The DOI matches its Crossref record; 111 of the 111 references it cites were found in a registry or an index.
Stochastic resonance
Abstract
We are taught by conventional wisdom that the transmission and detection of signals is hindered by noise. However, during the last two decades, the paradigm of stochastic resonance (SR) proved this assertion wrong: indeed, addition of the appropriate amount of noise can boost a signal and hence facilitate its detection in a noisy environment. Due to its simplicity and robustness, SR has been implemented by mother nature on almost every scale, thus attracting interdisciplinary interest from physicists, geologists, engineers, biologists and medical doctors, who nowadays use it as an instrument for their specific purposes. At the present time, there exist a lot of diversified models of SR. Taking into account the progress achieved in both theoretical understanding and practical application of this phenomenon, we put the focus of the present review not on discussing in depth technical details of different models and approaches but rather on presenting a general and clear physical picture of SR on a pedagogical level. Particular emphasis will be given to the implementation of SR in generic quantum systems—an issue that has received limited attention in earlier review papers on the topic. The major part of our presentation relies on the two-state model of SR (or on simple variants thereof), which is general enough to exhibit the main features of SR and, in fact, covers many (if not most) of the examples of SR published so far. In order to highlight the diversity of the two-state model, we shall discuss several examples from such different fields as condensed matter, nonlinear and quantum optics and biophysics. Finally, we also discuss some situations that go beyond the generic SR scenario but are still characterized by a constructive role of noise.
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Cites
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Cited by
What Is Stochastic Resonance? Definitions, Misconceptions, Debates, and Its Relevance to Biology
McDonnell, M. D., & Abbott, D. (2009) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1000348 · Cited by 774
Increased Brain Signal Variability Accompanies Lower Behavioral Variability in Development
McIntosh, A. R., Kovacevic, N., & Itier, R. J. (2008) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1000106 · Cited by 431
Applications of stochastic resonance to machinery fault detection: A review and tutorial
Qiao, Z., Lei, Y., & Li, N. (2019) · Mechanical Systems and Signal Processing · doi:10.1016/j.ymssp.2018.12.032 · Cited by 308
Metadata
- Authors
- Wellens, T., Shatokhin, V., & Buchleitner, A.
- Venue
- Reports on Progress in Physics
- Publisher
- IOP Publishing
- Published
- 2003-12-04
- Volume
- 67
- Issue
- 1
- Pages
- 45-105
- ISSN
- 0034-4885 (ISSN-L)
- 1361-6633
- OpenAlex
- W3164420190
- Cited by
- 396
- References
- 111
- FWCI
- 8.71
- Type
- journal article
- Language
- en
- Open access
- closed
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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