Stochastic identification of crsd models from arma representations or covariances

2005 ◽  
pp. 294-308
Author(s):  
Fabrice J. Clara ◽  
Leonard M. Silverman
Keyword(s):  
Stochastic Identification ◽  
Arma Representations

scholarly journals Stochastic Identification of Stability of Competitive Interactions in Ecosystems

PLoS ONE ◽  
2016 ◽  
Vol 11 (5) ◽  
pp. e0155023
Author(s):  
Marek Vach ◽  
Pavla Vachová
Keyword(s):  
Competitive Interactions ◽  
Stochastic Identification

scholarly journals Output-Only Identification of System Parameters from Noisy Measurements by Multiwavelet Denoising

2014 ◽  
Vol 6 ◽  
pp. 218328 ◽  
Author(s):  
O. Al-Gahtani ◽  
M. El-Gebeily ◽  
Y. Khulief
Keyword(s):  
Wavelet Transforms ◽  
Model Identification ◽  
Subspace Identification ◽  
Measuring Devices ◽  
Noisy Output ◽  
Output Only ◽  
Modal Values ◽  
Noisy Measurements ◽  
Stochastic Identification ◽  
Wavelet Methods

In this paper we estimate the parameters of a multidimensional system from a record of noisy output measurements by using a multiwavelet denoising technique. In this output-only identification scheme, we extend wavelet denoising methods to the multiwavelet case. After the noise has been removed from the output records by wavelet methods, either full model identification or deterministic subspace identification can be performed. In the former case, full information on the system such as modal values and shapes becomes available by postprocessing. In the latter case, the observable modal values of the system as well as modal shapes at the sensor locations can be extracted from the identified parameters. Additionally, we discuss the requirements on the measuring devices to be compatible with wavelet transforms of a particular type. The validity and merit of the developed scheme are illustrated by examples of numerically simulated and experimentally measured signals, including comparisons with stochastic identification methods.

scholarly journals Physical Context Detection using Wearable Wireless Sensor Networks

2008 ◽  
Vol 4 (3) ◽  
pp. 191 ◽  
Author(s):  
Muhannad Quwaider ◽  
Subir Biswas
Keyword(s):  
Markov Model ◽  
Hidden Markov Model ◽  
Hidden Markov ◽  
Human Subjects ◽  
Real Life ◽  
Sensor Data ◽  
Physical Context ◽  
Significant Extension ◽  
The Individual ◽  
Stochastic Identification

This paper presents the architecture of a wearable sensor network and a Hidden Markov Model (HMM) processingframework for stochastic identification of body postures andphysical contexts. The key idea is to collect multi-modal sensor data from strategically placed wireless sensors over a human subject’s body segments, and to process that using HMM in order to identify the subject’s instantaneous physical context. The key contribution of the proposed multi-modal approach is a significant extension of traditional uni-modal accelerometry in which only the individual body segment movements, without their relative proximities and orientation modalities, is used for physical context identification. Through real-life experiments with body mounted sensors it is demonstrated that while the unimodal accelerometry can be used for differentiating activityintensive postures such as walking and running, they are not effective for identification and differentiation between lowactivity postures such as sitting, standing, lying down, etc. In the proposed system, three sensor modalities namely acceleration, relative proximity and orientation are used for context identification through Hidden Markov Model (HMM) based stochastic processing. Controlled experiments using human subjects are carried out for evaluating the accuracy of the HMMidentified postures compared to a naïve threshold based mechanism over different human subjects.

Sequential stochastic identification of myocardial parameters

1968 ◽  
Vol 2 (1-2) ◽  
pp. 139-144 ◽  
Author(s):  
H. Stephen Schloss
Keyword(s):  
Stochastic Identification

Stochastic identification and digital control of a heat exchanger: a simulation test case

1984 ◽  
Vol 318 (1) ◽  
pp. 29-56 ◽  
Author(s):  
Sergio Bittanti ◽  
Fabio Romeo ◽  
Riccardo Scattolini
Keyword(s):  
Heat Exchanger ◽  
Digital Control ◽  
Test Case ◽  
Simulation Test ◽  
Stochastic Identification
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