S.C. Douglas

6.3k total citations · 1 hit paper
186 papers, 4.3k citations indexed

About

S.C. Douglas is a scholar working on Signal Processing, Computational Mechanics and Computer Vision and Pattern Recognition. According to data from OpenAlex, S.C. Douglas has authored 186 papers receiving a total of 4.3k indexed citations (citations by other indexed papers that have themselves been cited), including 127 papers in Signal Processing, 103 papers in Computational Mechanics and 32 papers in Computer Vision and Pattern Recognition. Recurrent topics in S.C. Douglas's work include Advanced Adaptive Filtering Techniques (101 papers), Blind Source Separation Techniques (100 papers) and Speech and Audio Processing (75 papers). S.C. Douglas is often cited by papers focused on Advanced Adaptive Filtering Techniques (101 papers), Blind Source Separation Techniques (100 papers) and Speech and Audio Processing (75 papers). S.C. Douglas collaborates with scholars based in United States, United Kingdom and Japan. S.C. Douglas's co-authors include Marc Bodson, Mark J. Martinko, Andrzej Cichocki, Danilo P. Mandic, S. Amari, T.H. Meng, Шун-ичи Амари, Yili Xia, Howard H. Yang and M. J. Duff and has published in prestigious journals such as Journal of Applied Psychology, Proceedings of the IEEE and Automatica.

In The Last Decade

S.C. Douglas

176 papers receiving 4.0k citations

Hit Papers

Adaptive algorithms for the rejection of sinusoidal distu... 1997 2026 2006 2016 1997 100 200 300 400

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
S.C. Douglas United States 34 2.3k 2.0k 830 582 458 186 4.3k
J. Makhoul United States 31 4.7k 2.0× 1.5k 0.7× 466 0.6× 3.6k 6.2× 2.2k 4.9× 124 7.6k
Edward J. Coyle United States 32 779 0.3× 599 0.3× 234 0.3× 637 1.1× 1.6k 3.5× 195 5.4k
Scott Rickard Ireland 18 1.9k 0.8× 1.1k 0.5× 212 0.3× 344 0.6× 414 0.9× 93 2.8k
M. M. Sondhi United States 35 3.3k 1.4× 1.8k 0.9× 276 0.3× 1.9k 3.2× 1.2k 2.7× 88 6.6k
Todd K. Moon United States 16 808 0.4× 381 0.2× 284 0.3× 1.2k 2.0× 795 1.7× 138 4.8k
Y. Neuvo Finland 31 2.0k 0.9× 1.2k 0.6× 260 0.3× 594 1.0× 3.7k 8.0× 215 5.8k
Ingo Wald United States 30 417 0.2× 1.5k 0.8× 188 0.2× 682 1.2× 2.4k 5.3× 115 5.1k
Emmanuel Ifeachor United Kingdom 30 765 0.3× 171 0.1× 160 0.2× 480 0.8× 951 2.1× 146 3.5k
Mounir Ghogho United Kingdom 35 1.0k 0.4× 257 0.1× 293 0.4× 1.2k 2.0× 391 0.9× 362 5.3k
Howard H. Yang China 26 1.8k 0.8× 394 0.2× 235 0.3× 3.0k 5.2× 507 1.1× 160 5.6k

Countries citing papers authored by S.C. Douglas

Since Specialization
Citations

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

Fields of papers citing papers by S.C. Douglas

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of S.C. Douglas

This figure shows the co-authorship network connecting the top 25 collaborators of S.C. Douglas. A scholar is included among the top collaborators of S.C. Douglas 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 S.C. Douglas. S.C. Douglas 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.
Douglas, S.C.. (2020). The Infinity Project: On The Design And Implementation Of A High School Engineering Curriculum. Papers on Engineering Education Repository (American Society for Engineering Education). 11.1304.1–11.1304.7.
2.
Xiang, Min, S.C. Douglas, & Danilo P. Mandic. (2017). The quaternion least mean magnitude phase adaptive filtering algorithm. 1–5. 7 indexed citations
3.
Xia, Yili, S.C. Douglas, & Danilo P. Mandic. (2012). Adaptive Frequency Estimation in Smart Grid Applications: Exploiting Noncircularity and Widely Linear Adaptive Estimators. IEEE Signal Processing Magazine. 29(5). 44–54. 138 indexed citations
4.
Douglas, S.C., et al.. (2010). Experimentally validated computational imaging with adaptive multiaperture folded architecture. Applied Optics. 49(10). B51–B51. 5 indexed citations
5.
Rajan, Dinesh, et al.. (2008). Computational imaging systems: joint design and end-to-end optimality. Applied Optics. 47(10). B86–B86. 7 indexed citations
6.
Gupta, Malay & S.C. Douglas. (2008). An iterative spatio-temporal speech enhancement algorithm for microphone arrays. Proceedings of the ... IEEE International Conference on Acoustics, Speech, and Signal Processing. 81–84. 2 indexed citations
7.
Christensen, Marc P., et al.. (2006). Adaptive flat multiresolution multiplexed computational imaging architecture utilizing micromirror arrays to steer subimager fields of view. Applied Optics. 45(13). 2884–2884. 22 indexed citations
8.
Douglas, S.C., et al.. (2006). A Secure Event Agreement (SEA) protocol for peer-to-peer games. 8 pp.–41. 26 indexed citations
9.
Douglas, S.C.. (2006). An Adaptive Constraint Method for Paraunitary Filter Banks with Applications to Spatiotemporal Subspace Tracking. EURASIP Journal on Advances in Signal Processing. 2007(1). 4 indexed citations
10.
Douglas, S.C., et al.. (2002). Designing orthonormal subspace tracking algorithms. 2. 1441–1445. 6 indexed citations
11.
Douglas, S.C., et al.. (2002). Mean square error analyses of adaptive blind source separation algorithms. i. 333–342. 1 indexed citations
12.
Douglas, S.C., Andrzej Cichocki, & S. Amari. (2002). Quasi-Newton filtered-error and filtered-regressor algorithms for adaptive equalization and deconvolution. 109–112. 2 indexed citations
13.
Douglas, S.C. & Markus Rupp. (2002). A posteriori updates for adaptive filters. 2. 1641–1645. 10 indexed citations
14.
Douglas, S.C.. (2002). Simplified stochastic gradient adaptive filters using partial updating. assp 34. 265–268. 5 indexed citations
15.
Douglas, S.C., et al.. (2002). Adaptive paraunitary filter banks for contrast-based multichannel blind deconvolution. 5. 2753–2756. 6 indexed citations
16.
Douglas, S.C. & Mark J. Martinko. (2001). Exploring the role of individual differences in the prediction of workplace aggression.. Journal of Applied Psychology. 86(4). 547–559. 407 indexed citations
17.
Douglas, S.C.. (2000). Self-stabilized gradient algorithms for blind source separation with orthogonality constraints. IEEE Transactions on Neural Networks. 11(6). 1490–1497. 51 indexed citations
18.
Амари, Шун-ичи, S.C. Douglas, & Andrzej Cichocki. (1998). Multichannel blind deconvolution and source separation using the natural gradient. IEEE Transactions on Signal Processing. 46(3). 821. 8 indexed citations
19.
Douglas, S.C.. (1995). Analysis and implementation of the max-NLMS adaptive filterAdaptive discrete cosine transform for feedback active noise control. 8(2). 659–3. 11 indexed citations
20.
Douglas, S.C.. (1995). Analysis of the multiple-error and block least-mean-square adaptive algorithms. IEEE Transactions on Circuits and Systems II Analog and Digital Signal Processing. 42(2). 92–101. 21 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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