A rank test based approach to order estimation. I. 2-D AR models application

Aksasse, Brahim; Badidi, L.; Radouane, L.

doi:10.1109/78.771062

Cited by 19 publications

(4 citation statements)

References 21 publications

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“…A reservation is that product moment methods [35] have been found to be insensitive to changes in model support, even in simple simulated 2-D supports [36]. This "nding is, however, challenged by recent work in the signal processing "eld [37] which suggest that product moment methods can yield useful results.…”

Section: -D Support Estimationmentioning

confidence: 95%

Signal processing and control paradigms for industrial web and sheet manufacturing

Wellstead¹,

Zarrop²,

Duncan

2000

Int. J. Adapt. Control Signal Process.

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SUMMARYThe dynamic analysis of paper making, polymer extrusion and similar web (also known as sheet) forming processes is treated in a number of di!erent ways in the literature. However, fundamental modelling arguments lead to contol paradigms based upon two-dimensional (2-D) dynamical systems and orthogonal basis function representations. These paradigms are pursued here in a way which traces the associated estimation and control algorithms and the vital issue of sensing.

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Section: -D Support Estimationmentioning

confidence: 95%

Signal processing and control paradigms for industrial web and sheet manufacturing

Wellstead¹,

Zarrop²,

Duncan

2000

Int. J. Adapt. Control Signal Process.

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“…. , n 1 n 2 is provided to satisfy the threshold test NR m ≥ ξ , where ξ is a fixed threshold close to but less than one [25]. The smallest k is selected as the effective rank of R m , where σ m and n 1 n 2 are the singular values and the number of columns of R m , m = 0, 1, 2, respectively.…”

Section: Appendix a Rank Test Based Approach For Ar Order Determinatmentioning

confidence: 99%

“…In these methods, the order of the system is usually determined using the rank of special matrices. [24][25][26][27] are examples of this class.…”

Section: Introductionmentioning

confidence: 98%

Two-dimensional ARMA model order determination

Sadabadi¹,

Shafiee²,

Karrari³

2009

ISA Transactions

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“…But AR and ARMA model parameter estimation has not received much attention. Spectral estimation of 2-D series [1], [2] and model order estimation of 2-D AR/ARMA [3], [4], [5], [6] were investigated in a few studies. In time domain, literatures have focused on Yule-Walker method.…”

Section: Introductionmentioning

confidence: 99%

A new method for 2-D AR model parameter estimation

Zeinali

Shafiee

2013

The 3rd International Conference on Control, Instrumentation, and Automation

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This paper presents a new method for two dimensional (2-D) autoregressive (AR) model parameters estimation. Based on Levinson-Durbin method, a new approach is extended for 2-D series, and for this purpose, an algorithm is presented. The presented method preserves in the 2-D case advantages of Levinson-Durbin such as recursive and online estimation similar 1-D case. This approach is illustrated by a numerical example. 1

show abstract

A rank test based approach to order estimation. I. 2-D AR models application

Cited by 19 publications

References 21 publications

Signal processing and control paradigms for industrial web and sheet manufacturing

Signal processing and control paradigms for industrial web and sheet manufacturing

Two-dimensional ARMA model order determination

A new method for 2-D AR model parameter estimation

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