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Some systems cannot be predicted by classical theories and it is required the development of combined deterministic and stochastic theories that make used of noise for dynamical prediction. Noise is not always an interfering signal which…

Adaptation and Self-Organizing Systems · Physics 2019-05-14 Alexandra Pinto Castellanos

Stochastic resonance holds much promise for the detection of weak signals in the presence of relatively loud noise. Following the discovery of nondynamical and of aperiodic stochastic resonance, it was recently shown that the phenomenon can…

Condensed Matter · Physics 2009-10-31 Redouane Fakir

Stochastic resonance is a non-linear phenomenon, in which the sensitivity of signal detectors can be enhanced by adding random noise to the detector input. Here, we demonstrate that noise can also improve the information flux in recurrent…

Neurons and Cognition · Quantitative Biology 2018-11-30 Patrick Krauss , Karin Prebeck , Achim Schilling , Claus Metzner

Varied sensory systems use noise in order to enhance detection of weak signals. It has been conjectured in the literature that this effect, known as stochastic resonance, may take place in central cognitive processes such as the memory…

Neurons and Cognition · Quantitative Biology 2007-05-23 Julien Mayor , Wulfram Gerstner

Can noise be beneficial to machine-learning prediction of chaotic systems? Utilizing reservoir computers as a paradigm, we find that injecting noise to the training data can induce a stochastic resonance with significant benefits to both…

Machine Learning · Computer Science 2022-11-21 Zheng-Meng Zhai , Ling-Wei Kong , Ying-Cheng Lai

Many modern applications of the artificial neural networks ensue large number of layers making traditional digital implementations increasingly complex. Optical neural networks offer parallel processing at high bandwidth, but have the…

Neural and Evolutionary Computing · Computer Science 2022-08-24 Egor Manuylovich , Diego Argüello Ron , Morteza Kamalian-Kopae , Sergei Turitsyn

The paradigm of stochastic resonance (SR)---the idea that signal detection and transmission may benefit from noise---has met with great interest in both physics and the neurosciences. We investigate here the consequences of reducing the…

Biological Physics · Physics 2009-11-06 Hans E. Plesser , Theo Geisel

Signal analysis and classification is fraught with high levels of noise and perturbation. Computer-vision-based deep learning models applied to spectrograms have proven useful in the field of signal classification and detection; however,…

Machine Learning · Computer Science 2024-09-04 Joel Brogan , Olivera Kotevska , Anibely Torres , Sumit Jha , Mark Adams

Stochastic resonance (SR) - a counter-intuitive phenomenon in which the signal due to a weak periodic force in a nonlinear system can be {\it enhanced} by the addition of external noise - is reviewed. A theoretical approach based on linear…

It is by now established that, remarkably, the addition of noise to a nonlinear system may sometimes facilitate, rather than hamper the detection of weak signals. This phenomenon, usually referred to as stochastic resonance, was originally…

Condensed Matter · Physics 2009-10-31 Redouane Fakir

Stochastic Resonance (SR) describes a phenomenon where an additive noise (stochastic carrier-wave) enhances the signal transmission in a nonlinear system. In the nervous system, nonlinear properties are present from the level of single ion…

Signal Processing · Electrical Eng. & Systems 2023-10-09 Weronika Potok , Onno van der Groen , Sahana Sivachelvam , Marc Bächinger , Flavio Fröhlich , Laszlo B. Kish , Nicole Wenderoth

Stochastic resonance shows that under some circumstances noise can enhance the response of a system to a periodic force. While this effect has been extensively investigated theoretically and demonstrated experimentally in classical systems,…

Quantum Physics · Physics 2009-11-06 S. F. Huelga , M. B. Plenio

Noise is an inherent part of neuronal dynamics, and thus of the brain. It can be observed in neuronal activity at different spatiotemporal scales, including in neuronal membrane potentials, local field potentials, electroencephalography,…

Neurons and Cognition · Quantitative Biology 2019-01-03 Daqing Guo , Matjaz Perc , Tiejun Liu , Dezhong Yao

Stochastic resonance is a phenomenon in which noise enhances the response of a system to an input signal. The brain is an example of a system that has to detect and transmit signals in a noisy environment, suggesting that it is a good…

Neurons and Cognition · Quantitative Biology 2017-10-16 Bertha Vázquez-Rodríguez , Andrea Avena-Koenigsberger , Olaf Sporns , Alessandra Griffa , Patric Hagmann , Hernán Larralde

Spectrum sensing is essential in cognitive radio to enable dynamic spectrum access. In many scenarios, primary user signal must be detected reliably in low signal-to-noise ratio (SNR) regime under required sensing time. We propose to use…

Information Theory · Computer Science 2009-06-04 Kun Zheng , Husheng Li , Seddik M. Djouadi , Jun Wang

Chaos and Noise are ubiquitous in the Brain. Inspired by the chaotic firing of neurons and the constructive role of noise in neuronal models, we for the first time connect chaos, noise and learning. In this paper, we demonstrate Stochastic…

Neurons and Cognition · Quantitative Biology 2021-03-10 Harikrishnan NB , Nithin Nagaraj

Stochastic resonance (SR) is a coherence enhancement effect due to noise that occurs in periodically-driven nonlinear dynamical systems. A very broad range of physical and biological systems present this effect such as climate change,…

Pattern Formation and Solitons · Physics 2021-06-08 Adriano A. Batista , A. A. Lisboa de Souza , Raoni S. N. Moreira

This study explores stochastic resonance (SR) in a Schmitt trigger circuit and its application to weak signal detection. SR, a phenomenon where noise synchronizes with weak signals to enhance detectability, was demonstrated using a…

Signal Processing · Electrical Eng. & Systems 2025-01-22 Yoonkang Kim , Donghyeok Seo

Stochastic resonance is a phenomenon where a noise of appropriate intensity enhances the input signal strength. In this work, by employing the recently developed convex optimization methods in the context of dynamical systems and stochastic…

Dynamical Systems · Mathematics 2023-09-22 Minjae Cho

In this paper, we adapt Recurrent Neural Networks with Stochastic Layers, which are the state-of-the-art for generating text, music and speech, to the problem of acoustic novelty detection. By integrating uncertainty into the hidden states,…

Audio and Speech Processing · Electrical Eng. & Systems 2019-04-24 Duong Nguyen , Oliver S. Kirsebom , Fábio Frazão , Ronan Fablet , Stan Matwin
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