Spare optimistic based on improved ADMM and the minimum entropy de-convolution for the early weak fault diagnosis of bearings in marine systems

Y Gao, M Karimi, AA Kudreyko, W Song - ISA transactions, 2018 - Elsevier
In the marine systems, engines represent the most important part of ships, the probability of
the bearings fault is the highest in the engines, so in the bearing vibration analysis, early …

Direction-of-arrival and power spectral density estimation using a single directional microphone and group-sparse optimization

E Tengan, T Dietzen, F Elvander… - EURASIP Journal on …, 2023 - Springer
In this paper, two approaches are proposed for estimating the direction of arrival (DOA) and
power spectral density (PSD) of stationary point sources by using a single, rotating …

Group-sparse regression using the covariance fitting criterion

T Kronvall, SI Adalbjörnsson, S Nadig, A Jakobsson - Signal Processing, 2017 - Elsevier
In this work, we present a novel formulation for efficient estimation of group-sparse
regression problems. By relaxing a covariance fitting criteria commonly used in array signal …

Harmonic differences method for robust fundamental frequency detection in wideband and narrowband speech signals

C Parlak, Y Altun - Mathematical Problems in Engineering, 2021 - Wiley Online Library
In this article, a novel pitch determination algorithm based on harmonic differences method
(HDM) is proposed. Most of the algorithms today rely on autocorrelation, cepstrum, and lastly …

Off-grid fundamental frequency estimation

J Swärd, H Li, A Jakobsson - IEEE/ACM Transactions on Audio …, 2017 - ieeexplore.ieee.org
In this paper, we propose a gridless method for estimating an unknown number of
fundamental frequencies. Starting with a conventional dictionary matrix, containing sets of …

Hyperparameter selection for group-sparse regression: A probabilistic approach

T Kronvall, A Jakobsson - Signal Processing, 2018 - Elsevier
This work analyzes the effects on support recovery for different choices of the hyper-or
regularization parameter in LASSO-like sparse and group-sparse regression problems. The …

Online estimation of multiple harmonic signals

F Elvander, J Swärd… - IEEE/ACM Transactions on …, 2016 - ieeexplore.ieee.org
In this paper, we propose a time-recursive multipitch estimation algorithm using a sparse
reconstruction framework, assuming that only a few pitches from a large set of candidates …

Using optimal transport for estimating inharmonic pitch signals

F Elvander, SI Adalbjörnsson… - … , Speech and Signal …, 2017 - ieeexplore.ieee.org
In this work, we propose a novel multi-pitch estimation technique that is robust with respect
to the inharmonicity commonly occurring in many applications. The method does not require …

Domain knowledge embedding regularization neural networks for workload prediction and analysis in cloud computing

L Li, M Feng, L Jin, S Chen, L Ma… - Research Anthology on …, 2021 - igi-global.com
Online services are now commonly deployed via cloud computing based on Infrastructure as
a Service (IaaS) to Platform-as-a-Service (PaaS) and Software-as-a-Service (SaaS) …

Estimation of fundamental frequencies in stereophonic music mixtures

MW Hansen, JR Jensen… - IEEE/ACM Transactions …, 2018 - ieeexplore.ieee.org
In this paper, a method for multi-pitch estimation of stereophonic mixtures of harmonic
signals, eg, instrument recordings, is presented. The proposed method is based on a signal …