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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

Neural correlations play a critical role in sensory information coding. They are of two kinds: signal correlations, when neurons have overlapping sensitivities, and noise correlations from network effects and shared noise. In experiments…

Neurons and Cognition · Quantitative Biology 2025-07-03 Gabriel Mahuas , Thomas Buffet , Olivier Marre , Ulisse Ferrari , Thierry Mora

Two familiar notions of correlation are rediscovered as the extreme operating points for distributed synthesis of a discrete memoryless channel, in which a stochastic channel output is generated based on a compressed description of the…

Information Theory · Computer Science 2016-11-18 Paul Cuff

Cross-correlation heterodyne detectors exhibit the potential for suppression of the detection quantum noise below shot noise without use of optical squeezing for capturing weak optical signals in low frequency bands. To understand the…

Quantum Physics · Physics 2022-11-09 Sheng Feng , Kaikai Wu

One major challenge for living cells is the measurement and prediction of signals corrupted by noise. In general, cells need to make decisions based on their compressed representation of noisy, time-varying signals. Strategies for signal…

Quantitative Methods · Quantitative Biology 2023-07-07 Jenny Poulton , Age Tjalma , Lotte Slim , Pieter Rein ten Wolde

The performance of Bayesian detection of Gaussian signals using noisy observations is investigated via the error exponent for the average error probability. Under unknown signal correlation structure or limited processing capability it is…

Information Theory · Computer Science 2009-11-11 Youngchul Sung , Lang Tong , H. Vincent Poor

The strong converse for a coding theorem shows that the optimal asymptotic rate possible with vanishing error cannot be improved by allowing a fixed error. Building on a method introduced by Gu and Effros for centralized coding problems, we…

Information Theory · Computer Science 2019-08-22 Himanshu Tyagi , Shun Watanabe

The estimated accuracy of a classifier is a random quantity with variability. A common practice in supervised machine learning, is thus to test if the estimated accuracy is significantly better than chance level. This method of signal…

Methodology · Statistics 2020-01-28 Jonathan D. Rosenblatt , Yuval Benjamini , Roee Gilron , Roy Mukamel , Jelle J. Goeman

The best developed formulation of closed system quantum theory that handles multiple-time statements, is the consistent (or decoherent) histories approach. The most important weaknesses of the approach is that it gives rise to many…

Quantum Physics · Physics 2014-10-14 Petros Wallden

In Fourier-based medical imaging, sampling below the Nyquist rate results in an underdetermined system, in which linear reconstructions will exhibit artifacts. Another consequence of under-sampling is lower signal to noise ratio (SNR) due…

Computer Vision and Pattern Recognition · Computer Science 2016-10-04 Patrick Virtue , Michael Lustig

This paper presents a counterexample to the optimality conjecture in convex quantum channel optimization proposed by Coutts et al. The conjecture posits that for nuclear norm minimization problems in quantum channel optimization, the dual…

Quantum Physics · Physics 2026-02-03 Jianting Yang

We consider a separation problem where the observation consists of the sum of a high amplitude smooth signal and a low amplitude transient signal. We propose a method for decomposition that relies on solving instances of a `constrained…

Signal Processing · Electrical Eng. & Systems 2020-07-15 Ilker Bayram

Noise is the defining feature of the NISQ era, but it remains unclear if noisy quantum devices are capable of quantum speedups. Quantum supremacy experiments have been a major step forward, but gaps remain between the theory behind these…

Quantum Physics · Physics 2022-03-08 Adam Bouland , Bill Fefferman , Zeph Landau , Yunchao Liu

This paper considers the deconvolution problem in the case where the target signal is multidimensional and no information is known about the noise distribution. More precisely, no assumption is made on the noise distribution and no samples…

Statistics Theory · Mathematics 2021-02-18 Elisabeth Gassiat , Sylvain Le Corff , Luc Lehéricy

With the advent of massive data outputs at a regular rate, admittedly, signal processing technology plays an increasingly key role. Nowadays, signals are not merely restricted to physical sources, they have been extended to digital sources…

Information Theory · Computer Science 2015-07-28 Yi Lu

With the advent of massive data outputs at a regular rate, admittedly, signal processing technology plays an increasingly key role. Nowadays, signals are not merely restricted to physical sources, they have been extended to digital sources…

Information Theory · Computer Science 2018-01-22 Yi Janet Lu

The strong capacity of a particular channel can be interpreted as a sharp limit on the amount of information which can be transmitted reliably over that channel. To evaluate the strong capacity of a particular channel one must prove both…

Quantum Physics · Physics 2011-10-20 Tony Dorlas , Ciara Morgan

A fully general strong converse for channel coding states that when the rate of sending classical information exceeds the capacity of a quantum channel, the probability of correctly decoding goes to zero exponentially in the number of…

Quantum Physics · Physics 2013-05-29 Robert Koenig , Stephanie Wehner

Despite its importance to experimental design, statistical power (the probability that, given a real effect, an experiment will reject the null hypothesis) has largely been ignored by the NLP community. Underpowered experiments make it more…

Computation and Language · Computer Science 2020-10-15 Dallas Card , Peter Henderson , Urvashi Khandelwal , Robin Jia , Kyle Mahowald , Dan Jurafsky

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