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Autoregressive model

Known as: Autoregressive, AR process, Stochastic term 
In statistics and signal processing, an autoregressive (AR) model is a representation of a type of random process; as such, it describes certain time… 
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Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
2007
2007
Abstract —This article proposes a method for modeling andclassification apply on the uterine contractions in the electromyo-gram… 
2006
2006
We derive the fading number of stationary and ergodic (not necessarily Gaussian) single-input multiple-output (SIMO) fading… 
Highly Cited
2003
Highly Cited
2003
The miniaturization of GSM handsets creates nonlinear acoustical echoes between microphones and loudspeakers when the signal… 
Highly Cited
1993
Highly Cited
1993
The A(2Σ+)–X(2Π) transition of SH isolated in Ar and Kr matrices is studied by laser induced fluorescence spectroscopy. The (0,0… 
Highly Cited
1991
Highly Cited
1991
The author presents a fast algorithm for extended lapped transform (ELT), which is a modulated lapped transform (MLT) with longer… 
Highly Cited
1989
Highly Cited
1989
A method is given for unsupervised segmentation and classification of 1D and 2D signals. The method is based on a self-organizing… 
Highly Cited
1986
Highly Cited
1986
The concept of fast KL transform coding introduced earlier [7], [8] for first-order Markov processes and certain random fields… 
1982
1982
A spectral estimation technique is presented for autoregressive moving-average (ARMA) processes. The technique is based on a… 
1981
1981
New almost sure convergence results for a special form of the multidimensional Robbins-Monro stochastic approximation procedure…