An enhanced set-membership evolving participatory learning with kernel recursive least squares applied to thermal modeling of power transformers
A factor that directly impacts the lifespan of a power transformer is the hot-spot temperature,
and its monitoring is vital to prevent faults, reduce costs, keep the safety, and provide a …
and its monitoring is vital to prevent faults, reduce costs, keep the safety, and provide a …
Power transformers thermal modeling using an enhanced set-membership multivariable Gaussian evolving fuzzy system
MVG da Rocha, MB Hell, KSTR Alves… - Electric Power Systems …, 2021 - Elsevier
In this work we present two new models based on Evolving Multivariable Gaussian
approach and on the Set-Membership/Enhanced Set-Membership adaptive filtering …
approach and on the Set-Membership/Enhanced Set-Membership adaptive filtering …
Set-membership type-1 fuzzy logic system applied to fault classification in a switch machine
EP de Aguiar, FMA Nogueira… - IEEE Transactions …, 2017 - ieeexplore.ieee.org
This paper focuses on the classification of faults in an electromechanical switch machine,
which is an equipment used for handling railroad switches. In this paper, we introduce the …
which is an equipment used for handling railroad switches. In this paper, we introduce the …
An enhanced set-membership PNLMS algorithm with a correntropy induced metric constraint for acoustic channel estimation
Z Jin, Y Li, Y Wang - Entropy, 2017 - mdpi.com
In this paper, a sparse set-membership proportionate normalized least mean square (SM-
PNLMS) algorithm integrated with a correntropy induced metric (CIM) penalty is proposed …
PNLMS) algorithm integrated with a correntropy induced metric (CIM) penalty is proposed …
A new model to distinguish railhead defects based on set-membership type-2 fuzzy logic system
EP de Aguiar, TE Fernandes, FMA Nogueira… - International Journal of …, 2021 - Springer
This paper focuses on the new model for the classification of railhead defects, through
images acquired by a rail inspection vehicle. In this regard, we discuss the use of set …
images acquired by a rail inspection vehicle. In this regard, we discuss the use of set …
An improved set-membership proportionate adaptive algorithm for a block-sparse system
Z Jin, Y Li, J Liu - Symmetry, 2018 - mdpi.com
In this paper, an improved set-membership proportionate normalized least mean square
(SM-PNLMS) algorithm is proposed for block-sparse systems. The proposed algorithm …
(SM-PNLMS) algorithm is proposed for block-sparse systems. The proposed algorithm …
Distributed low-rank adaptive estimation algorithms based on alternating optimization
S Xu, RC de Lamare, HV Poor - Signal Processing, 2018 - Elsevier
This paper presents a novel distributed low-rank scheme and adaptive algorithms for
distributed estimation over wireless networks. The proposed distributed scheme is based on …
distributed estimation over wireless networks. The proposed distributed scheme is based on …
Stochastic optimization combined with type-2 fuzzy logic system for the classification of trends in hot boxes and hot wheels
LD Fonseca, E Pestana de Aguiar - International Journal of Fuzzy Systems, 2022 - Springer
Hot box and hot wheel threaten any rail operation, increasing fatigue and wear processes
which result in failures, costly train stoppages and derailments. For this reason, detectors …
which result in failures, costly train stoppages and derailments. For this reason, detectors …
A survey on active noise control techniques--Part I: Linear systems
Active noise control (ANC) is an effective way for reducing the noise level in electroacoustic
or electromechanical systems. Since its first introduction in 1936, this approach has been …
or electromechanical systems. Since its first introduction in 1936, this approach has been …
Transient analysis of the set-membership LMS algorithm
NN Siqueira, TP Ferreira, LC Resende… - IEEE …, 2021 - ieeexplore.ieee.org
Adaptive filtering algorithms, which adopt the set-membership strategy, are able to attain
good steady-state performance with low computational burden. In general, such advantages …
good steady-state performance with low computational burden. In general, such advantages …