K.C. Sharman

1.9k total citations · 1 hit paper
34 papers, 1.3k citations indexed

About

K.C. Sharman is a scholar working on Signal Processing, Artificial Intelligence and Civil and Structural Engineering. According to data from OpenAlex, K.C. Sharman has authored 34 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Signal Processing, 12 papers in Artificial Intelligence and 8 papers in Civil and Structural Engineering. Recurrent topics in K.C. Sharman's work include Direction-of-Arrival Estimation Techniques (16 papers), Structural Health Monitoring Techniques (8 papers) and Blind Source Separation Techniques (7 papers). K.C. Sharman is often cited by papers focused on Direction-of-Arrival Estimation Techniques (16 papers), Structural Health Monitoring Techniques (8 papers) and Blind Source Separation Techniques (7 papers). K.C. Sharman collaborates with scholars based in United Kingdom, United States and Spain. K.C. Sharman's co-authors include Petre Stoica, T.S. Durrani, B. Friedlander, Anna I. Esparcia-Alcázar, Eva Alfaro-Cid, Christopher P. Chambers, D.J. Murray-Smith, Yun Li, T.C. Tozer and Francisco Fernández de Vega and has published in prestigious journals such as IEEE Transactions on Signal Processing, Electronics Letters and Evolutionary Computation.

In The Last Decade

K.C. Sharman

34 papers receiving 1.3k citations

Hit Papers

Maximum likelihood methods for direction-of-arrival estim... 1990 2026 2002 2014 1990 200 400 600

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
K.C. Sharman United Kingdom 13 999 394 319 246 191 34 1.3k
Sylvie Marcos France 20 1.1k 1.1× 592 1.5× 377 1.2× 295 1.2× 180 0.9× 107 1.4k
Chaohuan Hou China 20 622 0.6× 577 1.5× 193 0.6× 158 0.6× 178 0.9× 103 1.2k
Christ D. Richmond United States 18 708 0.7× 751 1.9× 224 0.7× 138 0.6× 191 1.0× 82 1.2k
Da‐Zheng Feng China 19 553 0.6× 404 1.0× 187 0.6× 274 1.1× 206 1.1× 120 1.1k
R.D. DeGroat United States 14 490 0.5× 104 0.3× 115 0.4× 273 1.1× 77 0.4× 57 681
Fangqing Wen China 24 898 0.9× 905 2.3× 381 1.2× 161 0.7× 157 0.8× 68 1.5k
E. Satorius United States 14 462 0.5× 140 0.4× 183 0.6× 447 1.8× 117 0.6× 64 794
Α.Κ. Mahalanabis India 16 344 0.3× 188 0.5× 225 0.7× 103 0.4× 223 1.2× 91 877
Junpeng Shi China 26 1.3k 1.3× 1.5k 3.9× 532 1.7× 156 0.6× 165 0.9× 118 2.1k
Zhi Zheng China 25 1.7k 1.7× 1.3k 3.4× 843 2.6× 288 1.2× 76 0.4× 139 2.4k

Countries citing papers authored by K.C. Sharman

Since Specialization
Citations

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

Fields of papers citing papers by K.C. Sharman

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by K.C. Sharman. 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 K.C. Sharman. The network helps show where K.C. Sharman may publish in the future.

Co-authorship network of co-authors of K.C. Sharman

This figure shows the co-authorship network connecting the top 25 collaborators of K.C. Sharman. A scholar is included among the top collaborators of K.C. Sharman 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 K.C. Sharman. K.C. Sharman 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.
Alfaro-Cid, Eva, J. J. Merelo, Francisco Fernández de Vega, Anna I. Esparcia-Alcázar, & K.C. Sharman. (2010). Bloat Control Operators and Diversity in Genetic Programming: A Comparative Study. Evolutionary Computation. 18(2). 305–332. 31 indexed citations
2.
Esparcia-Alcázar, Anna I., et al.. (2006). An Evolutionary Algorithm for the Product to Shelf Allocation Problem. 3197–3203. 3 indexed citations
3.
Alfaro-Cid, Eva, K.C. Sharman, & Anna I. Esparcia-Alcázar. (2006). Evolving a Learning Machine by Genetic Programming. 2439. 254–258. 1 indexed citations
4.
Sharman, K.C. & B. Friedlander. (2005). Time-varying autoregressive modeling of a class of nonstationary signals. 9. 227–230. 17 indexed citations
5.
Sharman, K.C. & T.S. Durrani. (2005). Resolving power of signal subspace methods for finite data lengths. 10. 1501–1504. 12 indexed citations
6.
Sharman, K.C.. (2003). Maximum likelihood parameter estimation by simulated annealing. 2741–2744. 42 indexed citations
7.
Sharman, K.C., et al.. (2003). Genetic algorithms for spatial spectral estimation. 318–322. 4 indexed citations
8.
Esparcia-Alcázar, Anna I. & K.C. Sharman. (2002). Genetic programming techniques that evolve recurrent neural network architectures for signal processing. 4. 139–148. 6 indexed citations
9.
Murray-Smith, D.J., et al.. (1996). Nonlinear System Modelling Using Output Error Estimation Of A Local Model Network. ENLIGHTEN (Jurnal Bimbingan dan Konseling Islam). 5 indexed citations
10.
Chambers, Christopher P., T.C. Tozer, K.C. Sharman, & T.S. Durrani. (1996). Temporal and spatial sampling influence on the estimates of superimposed narrowband signals: when less can mean more. IEEE Transactions on Signal Processing. 44(12). 3085–3098. 41 indexed citations
11.
Li, Yun, et al.. (1996). Structural system identification using genetic programmingand a block diagram oriented simulation tool. Electronics Letters. 32(15). 1422–1424. 33 indexed citations
12.
Sharman, K.C., et al.. (1994). Estimation of signal parameters using the maximum likelihood method. 2 indexed citations
13.
Stoica, Petre & K.C. Sharman. (1990). Maximum Likelhood Methods for Direction-of- Arrival Estimation. 6 indexed citations
14.
Sharman, K.C., T.S. Durrani, & Luis Vergara. (1986). Adaptive algorithms for eigenstructure based spectral estimation and filtering. 2224–2229. 3 indexed citations
15.
Sharman, K.C. & T.S. Durrani. (1986). A comparative study of modern eigenstructure methods for bearing estimation-A new high performance approach. 130. 1737–1742. 22 indexed citations
16.
Friedlander, B. & K.C. Sharman. (1985). Performance evaluation of the modified Yule-Walker estimator. IEEE Transactions on Acoustics Speech and Signal Processing. 33(3). 719–725. 16 indexed citations
17.
Durrani, T.S. & K.C. Sharman. (1983). Eigenfilter approaches to adaptive array processing. IEE Proceedings F Communications, Radar and Signal Processing. 130(1). 22–28. 23 indexed citations
18.
Sharman, K.C. & T.S. Durrani. (1983). Spatial lattice filter for high-resolution spectral analysis of array data. IEE Proceedings F Communications, Radar and Signal Processing. 130(3). 279–287. 12 indexed citations
19.
Durrani, T.S. & K.C. Sharman. (1983). Eigenfilter approaches to adaptive array processing. IEE Proceedings F Communications Radar and Signal Processing. 130(1). 22–22. 11 indexed citations
20.
Durrani, T.S. & K.C. Sharman. (1982). Extraction of an eigenvector-oriented "Spectrum" from the MESA coefficients. IEEE Transactions on Acoustics Speech and Signal Processing. 30(4). 649–651. 11 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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