Results 71 to 80 of about 44,498 (172)

THEORY OF DIGITAL FILTER BANKS REALIZED VIA MULTIVARIATE EMPIRICAL MODE DECOMPOSITION [PDF]

Advances in Adaptive Data Analysis, 2014
Undecimated and decimated multivariate empirical mode decomposition filter banks (MEMDFBs) are introduced in order to incorporate MEMD equipped with downsampling into any arbitrary tree structure and provide flexibility in the choice of frequency bands.
MIN-SUNG KOH, DANILO P. MANDIC, ANTHONY G. CONSTANTINIDES   +2 more
openaire   +1 more source

Scalable Rejection Sampling for Bayesian Hierarchical Models [PDF]

, 2014
Bayesian hierarchical modeling is a popular approach to capturing unobserved heterogeneity across individual units. However, standard estimation methods such as Markov chain Monte Carlo (MCMC) can be impracticable for modeling outcomes from a large ...
Braun, Michael, Damien, Paul
core  

The Linearly Independent Non Orthogonal yet Energy Preserving (LINOEP) vectors [PDF]

, 2014
It is well known that, in any inner product space, a set of linearly independent (LI) vectors can be transformed to a set of orthogonal vectors, spanning the same space, by the Gram-Schmidt Orthogonalization Method (GSOM).
Joshi, S. D., Patney, R. K., Saha, Kaushik, Singh, Pushpendra   +3 more
core  

Analysis of EEG via Multivariate Empirical Mode Decomposition for Depth of Anesthesia Based on Sample Entropy

Entropy, 2013
In monitoring the depth of anesthesia (DOA), the electroencephalography (EEG) signals of patients have been utilized during surgeries to diagnose their level of consciousness.
Jiann-Shing Shieh, Maysam F. Abbod, Tzu-Yu Lin, Cheng-Wei Lu, Shou-Zhen Fan, Qin Wei, Quan Liu   +6 more
doaj   +1 more source

Multiclass classification of imagined speech EEG using noise-assisted multivariate empirical mode decomposition and multireceptive field convolutional neural network. [PDF]

Front Hum Neurosci, 2023
Park HJ, Lee B.
europepmc   +1 more source

Trivariate Empirical Mode Decomposition via Convex Optimization for Rolling Bearing Condition Identification

Sensors, 2018
As a multichannel signal processing method based on data-driven, multivariate empirical mode decomposition (MEMD) has attracted much attention due to its potential ability in self-adaption and multi-scale decomposition for multivariate data.
Yong Lv, Houzhuang Zhang, Cancan Yi
doaj   +1 more source

Intelligent Monitoring System Based on Noise-Assisted Multivariate Empirical Mode Decomposition Feature Extraction and Neural Networks. [PDF]

Comput Intell Neurosci, 2022
Zhao LF, Siahpour S, Haeri Yazdi MR, Ayati M, Zhao TY.   +4 more
europepmc   +1 more source

Extracting the Italian output gap: a Bayesian approach [PDF]

, 2014
During the last decades particular effort has been directed towards understanding and predicting the relevant state of the business cycle with the objective of decomposing permanent shocks from those having only a transitory impact on real output.
Bernardi, Mauro, Di Ruggiero, Antonio
core   +1 more source

A nested factor model for non-linear dependences in stock returns

, 2013
The aim of our work is to propose a natural framework to account for all the empirically known properties of the multivariate distribution of stock returns. We define and study a "nested factor model", where the linear factors part is standard, but where
Bouchaud, Jean-Philippe, Chicheportiche, Rémy   +1 more
core   +1 more source

Research on rotor fault diagnosis technology of three-phase asynchronous motor based on NA-MEMD mutual information and SVM

Measurement + Control
Aiming at the problem of mode aliasing in the adaptive decomposition of nonlinear and non-stationary current signals generated by three-phase asynchronous motor faults, and the fault features contained in signals collected by a single sensor can not be ...
Hui Ali, Yu Jie, Lu Weiqiang
doaj   +1 more source