V.J. Mathews

4.8k total citations · 2 hit papers
151 papers, 3.4k citations indexed

About

V.J. Mathews is a scholar working on Computational Mechanics, Signal Processing and Control and Systems Engineering. According to data from OpenAlex, V.J. Mathews has authored 151 papers receiving a total of 3.4k indexed citations (citations by other indexed papers that have themselves been cited), including 62 papers in Computational Mechanics, 60 papers in Signal Processing and 35 papers in Control and Systems Engineering. Recurrent topics in V.J. Mathews's work include Advanced Adaptive Filtering Techniques (61 papers), Blind Source Separation Techniques (34 papers) and Control Systems and Identification (32 papers). V.J. Mathews is often cited by papers focused on Advanced Adaptive Filtering Techniques (61 papers), Blind Source Separation Techniques (34 papers) and Control Systems and Identification (32 papers). V.J. Mathews collaborates with scholars based in United States, Italy and Taiwan. V.J. Mathews's co-authors include Giovanni L. Sicuranza, Giovanni Ramponi, Andrea Polesel, Zhong Xie, Sung Ho Cho, Junghsi Lee, Alberto Carini, M.A. Syed, Ashutosh Pandey and Gregory A. Clark and has published in prestigious journals such as Proceedings of the IEEE, CHEST Journal and IEEE Transactions on Image Processing.

In The Last Decade

V.J. Mathews

138 papers receiving 3.2k citations

Hit Papers

Image enhancement via adaptive unsharp masking 2000 2026 2008 2017 2000 2000 100 200 300 400 500

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
V.J. Mathews United States 24 1.5k 1.3k 802 729 482 151 3.4k
Maurice Bellanger France 19 1.6k 1.1× 1.7k 1.3× 517 0.6× 375 0.5× 1.4k 3.0× 70 3.8k
J.C.M. Bermudez Brazil 25 1.7k 1.1× 1.5k 1.1× 503 0.6× 361 0.5× 230 0.5× 160 2.4k
Søren Holdt Jensen Denmark 33 1.8k 1.2× 2.5k 1.9× 923 1.2× 180 0.2× 753 1.6× 237 4.7k
Tianshuang Qiu China 26 549 0.4× 965 0.7× 534 0.7× 360 0.5× 413 0.9× 194 2.7k
Paulo S. R. Diniz Brazil 32 2.6k 1.7× 2.6k 1.9× 715 0.9× 727 1.0× 1.4k 2.9× 271 4.8k
Kenneth E. Barner United States 34 873 0.6× 931 0.7× 1.7k 2.1× 400 0.5× 470 1.0× 215 4.6k
Mads Græsbøll Christensen Denmark 28 1.7k 1.1× 2.7k 2.0× 674 0.8× 206 0.3× 490 1.0× 315 3.8k
Kjersti Engan Norway 19 2.1k 1.3× 1.3k 1.0× 1.7k 2.1× 138 0.2× 395 0.8× 115 4.3k
S.T. Alexander United States 15 1.5k 1.0× 1.4k 1.0× 433 0.5× 398 0.5× 487 1.0× 58 2.7k
Srdjan Stanković Montenegro 26 969 0.6× 701 0.5× 1.1k 1.4× 392 0.5× 328 0.7× 162 2.5k

Countries citing papers authored by V.J. Mathews

Since Specialization
Citations

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

Fields of papers citing papers by V.J. Mathews

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by V.J. Mathews. 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 V.J. Mathews. The network helps show where V.J. Mathews may publish in the future.

Co-authorship network of co-authors of V.J. Mathews

This figure shows the co-authorship network connecting the top 25 collaborators of V.J. Mathews. A scholar is included among the top collaborators of V.J. Mathews 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 V.J. Mathews. V.J. Mathews 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.
Mathews, V.J., et al.. (2024). A Multimodal Assistive-Robotic-Arm Control System to Increase Independence After Tetraplegia. IEEE Transactions on Neural Systems and Rehabilitation Engineering. 32. 2124–2133. 5 indexed citations
2.
Mathews, V.J., et al.. (2024). A Standardized Vibro-tactile Sensory Feedback System For Upper-limb Prostheses. PubMed. 2024. 1–4.
3.
Gurney, Jason, et al.. (2023). An online learning algorithm for adapting leg stiffness and stride angle for efficient quadruped robot trotting. Frontiers in Robotics and AI. 10. 1127898–1127898. 1 indexed citations
4.
Warren, David J., et al.. (2020). A Nonlinear Latching Filter to Remove Jitter From Movement Estimates for Prostheses. IEEE Transactions on Neural Systems and Rehabilitation Engineering. 28(12). 2849–2858. 6 indexed citations
5.
Warren, David J., et al.. (2019). Deep Learning Movement Intent Decoders Trained With Dataset Aggregation for Prosthetic Limb Control. IEEE Transactions on Biomedical Engineering. 66(11). 3192–3203. 38 indexed citations
6.
Wendelken, Suzanne, Tyler S. Davis, David T. Kluger, et al.. (2017). Polynomial Kalman filter for myoelectric prosthetics using efficient kernel ridge regression. 432–435. 9 indexed citations
7.
Lanspa, Michael J., et al.. (2017). Systolic blood pressure variability in patients with early severe sepsis or septic shock: a prospective cohort study. BMC Anesthesiology. 17(1). 82–82. 21 indexed citations
8.
Mathews, V.J., et al.. (2016). Control of Dynamic Limb Motion Using Fatigue-Resistant Asynchronous Intrafascicular Multi-Electrode Stimulation. Frontiers in Neuroscience. 10. 414–414. 13 indexed citations
9.
Mathews, V.J., et al.. (2014). A phase likelihood-based algorithm for blind identification of PSK signals. 5730–5734. 3 indexed citations
10.
Mathews, V.J., et al.. (2014). Equalization of excursion and current-dependent nonlinearities in loudspeakers. 6697–6701. 2 indexed citations
11.
Brown, Samuel M., Jason P. Jones, Daniel Knox, et al.. (2013). Initial fractal exponent of heart rate variability is associated with success of early resuscitation in patients with severe sepsis or septic shock: a prospective cohort study. Journal of Critical Care. 28(6). 959–963. 13 indexed citations
13.
Mathews, V.J., et al.. (2011). Multiple-Input Single-Output Closed-Loop Isometric Force Control Using Asynchronous Intrafascicular Multi-Electrode Stimulation. IEEE Transactions on Neural Systems and Rehabilitation Engineering. 19(3). 325–332. 19 indexed citations
14.
Struijk, P. C., V.J. Mathews, T. Loupas, et al.. (2008). Blood pressure estimation in the human fetal descending aorta. Ultrasound in Obstetrics and Gynecology. 32(5). 673–681. 53 indexed citations
15.
Struijk, P. C., P. A. Stewart, V.J. Mathews, et al.. (2005). Wall shear stress and related hemodynamic parameters in the fetal descending aorta derived from color Doppler velocity profiles. Ultrasound in Medicine & Biology. 31(11). 1441–1450. 28 indexed citations
16.
Mathews, V.J., et al.. (2003). Robust estimation of fetal heart rate variability using doppler ultrasound. IEEE Transactions on Biomedical Engineering. 50(8). 950–957. 8 indexed citations
17.
Mathews, V.J., et al.. (2003). A fast recursive least-squares second order Volterra filter. 1383–1386. 6 indexed citations
18.
Mathews, V.J., et al.. (2002). Adaptive bilinear predictors. iii. III/489–III/492. 7 indexed citations
19.
Mathews, V.J.. (1992). Multiplication free vector quantization using L/sub 1/ distortion measure and its variants. IEEE Transactions on Image Processing. 1(1). 11–17. 12 indexed citations
20.
East, Katherine, et al.. (1989). Computerized artifact detection for ventilatory inductance plethysmographic apnea monitors. Journal of Clinical Monitoring and Computing. 5(3). 170–176. 10 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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