Filtering in Presence of Unknown Outer Network Actuations. IEEE Control Systems Letters. 3(1). 186–191. 11 indexed citations
15.
Talebi, Sayed Pouria & Danilo P. Mandic. (2017). Distributed Particle Filtering of $\alpha$ -Stable Signals. IEEE Signal Processing Letters. 24(12). 1862–1866. 19 indexed citations
16.
Talebi, Sayed Pouria, Sithan Kanna, & Danilo P. Mandic. (2015). Real-time estimation of quaternion impropriety. 557–561. 11 indexed citations
17.
Talebi, Sayed Pouria, Sithan Kanna, & Danilo P. Mandic. (2015). A non-linear state space frequency estimator for three-phase power systems. 1–7. 6 indexed citations
18.
Talebi, Sayed Pouria, Dongpo Xu, Anthony Kuh, & Danilo P. Mandic. (2014). A Quaternion Least Mean Phase adaptive estimator. 6419–6423. 2 indexed citations
19.
Talebi, Sayed Pouria. (2014). Primary service outage and secondary service performance in cognitive radio networks. Wireless Communications and Mobile Computing. 15(16). 1982–1990. 6 indexed citations
20.
Kanna, Sithan, Sayed Pouria Talebi, & Danilo P. Mandic. (2014). Diffusion widely linear adaptive estimation of system frequency in distributed power grids. 772–778. 22 indexed citations

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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