20 papers · ranked by Valyu relevance
He Wen, Mohamad Sofian Abu Talip, Mohamadariff Othman, S. M. Kayser Azam + 5 more
This paper comprehensively reviews advanced signal processing methods for partial discharge (PD) analysis, covering traditional time-frequency techniques, wavelet transform, Hilbert-Huang transform, and artificial intelligence-based methods. This paper critically examines the principles, advantages, limitations, and…
Chongjun Huang, Wenbo Cai, Dongxiao Pang, Yan Yang + 7 more
During drilling operations, mud continuous-wave signals suffer severe distortion at the surface receiver due to dynamic and complex background noise. Traditional noise cancelation methods face limitations in effectiveness and generalization. To address this, this paper proposes a particle swarm optimization (PSO)-based…
Stefan Ciba
This work introduces a robust single-channel inverse filter for dereverberation of non-ideal recordings, validated on real audio. The developed method focuses on the calculation and modification of a discrete impulse response in order to filter the characteristics from a known digital single channel recording setup and…
Janet M. Baker, Peter Cariani
Waves are fundamental. In our view, waves in the brain may constitute and drive organized neural activity patterns on individual neural and population levels. Their interactions follow basic physical principles. Taking a comprehensive, temporal and spatiotemporal perspective, we endeavor to explain multiple brain…
Vimalajeewa, Dixon, Muller, Ursula U. + 2 more
—Stochastic resonance (SR), a phenomenon originally introduced in climate modeling, enhances signal detection by leveraging optimal noise levels within non-linear systems. Traditional SR techniques, mainly based on single-threshold detectors, are limited to signals whose behavior does not depend on time. Often large…
Jordan Tschida, Matthew Yohe, Edward Kane, Gavin Jager + 9 more
Time series classification (TSC) of biological signals has progressed from handcrafted, modality-specific approaches to deep architectures capable of representing the diverse waveform structures of underlying physiological processes (i.e., morphology). This review introduces a unified morphology--modality framework…
Abdelouahad Achmamad, Atman Jbari, Nourdin Yaakoubi, Georg Fischer + 1 more
Surface electromyography (sEMG) signal processing has been the subject of many studies for many years now. These studies had the main objective of providing pertinent information to medical experts to help them make correct interpretations and medical diagnoses. Beyond its clinical relevance, sEMG plays a critical role…
André Lopes, Luís Fernandes, Paulo Chaves, Richard J. J. Povinelli + 2 more
This work aimed to develop and evaluate a real-time communication channel detection system in the Very High Frequency (VHF) band using software-defined radio (SDR). For this purpose, an FFT based spectral analyzer with 32,768 points was designed, capable of converting signals from the time domain to the frequency…
Norbert Ádám, Dávid Val’ko, Zoltán Balogh, Branislav Madoš + 1 more
This paper explores filtration techniques for processing ECG signals, focusing on the evaluation of effective denoising methods. We highlight the effectiveness of Stationary Wavelet Transform as the most suitable approach for denoising ECG signals while preserving critical cardiac features. Stationary Wavelet…
Nazila Ahmadi Daryakenari, Seyed Kamaleddin Setaredan
Schizophrenia (SZ) is a chronic and complex mental disorder associated with neurobiological deficits. The complexity and heterogeneity of schizophrenia symptoms pose challenges for objective diagnosis, which is currently based on behavioral and clinical manifestations. Furthermore, other psychiatric disorders such as…
J.C. Couchman, Phillip Stanley‐Marbell
—A common assumption in signal processing is that underlying data numerically conforms to a Gaussian distribution. It is commonly utilized in signal processing to describe unknown additive noise in a system and is often justified by citing the central limit theorem for sums of random variables, although the central…
Priyalakshmi Sheela, Indrakshi Dey
Wavelet denoising suppresses nonstationary, impulsive, and interference-like disturbances in communication signals, but its effectiveness depends on jointly selecting the transform family, mother wavelet, decomposition level, thresholding rule, and shrinkage function. This review synthesises studies published during…
Aonan He, Xi Wang, Jiangwei Yu, Xiaojia Wang + 6 more
Electroencephalography (EEG) serves as a fundamental tool in modern neurology, cognitive neuroscience, and brain-computer interfaces, but its practical application is often compromised by artifacts. Physiological artifacts are particularly intractable due to overlapping spectral features with neural signals, hindering…
Giulio Ruffini
Hierarchical encoding is a structural element of the Free Energy Principle and related information-centric accounts of brain function, but a concrete circuit-level mechanism for it remains elusive. Here we examine Hierarchical Amplitude Modulation (HAM). In this computationally grounded scheme, information is encoded…
Adam Hockley, Connor G Gallimore, Jordan P Hamm, Manuel S Malmierca
Context modulates neural processing of sensory stimuli. Neural responses are suppressed to stimuli that are typical in their context and augmented to stimuli that deviate from their context. The latter has been conceptualized as a “prediction error”, which can serve to enhance the salience, direct attention, or support…
Lily Cassandra Paulick, Helia Relaño-Iborra, Torsten Dau
Spectro-temporal modulation (STM) sensitivity has been proposed as a sensitive marker of speech intelligibility in challenging listening conditions, yet the underlying auditory mechanisms involved in STM detection remain incompletely understood. The present study measured STM detection thresholds in young…
Kono, Yohei, Tajima, Yoshiyuki
Extracting pulsive temporal patterns from a small dataset without their repetition or singularity shows significant importance in manufacturing applications but does not sufficiently attract scientific attention. We propose to quantify how long temporal patterns appear without relying on their repetition or…
Gavin M. Bidelman, Zara Eisenhut, Lucy Borowski, Rose Rizzi + 1 more
Speech perception requires that listeners classify sensory information into smaller groupings while also coping with noise that often corrupts the speech signal. The strength of categorization and speech-in-noise (SIN) abilities show stark individual differences. Some listeners perceive speech sounds in a gradient…
Onnipekka V. Varis, Ilkka A. Muukkonen, Patrik A. Wikman
The human auditory system represents sounds at multiple levels, from low-level acoustic features to abstract category- and object-level information. Although selective attention enables listening in complex natural soundscapes, it remains unclear which representational levels are modulated by attention and how this…
Authors not listed
The process of label selection holds significant importance in the field of electrochemical biosensors, as it directly impacts the achievement of low detection limits and a wide dynamic range. To attain these objectives, it is necessary to take into account several aspects, including low electroactive potential, high…