Two-dimensional multiphase batch process monitoring based on sparse canonical variate analysis
S Zhang, X Bao - Journal of Process Control, 2022 - Elsevier
Most industrial batch processes involve inherent dynamic characteristics in both within-batch
time direction and batch-wise direction. In order to ensure process safety and improve …
time direction and batch-wise direction. In order to ensure process safety and improve …
Frequency-domain in-vehicle UWB channel modeling
This paper aims to present a simple but robust model characterizing the frequency-
dependent transfer function of an in-vehicle ultrawideband (UWB) channel. A large number …
dependent transfer function of an in-vehicle ultrawideband (UWB) channel. A large number …
Analysis of the Earthʼs magnetic field variations on the basis of a wavelet-based approach
O Mandrikova, I Solovjev, V Geppener… - Digital Signal …, 2013 - Elsevier
In the present paper we will discuss a new wavelet-based approach aimed at processing
and analyzing different features of complex geomagnetic signals. This approach makes it …
and analyzing different features of complex geomagnetic signals. This approach makes it …
Near-optimal moving average estimation at characteristic timescales: An Allan variance approach
A major challenge in moving average (MA) estimation is the selection of an appropriate
averaging window length or timescale over which measurements remain relevant to the …
averaging window length or timescale over which measurements remain relevant to the …
[PDF][PDF] Towards optimal model order selection for autoregressive spectral analysis of mental tasks using genetic algorithm
R Palaniappan - International Journal of Computer Science and …, 2006 - academia.edu
Autoregressive (AR) models for spectral analysis of electroencephalogram (EEG) signals
are advantageous over the classical Fourier transform methods due to their ability to deal …
are advantageous over the classical Fourier transform methods due to their ability to deal …
Batch process monitoring in score space of two-dimensional dynamic principal component analysis (PCA)
Two-dimensional dynamic principal component analysis (2-D-DPCA) is a recent developed
method for two-dimensional (2-D) dynamic batch process monitoring. However, it only …
method for two-dimensional (2-D) dynamic batch process monitoring. However, it only …
[HTML][HTML] Detection in reverberation using space time adaptive prewhiteners
W Li, X Ma, Y Zhu, J Yang, C Hou - The journal of the acoustical society …, 2008 - pubs.aip.org
Detection in reverberation using space time adaptive prewhiteners | The Journal of the
Acoustical Society of America | AIP Publishing Skip to Main Content Umbrella Alt Text Umbrella …
Acoustical Society of America | AIP Publishing Skip to Main Content Umbrella Alt Text Umbrella …
Two-dimensional ARMA model order determination
MS Sadabadi, M Shafiee, M Karrari - ISA transactions, 2009 - Elsevier
Determination of the order of a model is the key first step towards modeling any dynamic
systems, particularly two-dimensional processes. In this paper, a new method for two …
systems, particularly two-dimensional processes. In this paper, a new method for two …
Measurement and modelling of an UWB channel at hospital
L Hentila, A Taparungssanagorn… - … Conference on Ultra …, 2005 - ieeexplore.ieee.org
This paper describes the results of an ultra wideband (UWB) channel measurements and
modelling from 3.1 to 6.0 GHz carried out at the Oulu University Hospital. Mainly line-of-sight …
modelling from 3.1 to 6.0 GHz carried out at the Oulu University Hospital. Mainly line-of-sight …
A new Levinson–Durbin based 2-D AR model parameter estimation method
M Zeinali, M Shafiee - Multidimensional Systems and Signal Processing, 2016 - Springer
This paper presents a new method for estimating the parameters of quarterplane two
dimensional (2-D) autoregressive model based on the Levinson–Durbin algorithm. To …
dimensional (2-D) autoregressive model based on the Levinson–Durbin algorithm. To …