q-State Space Least Mean Family of Algorithms
Sign Up to like & getrecommendations! Published in 2018 at "Circuits, Systems, and Signal Processing"
DOI: 10.1007/s00034-017-0569-7
Abstract: It is generally known that model-based estimation algorithms (such as Kalman filter and its family) perform better than the non-model-based algorithms [such as least mean square (LMS), recursive least squares] due to extra information available… read more here.
Keywords: state; state space; algorithms; space least ... See more keywords
Incorporating Nonparametric Knowledge to the Least Mean Square Adaptive Filter
Sign Up to like & getrecommendations! Published in 2019 at "Circuits, Systems, and Signal Processing"
DOI: 10.1007/s00034-018-0954-x
Abstract: In the framework of the maximum a posteriori estimation, the present study proposes the nonparametric probabilistic least mean square (NPLMS) adaptive filter for the estimation of an unknown parameter vector from noisy data. The NPLMS… read more here.
Keywords: least mean; adaptive filter; mean square; incorporating nonparametric ... See more keywords
Communication-Reducing Algorithm of Distributed Least Mean Square Algorithm with Neighbor-Partial Diffusion
Sign Up to like & getrecommendations! Published in 2020 at "Circuits, Systems, and Signal Processing"
DOI: 10.1007/s00034-020-01374-1
Abstract: With the development of distributed algorithms, many researchers are committed to the goal of maintaining the long-term stability of the network by reducing the communication cost. However, many algorithms that lessen communication costs often result… read more here.
Keywords: partial diffusion; communication; neighbor partial; mean square ... See more keywords
Logarithmic reweighting nonnegative least mean square algorithm
Sign Up to like & getrecommendations! Published in 2018 at "Signal, Image and Video Processing"
DOI: 10.1007/s11760-017-1129-0
Abstract: System identification based on least mean square (LMS) adaptive filters is effective due to their simplicity and robustness. Inherent physical characteristic of intended system usually make nonnegativity constraint desirable. In other words, imposing nonnegativity constraint… read more here.
Keywords: nonnegative least; mean square; logarithmic reweighting; least mean ... See more keywords
Noise cancellation of a multi-reference full-wave magnetic resonance sounding signal based on a modified sigmoid variable step size least mean square algorithm
Sign Up to like & getrecommendations! Published in 2017 at "Journal of Central South University"
DOI: 10.1007/s11771-017-3492-y
Abstract: Nano-volt magnetic resonance sounding (MRS) signals are sufficiently weak so that during the actual measurement, they are affected by environmental electromagnetic noise, leading to inaccuracy of the extracted characteristic parameters and hindering effective inverse interpretation.… read more here.
Keywords: multi reference; reference; noise; least mean ... See more keywords
Least Mean Squares Adaptive Algorithms Optimization for Fetal Phonocardiogram Extraction
Sign Up to like & getrecommendations! Published in 2018 at "IFAC-PapersOnLine"
DOI: 10.1016/j.ifacol.2018.07.130
Abstract: Abstract The paper deals with extraction of fetal phonocardiogram (fPCG) from the abdominal signal mixture by using adaptive filters based on Least Mean Squares (LMS) algorithms. Optimal setting of the filter parameters is a vital… read more here.
Keywords: adaptive algorithms; squares adaptive; mean squares; algorithms optimization ... See more keywords
Functional link artificial neural network filter based on the q-gradient for nonlinear active noise control
Sign Up to like & getrecommendations! Published in 2018 at "Journal of Sound and Vibration"
DOI: 10.1016/j.jsv.2018.08.015
Abstract: Abstract As one of the most commonly used nonlinear active noise control (NANC) algorithms, the filtered-s least mean square (FsLMS) algorithm outperforms the conventional filtered-x least mean square (FxLMS) algorithm when the primary path has… read more here.
Keywords: nonlinear active; active noise; filtered least; noise control ... See more keywords
A generic FPGA-based hardware architecture for recursive least mean p-power extreme learning machine
Sign Up to like & getrecommendations! Published in 2021 at "Neurocomputing"
DOI: 10.1016/j.neucom.2021.05.069
Abstract: Abstract Recursive least mean p-power extreme learning machine (RLMP-ELM) is a newly proposed online machine learning algorithm and is able to provide a robust online prediction of the datasets with noises of different statistics. To… read more here.
Keywords: recursive least; least mean; hardware architecture; machine ... See more keywords
Affine Projection Algorithm Based on Least Mean Fourth Algorithm for System Identification
Sign Up to like & getrecommendations! Published in 2020 at "IEEE Access"
DOI: 10.1109/access.2020.2966038
Abstract: In the field of signal processing such as system identification, the affine projection algorithm (APA) is extensively implemented. However, running such algorithms in a non-Gaussian scenario may degrade its performance, since the second-order moment cannot… read more here.
Keywords: least mean; affine projection; mean fourth; system identification ... See more keywords
Robust Incremental Least Mean Square Algorithm With Dynamic Combiner
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Access"
DOI: 10.1109/access.2022.3192018
Abstract: In distributed wireless networks, the adaptation process depends on the information being shared between various nodes. The global minimum, is therefore, likely to be affected when the information shared between the nodes gets corrupted. This… read more here.
Keywords: information; mean square; square; robust incremental ... See more keywords
Transient Analysis of the Block Least Mean Squares Algorithm
Sign Up to like & getrecommendations! Published in 2021 at "IEEE Communications Letters"
DOI: 10.1109/lcomm.2020.3026610
Abstract: It is known that adaptive filtering algorithms may tackle relevant communication tasks. In order to reduce the adaptation rate, the least mean squares algorithm and its normalized version may be implemented in a block manner,… read more here.
Keywords: least mean; mean squares; block; squares algorithm ... See more keywords