Two-dimensional model-based power spectrum estimation for nonextendible correlation bisequences

1997 ◽  
Vol 16 (2) ◽  
pp. 141-163 ◽  
Author(s):  
K. J. Boo ◽  
N. K. Bose
Keyword(s):  
Power Spectrum ◽  
Spectrum Estimation ◽  
Two Dimensional ◽  
Dimensional Model ◽  
Power Spectrum Estimation ◽  
Model Based ◽  
Two Dimensional Model

The Power Spectrum Estimation of the AR Model Based on Motor Imagery EEG

2013 ◽  
Vol 706-708 ◽  
pp. 1923-1927 ◽  
Author(s):  
Li Zhao ◽  
Yang He
Keyword(s):  
Power Spectrum ◽  
Motor Imagery ◽  
Ar Model ◽  
Spectrum Estimation ◽  
Power Spectrum Estimation ◽  
Estimation Algorithms ◽  
Model Based

This paper uses three common AR model power spectrum estimation algorithms which are the Yule-Walker method, the burg method and the improved covariance method. Taking Matlab as a tool, the corresponding algorithms are used to carry out the power spectrum estimation of motor imagery EEG, the relationships and distinctions between the spectrum charts are compared in order to find the relatively appropriate algorithm for analyzing the EEG, which aims at providing a theoretical guidance for processing the motor imagery EEG and laying a foundation for further research.

Exponential ergodicity of an affine two-factor model based on the α-root process

2017 ◽  
Vol 49 (4) ◽  
pp. 1144-1169 ◽  
Author(s):  
Peng Jin ◽  
Jonas Kremer ◽  
Barbara Rüdiger
Keyword(s):  
Parameter Estimation ◽  
Factor Model ◽  
Estimation Problem ◽  
Two Dimensional ◽  
Dimensional Model ◽  
Parameter Estimation Problem ◽  
Exponential Ergodicity ◽  
Model Based ◽  
Defaultable Bonds ◽  
Two Dimensional Model

Abstract We study an affine two-factor model introduced by Barczy et al. (2014). One component of this two-dimensional model is the so-called α-root process, which generalizes the well-known Cox–Ingersoll–Ross process. In the α = 2 case, this two-factor model was used by Chen and Joslin (2012) to price defaultable bonds with stochastic recovery rates. In this paper we prove exponential ergodicity of this two-factor model when α ∈ (1, 2). As a possible application, our result can be used to study the parameter estimation problem of the model.

Two-Dimensional, Model-Based, Boundary Matching Using Footprints

1986 ◽  
Vol 5 (4) ◽  
pp. 38-55 ◽  
Author(s):  
Alan Kalvin ◽  
Edith Schonberg ◽  
Jacob T. Schwartz ◽  
Micha Sharir
Keyword(s):  
Two Dimensional ◽  
Dimensional Model ◽  
Model Based ◽  
Two Dimensional Model ◽  
Boundary Matching

Model design for scalable two-dimensional model-based video coding

2002 ◽  
Vol 38 (24) ◽  
pp. 1513 ◽  
Author(s):  
M. Hu ◽  
S. Worrall ◽  
A.H. Sadka ◽  
A.M. Kondoz
Keyword(s):  
Video Coding ◽  
Two Dimensional ◽  
Model Design ◽  
Dimensional Model ◽  
Model Based ◽  
Two Dimensional Model

A two-dimensional model based on the expansion of physical wake boundary for wind-turbine wakes

2019 ◽  
Vol 233-234 ◽  
pp. 975-984 ◽  
Author(s):  
Mingwei Ge ◽  
Ying Wu ◽  
Yongqian Liu ◽  
Qi Li
Keyword(s):  
Wind Turbine ◽  
Two Dimensional ◽  
Dimensional Model ◽  
Model Based ◽  
Two Dimensional Model
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