Results 191 to 200 of about 75,217 (233)

Delamination area quantification in composite structures using Gaussian process regression and auto-regressive models

Journal of Vibration and Control, 2020
After detecting initial delamination damage in a hotspot region of a composite structure monitored through a data-driven approach, the user needs to decide if there is an imminent structural failure or if the system can be kept in operation under ...
Jessé Paixão, S. da Silva, E. Figueiredo, L. Radu, G. Park   +4 more
semanticscholar   +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

Probabilistic Wind Power Forecasting Using Optimized Deep Auto-Regressive Recurrent Neural Networks

IEEE Transactions on Industrial Informatics, 2023
Wind power forecasting is very crucial for power system planning and scheduling. Deep neural networks (DNNs) are widely used in forecasting applications due to their exceptional performance.
Parul Arora, S. M. Jalali, S. Ahmadian, B. K. Panigrahi, P. Suganthan, A. Khosravi   +5 more
semanticscholar   +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 ...
Evans, Jamie, Krishnamurthy, Vikram
openaire   +2 more sources

Impact of Auto-regressive (AR) Process in Bullwhip Analysis in a Multi-location Supply Chain Network

Journal of business management and information systems, 2019
The present study is an attempt to quantify the Bullwhip Effect (BWE) -the phenomenon in which information on demand is distorted in moving up a supply chain. Assuming that the retailer employs an order-up-to level policy with auto-regressive process (AR)
Prabhat Mittal
semanticscholar   +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

2-Dimensional auto-regressive process applied to edge detection

2014 22nd Signal Processing and Communications Applications Conference (SIU), 2014
Edge detection has important applications in image processing area. In addition to well-known deterministic approaches, stochastic models have been developed and validated on edge detection. In this study, a stochastic auto-regressive process method has been presented and this method applied to gray scale and color scale images.
Muammer Catak, Necati Duran
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\
Krishnamurthy, Vikram, Elliott, Robert J.   +1 more
openaire   +1 more source

HMAR: Efficient Hierarchical Masked Auto-Regressive Image Generation

Computer Vision and Pattern Recognition
Visual Auto-Regressive modeling (VAR) has shown promise in bridging the speed and quality gap between autoregressive image models and diffusion models.
Hermann Kumbong, Xian Liu, Tsung-Yi Lin, Ming-Yu Liu, Xihui Liu, Ziwei Liu, Daniel Y. Fu, Christopher R'e, David W. Romero   +8 more
semanticscholar   +1 more source

Dynamic synthetic control method for evaluating treatment effects in auto-regressive processes

Journal of the Royal Statistical Society Series B: Statistical Methodology, 2023
Abstract Motivated by evaluating the effects of air pollution alerts on air quality, we propose the dynamic synthetic control method for micro-level data with time-varying confounders and spatial dependence under an auto-regressive model setting.
Xiangyu Zheng, Song Xi Chen
openaire   +1 more source