Results 211 to 220 of about 39,760 (245)

Tracking an Auto-Regressive Process with Limited Communication

2020 IEEE International Symposium on Information Theory (ISIT), 2020
Samples from a high-dimensional AR[1] process are quantized and sent over a time-slotted communication channel of finite capacity. The receiver seeks to form an estimate of the process in real-time. We consider the slow-sampling regime where multiple communication slots occur between two sampling instants.
Rooji Jinan, Parimal Parag, Himanshu Tyagi   +2 more
openaire   +1 more source

Video textures using the auto-regressive process

ACM SIGGRAPH 2002 conference abstracts and applications, 2002
Recently, there have been attempts at creating 'video textures', that is, synthesising new video clips based on existing ones. Schodl et al. showed new video clips by carefully choosing sub-loops of an original video sequence that could be replayed.
Neill W. Campbell, Colin J. Dalton, David P. Gibson, Barry T. Thomas   +3 more
openaire   +1 more source

Optimal filtering of doubly stochastic auto-regressive processes

Automatica, 1999
Here the authors derive exact finite-dimensional filters for a class of doubly stochastic auto-regressive models, the parameters of such processes varying according to a nonlinear function of a Gauss-Markov process. A characterization of the general solution is provided, and examples in which the state of the filter is determined by a finite number of ...
Jamie S. Evans, Vikram Krishnamurthy
openaire   +2 more sources

Prediction of software reliability using an auto regressive process

International Journal of Systems Science, 1997
Abstract This paper proposes a procedure for predicting software reliability, using an Auto Regressive (AR) model. The parameters of the models are selected using computationally efficient numerical methods like Singular Value Decomposition ( SVD) and QR factorization.
Subhashis Chatterjee, Ravindra Babu Misra, Syed Samsul Alam   +2 more
openaire   +1 more source

Auto‐Regressive Model for Nonstationary Stochastic Processes

Journal of Engineering Mechanics, 1988
An autoregressive model for univariate, one‐dimensional, nonstationary, Gaussian random processes with evolutionary power spectra is introduced. At the same time, an efficient technique for numerically generating sample functions of such nonstationary processes is developed.
George Deodatis, M. Shinozuka
openaire   +1 more source

ALARM: A logistic auto-regressive model for binary processes on networks

2013 IEEE Global Conference on Signal and Information Processing, 2013
We introduce the ALARM model, a logistic autoregressive model for discrete-time binary processes on networks, and describe a technique for learning the graph structure underlying the model from observations. Using only a small number of parameters, the proposed ALARM can describe a wide range of dynamic behavior on graphs, such as the contact process ...
Ameya Agaskar, Yue M. Lu
openaire   +1 more source

A new order selection method for auto-regressive processes

IEEE Oceanic Engineering Society. OCEANS'98. Conference Proceedings (Cat. No.98CH36259), 2002
An approximate formula for the residual variance of autoregressive modeling with the least-squares-forward (LSF) method is derived. By using this formula the statistical behavior of the residual variance is determined approximately. Based on this formula, a new sequential testing algorithm for order selection of auto-regressive processes is proposed ...
M. Karimi, M.H. Bastani
openaire   +1 more source

Fault detection based on auto-regressive extreme learning machine for nonlinear dynamic processes

Applied Soft Computing, 2021
Abstract Through utilizing the extreme learning machines (ELM) in modeling the nonlinear dynamic relationship of the time-series data, a novel fault detection approach based on auto-regressive ELM (ARELM) is proposed for nonlinear dynamic processes.
Yang Chen, Chudong Tong, Yinghui Ge, Ting Lan 0001   +3 more
openaire   +1 more source

Exact finite-dimensional filters for doubly stochastic auto-regressive processes

IEEE Transactions on Automatic Control, 1997
The authors consider the classical scalar linear Gaussian model for the state \(x\) and observations \(y\): \[ x_{k+1} =A_{k+1} x_k+ B_{k+1} w_{k+1}, \quad y_k= C_k x_k+ d_k v_k. \] They derive an exact finite-dimensional recursive filter for the vector-valued process \(s_k\): \[ s_{k+1} =F(x_k) s_k+ u_k, \] where \(F(x)\) is a polynomial matrix in \(x\
Vikram Krishnamurthy, Robert J. Elliott
openaire   +1 more source

Nested auto-regressive processes for MPEG-encoded video traffic modeling

IEEE Transactions on Circuits and Systems for Video Technology, 2001
This paper presents a new traffic model for MPEG-encoded video sequences. The hybrid gamma/Pareto distribution is used for all three types of frames in MPEG-encoded video sequences, and the present model takes scene changes into account. The autocorrelation structure is modeled using two second-order auto-regressive (AR) processes nested with each ...
Derong Liu 0001, Endre I. Sára, Wei Sun
openaire   +1 more source