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A study on the correlation between annual noise exposure (ANE) and auditory attention, as well as hearing loss in military personnel.
Work
December 2024
Health Research Center, Lifestyle Institute, Baqiyatallah University of Medical Sciences, Tehran, Iran.
Background: The accurate processing of auditory signals holds significant importance in military occupations and can be adversely affected by exposure to noise.
Objectives: This study investigates the correlation between annual noise exposure (ANE) and military personnel's auditory attention and hearing loss.
Methods: This study assessed 220 military personnel serving in an armored brigade unit.
Preprocessing choices for P3 analyses with mobile EEG: A systematic literature review and interactive exploration.
Psychophysiology
January 2025
Neuropsychology Lab, Department of Psychology, Carl von Ossietzky Universität Oldenburg, Oldenburg, Germany.
Preprocessing is necessary to extract meaningful results from electroencephalography (EEG) data. With many possible preprocessing choices, their impact on outcomes is fundamental. While previous studies have explored the effects of preprocessing on stationary EEG data, this research delves into mobile EEG, where complex processing is necessary to address motion artifacts.
View Article and Find Full Text PDFSeparable synchronous auxiliary model adaptive momentum estimation strategy for a time-varying system with colored noise from on-line measurements.
ISA Trans
December 2024
College of Automation and Electronic Engineering, Qingdao University of Science and Technology, Qingdao 266061, China. Electronic address:
The primary focus of this article is to explore parameter estimation for time-varying systems affected by colored noise. Based on the attributes of the time-varying system with colored noise under investigation, the original system is separated and two different subsystems are reconstructed. To address the influence of the hidden variables in the system and the time-varying noise signal, we introduce auxiliary models into the reconstructed systems to achieve the separation and synchronization estimation of the time-varying parameters within the system.
View Article and Find Full Text PDFAccurate numerical simulations of open quantum systems using spectral tensor trains.
J Chem Phys
December 2024
Department of Chemistry, University of Colorado Boulder, Boulder, Colorado 80309, USA.
Decoherence between qubits is a major bottleneck in quantum computations. Decoherence results from intrinsic quantum and thermal fluctuations as well as noise in the external fields that perform the measurement and preparation processes. With prescribed colored noise spectra for intrinsic and extrinsic noise, we present a numerical method, Quantum Accelerated Stochastic Propagator Evaluation (Q-ASPEN), to solve the time-dependent noise-averaged reduced density matrix in the presence of intrinsic and extrinsic noise.
View Article and Find Full Text PDFIt has been an open question in deep learning if fault-tolerant computation is possible: can arbitrarily reliable computation be achieved using only unreliable neurons? In the grid cells of the mammalian cortex, analog error correction codes have been observed to protect states against neural spiking noise, but their role in information processing is unclear. Here, we use these biological error correction codes to develop a universal fault-tolerant neural network that achieves reliable computation if the faultiness of each neuron lies below a sharp threshold; remarkably, we find that noisy biological neurons fall below this threshold. The discovery of a phase transition from faulty to fault-tolerant neural computation suggests a mechanism for reliable computation in the cortex and opens a path towards understanding noisy analog systems relevant to artificial intelligence and neuromorphic computing.
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