A. Chandrasekar

2.1k total citations · 1 hit paper
38 papers, 1.7k citations indexed

About

A. Chandrasekar is a scholar working on Computer Networks and Communications, Statistical and Nonlinear Physics and Control and Systems Engineering. According to data from OpenAlex, A. Chandrasekar has authored 38 papers receiving a total of 1.7k indexed citations (citations by other indexed papers that have themselves been cited), including 31 papers in Computer Networks and Communications, 15 papers in Statistical and Nonlinear Physics and 11 papers in Control and Systems Engineering. Recurrent topics in A. Chandrasekar's work include Neural Networks Stability and Synchronization (30 papers), stochastic dynamics and bifurcation (13 papers) and Advanced Memory and Neural Computing (9 papers). A. Chandrasekar is often cited by papers focused on Neural Networks Stability and Synchronization (30 papers), stochastic dynamics and bifurcation (13 papers) and Advanced Memory and Neural Computing (9 papers). A. Chandrasekar collaborates with scholars based in India, China and United Arab Emirates. A. Chandrasekar's co-authors include R. Rakkiyappan, Jinde Cao, Quanxin Zhu, T. Radhika, S. Lakshmanan, Ju H. Park, V. Vijayakumar, Yang Cao, Fathalla A. Rihan and R. Krishnasamy and has published in prestigious journals such as IEEE Transactions on Neural Networks and Learning Systems, Neurocomputing and Journal of the Franklin Institute.

In The Last Decade

A. Chandrasekar

33 papers receiving 1.7k citations

Hit Papers

Analysis of Markovian Jump Stochastic Cohen–Grossberg BAM... 2023 2026 2024 2023 25 50 75 100
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Analysis of Markovian Jump Stochastic Cohen–Grossberg BAM Neural Networks with Time Delays for Exponential Input-to-State Stability
    2023 105 citations T. Radhika, A. Chandrasekar et al. Neural Processing Letters profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
A. Chandrasekar India 24 1.2k 569 486 457 379 38 1.7k
Antonio G. Marqués Spain 26 991 0.9× 693 1.2× 827 1.7× 1.3k 2.8× 93 0.2× 150 2.5k
Paolo Di Lorenzo Italy 22 1.4k 1.2× 320 0.6× 757 1.6× 946 2.1× 70 0.2× 125 2.6k
Makan Fardad United States 19 640 0.6× 167 0.3× 398 0.8× 353 0.8× 506 1.3× 70 1.4k
Yongbin Yu China 20 592 0.5× 345 0.6× 401 0.8× 287 0.6× 251 0.7× 124 1.2k
Leimin Wang China 36 2.6k 2.3× 1.4k 2.4× 1.4k 2.8× 665 1.5× 615 1.6× 132 3.5k
Zhenjiang Zhao China 29 2.4k 2.0× 1.1k 1.9× 697 1.4× 1.1k 2.4× 511 1.3× 72 2.7k
Kun She China 19 685 0.6× 258 0.5× 192 0.4× 234 0.5× 203 0.5× 95 1.3k
Sichun Du China 23 385 0.3× 748 1.3× 710 1.5× 357 0.8× 82 0.2× 73 1.6k
Yong Xu China 30 2.0k 1.7× 293 0.5× 428 0.9× 596 1.3× 2.0k 5.3× 150 3.1k
Sezgin Kaçar Türkiye 22 333 0.3× 732 1.3× 156 0.3× 494 1.1× 121 0.3× 76 1.7k

Countries citing papers authored by A. Chandrasekar

Since Specialization
Citations

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

Fields of papers citing papers by A. Chandrasekar

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of A. Chandrasekar

This figure shows the co-authorship network connecting the top 25 collaborators of A. Chandrasekar. A scholar is included among the top collaborators of A. Chandrasekar 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 A. Chandrasekar. A. Chandrasekar 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.
2.
Chandrasekar, A., et al.. (2025). An adaptive frequency partitioning framework for epileptic seizure detection using TransseizNet. Neurological Research. 47(9). 876–890.
3.
Renjit, J. Arokia, et al.. (2025). Blockchain-Enhanced Iot Healthcare: Revolutionizing Secure Remote Access and Data Integrity. SSRN Electronic Journal.
4.
Chandrasekar, A., et al.. (2025). Resilient memory sampled-data controller for synchronization of semi-Markovian jump competitive neural networks with mixed delays. International Journal of Electrical Power & Energy Systems. 171. 110982–110982.
5.
Radhika, T., et al.. (2025). Robust dissipative sliding mode control synchronization of memristive inertial competitive neural networks with time-varying delay. The European Physical Journal Special Topics. 6 indexed citations
6.
Radhika, T., A. Chandrasekar, & V. Vijayakumar. (2024). Finite-time H∞ synchronization of semi-Markov jump neural networks with two delay components with stochastic sampled-data control. Bulletin des Sciences Mathématiques. 195. 103482–103482. 11 indexed citations
7.
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Panda, Sumati Kumari, et al.. (2024). Results on controllability of Sobolev-type nonlocal neutral functional integrodifferential evolution hemivariational inequalities with impulsive effects via resolvent operators. Journal of Applied Mathematics and Computing. 71(2). 2301–2326. 1 indexed citations
9.
Panda, Sumati Kumari, et al.. (2024). On the approximate controllability for neutral fractional stochastic differential hemivariational inequalities with history-dependent operator. Journal of Differential Equations. 422. 329–354. 2 indexed citations
10.
Cao, Yang, et al.. (2024). Exponential State Estimation for Delayed Competitive Neural Network Via Stochastic Sampled-Data Control with Markov Jump Parameters Under Actuator Failure. Journal of Artificial Intelligence and Soft Computing Research. 14(4). 373–385. 36 indexed citations
11.
Aslam, Muhammad Shamrooz, T. Radhika, A. Chandrasekar, & Quanxin Zhu. (2024). Improved Event-Triggered-Based Output Tracking for a Class of Delayed Networked T–S Fuzzy Systems. International Journal of Fuzzy Systems. 26(4). 1247–1260. 40 indexed citations
12.
Chandrasekar, A., et al.. (2022). Synchronization of Markovian jump neural networks for sampled data control systems with additive delay components: Analysis of image encryption technique. Mathematical Methods in the Applied Sciences. 49(3). 1879–1895. 56 indexed citations
13.
Rakkiyappan, R., et al.. (2016). Stability and synchronization analysis of inertial memristive neural networks with time delays. Cognitive Neurodynamics. 10(5). 437–451. 105 indexed citations
14.
Chandrasekar, A., R. Rakkiyappan, & Xiaodi Li. (2016). Effects of bounded and unbounded leakage time-varying delays in memristor-based recurrent neural networks with different memductance functions. Neurocomputing. 202. 67–83. 14 indexed citations
15.
Chandrasekar, A., R. Rakkiyappan, & Jinde Cao. (2015). Impulsive synchronization of Markovian jumping randomly coupled neural networks with partly unknown transition probabilities via multiple integral approach. Neural Networks. 70. 27–38. 50 indexed citations
16.
Rakkiyappan, R., A. Chandrasekar, Fathalla A. Rihan, & S. Lakshmanan. (2014). Exponential state estimation of Markovian jumping genetic regulatory networks with mode-dependent probabilistic time-varying delays. Mathematical Biosciences. 251. 30–53. 23 indexed citations
17.
Chandrasekar, A., R. Rakkiyappan, Jinde Cao, & S. Lakshmanan. (2014). Synchronization of memristor-based recurrent neural networks with two delay components based on second-order reciprocally convex approach. Neural Networks. 57. 79–93. 104 indexed citations
18.
19.
Rakkiyappan, R., A. Chandrasekar, & Jinde Cao. (2014). Passivity and Passification of Memristor-Based Recurrent Neural Networks With Additive Time-Varying Delays. IEEE Transactions on Neural Networks and Learning Systems. 26(9). 2043–2057. 122 indexed citations
20.
Rakkiyappan, R., A. Chandrasekar, S. Lakshmanan, & Ju H. Park. (2013). Exponential stability of Markovian jumping stochastic Cohen–Grossberg neural networks with mode-dependent probabilistic time-varying delays and impulses. Neurocomputing. 131. 265–277. 44 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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