Nigel G. Stocks

3.6k total citations · 1 hit paper
42 papers, 2.3k citations indexed

About

Nigel G. Stocks is a scholar working on Statistical and Nonlinear Physics, Cognitive Neuroscience and Computer Networks and Communications. According to data from OpenAlex, Nigel G. Stocks has authored 42 papers receiving a total of 2.3k indexed citations (citations by other indexed papers that have themselves been cited), including 25 papers in Statistical and Nonlinear Physics, 22 papers in Cognitive Neuroscience and 10 papers in Computer Networks and Communications. Recurrent topics in Nigel G. Stocks's work include stochastic dynamics and bifurcation (25 papers), Neural dynamics and brain function (20 papers) and Diffusion and Search Dynamics (6 papers). Nigel G. Stocks is often cited by papers focused on stochastic dynamics and bifurcation (25 papers), Neural dynamics and brain function (20 papers) and Diffusion and Search Dynamics (6 papers). Nigel G. Stocks collaborates with scholars based in United Kingdom, Australia and France. Nigel G. Stocks's co-authors include Mark D. McDonnell, Derek Abbott, C. E. M. Pearce, Yunfei Chen, Evor L. Hines, Robert P. Morse, Alexander P. Nikitin, Aruneema Das, Harsimrat Singh and Friederike Schlaghecken and has published in prestigious journals such as Physical Review Letters, Sensors and Actuators B Chemical and IEEE Transactions on Vehicular Technology.

In The Last Decade

Nigel G. Stocks

40 papers receiving 2.2k citations

Hit Papers

align trajectories

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.

Stochastic Resonance

2008 1.2k citations Mark D. McDonnell, Derek Abbott et al. arXiv (Cornell University) profile →

Peers

Nigel G. Stocks

SNP

CNC

GPC

François Chapeau‐Blondeau France

Thomas T. Imhoff United States

N. G. Stocks United Kingdom

T.D. Frank United States

Sudeshna Sinha India

D. G. Luchinsky United Kingdom

Erik M. Bollt United States

K. Murali India

Bruce McNamara United States

John F. Lindner United States

François Chapeau‐Blondeau France

Nigel G. Stocks

2.0k ×1.4

SNP

606 ×0.8

786 ×1.3

CNC

563 ×1.5

333 ×1.1

GPC

Citations per year, relative to Nigel G. Stocks Nigel G. Stocks (= 1×) peers François Chapeau‐Blondeau

Countries citing papers authored by Nigel G. Stocks

Since Specialization

Citations

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

Fields of papers citing papers by Nigel G. Stocks

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Nigel G. Stocks. 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 Nigel G. Stocks. The network helps show where Nigel G. Stocks may publish in the future.

Co-authorship network of co-authors of Nigel G. Stocks

This figure shows the co-authorship network connecting the top 25 collaborators of Nigel G. Stocks. A scholar is included among the top collaborators of Nigel G. Stocks 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 Nigel G. Stocks. Nigel G. Stocks is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Chatrabgoun, Omid, Amin Hosseinian‐Far, Victor Chang, Nigel G. Stocks, & Alireza Daneshkhah. (2017). Approximating non-Gaussian Bayesian networks using minimum information vine model with applications in financial modelling. Journal of Computational Science. 24. 266–276. 17 indexed citations

Yang, Jianhua, Harsimrat Singh, Evor L. Hines, et al.. (2012). Channel selection and classification of electroencephalogram signals: An artificial neural network and genetic algorithm-based approach. Artificial Intelligence in Medicine. 55(2). 117–126. 118 indexed citations

Durrant, Simon, Yanmei Kang, Nigel G. Stocks, & Jianfeng Feng. (2011). Suprathreshold stochastic resonance in neural processing tuned by correlation. Physical Review E. 84(1). 11923–11923. 27 indexed citations

Nikitin, Alexander P., Nigel G. Stocks, Robert P. Morse, & Mark D. McDonnell. (2009). Neural Population Coding Is Optimized by Discrete Tuning Curves. Physical Review Letters. 103(13). 138101–138101. 34 indexed citations

Freund, Jan A., Alexander P. Nikitin, & Nigel G. Stocks. (2009). Phase Locking Below Rate Threshold in Noisy Model Neurons. Neural Computation. 22(3). 599–620. 4 indexed citations

McDonnell, Mark D., Nigel G. Stocks, C. E. M. Pearce, & Derek Abbott. (2009). Stochastic Resonance: From Suprathreshold Stochastic Resonance to Stochastic Signal Quantization. Adelaide Research & Scholarship (AR&S) (University of Adelaide). 178 indexed citations

McDonnell, Mark D., Derek Abbott, Nigel G. Stocks, & C. E. M. Pearce. (2008). Stochastic Resonance. arXiv (Cornell University). 1223 indexed citations breakdown →

McDonnell, Mark D. & Nigel G. Stocks. (2008). Maximally Informative Stimuli and Tuning Curves for Sigmoidal Rate-Coding Neurons and Populations. Physical Review Letters. 101(5). 58103–58103. 47 indexed citations

McDonnell, Mark D. & Nigel G. Stocks. (2008). Maximally Informative Stimuli and Tuning Curves for Sigmoidal Rate-Coding Neurons with Quasi-Poisson Variability. arXiv (Cornell University). 394(1). 205–10.

10.

McDonnell, Mark D., Nigel G. Stocks, & Derek Abbott. (2007). Optimal stimulus and noise distributions for information transmission via suprathreshold stochastic resonance. Physical Review E. 75(6). 61105–61105. 39 indexed citations

11.

Amblard, Pierre‐Olivier, Steeve Zozor, Mark D. McDonnell, & Nigel G. Stocks. (2007). Pooling networks for a discrimination task: noise-enhanced detection. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 6602. 66020S–66020S. 6 indexed citations

12.

McDonnell, Mark D., Nigel G. Stocks, & Derek Abbott. (2007). Optimal coding of a random stimulus by a population of parallel neuron models. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 6602. 66020R–66020R.

13.

McDonnell, Mark D., Pierre‐Olivier Amblard, Nigel G. Stocks, Steeve Zozor, & Derek Abbott. (2006). High-resolution optimal quantization for stochastic pooling networks. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 6417. 641706–641706. 1 indexed citations

14.

McDonnell, Mark D., Nigel G. Stocks, C. E. M. Pearce, & Derek Abbott. (2005). Analog-to-digital conversion using suprathreshold stochastic resonance. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 5649. 75–75. 6 indexed citations

15.

Morse, Robert P. & Nigel G. Stocks. (2005). Enhanced cochlear implant coding using multiplicative noise (Invited Paper). Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 5841. 23–23. 4 indexed citations

16.

McDonnell, Mark D., Nigel G. Stocks, C. E. M. Pearce, & Derek Abbott. (2005). QUANTIZATION IN THE PRESENCE OF LARGE AMPLITUDE THRESHOLD NOISE. Fluctuation and Noise Letters. 5(3). L457–L468. 24 indexed citations

17.

Dutta, Ritaban, Aruneema Das, Nigel G. Stocks, & David W. Morgan. (2005). Stochastic resonance-based electronic nose: A novel way to classify bacteria. Sensors and Actuators B Chemical. 115(1). 17–27. 60 indexed citations

18.

McDonnell, Mark D., Nigel G. Stocks, C. E. M. Pearce, & Derek Abbott. (2002). Maximizing information transfer through nonlinear noisy devices. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 4937. 254–254. 1 indexed citations

19.

Dykman, M. I., D. G. Luchinsky, R. Mannella, et al.. (1995). Stochastic resonance and its provenance. Izvestiya VUZ Applied Nonlinear Dynamics. 3(3). 56–69. 1 indexed citations

20.

Tredgold, R.H., et al.. (1987). Langmuir—Blodgett films from porphyrins. British Polymer Journal. 19(3-4). 397–400. 6 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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