Results 221 to 230 of about 62,188 (257)
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Impulse-response function of photorefractive phase conjugation

Optics Letters, 1989
Explicit expressions for the impulse-response function of a photorefractive phase conjugator are derived. The expressions are in the form of an infinite series of Bessel functions. The results are derived by using the undepleted pump approximation and are therefore valid at least for small time intervals, even when the conjugator is unstable.
G C, Papen, B E, Saleh, J A, Tataronis
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An investigation of the impulse functions for the nonlinear BOLD response in functional MRI

Magnetic Resonance Imaging, 2000
Functional MRI (fMRI) based on blood oxygenation level dependent (BOLD) contrast can be used to detect hemodynamic responses to a broad range of stimuli. It however remains unclear in what fashion the BOLD response is a linear system, and how the impulse function differs with stimulation of varying duration.
H, Liu, J, Gao
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Multivariate Quantile Impulse Response Functions

Journal of Time Series Analysis, 2019
A reduced form multivariate quantile autoregressive model is developed to study heterogeneity in the effects of macroeconomic shocks. This framework is used for forecasting and for constructing quantile impulse response functions that explore dynamic heterogeneity in the response of endogenous variables to different shocks.
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System Identification: Impulse Response Functions

Journal of the Engineering Mechanics Division, 1978
An approach is presented for estimating the impulse response function of a multidegree-of-freedom structural system. The approach discretizes the time axis into contiguous time segments and estimates the structure's impulse response function for each time segment.
Morteza A.M. Torkamani, Gary C. Hart
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An impulse response function for a fuzzy structure

The Journal of the Acoustical Society of America, 1995
The authors are employing some of their previous works in structural acoustics to define, investigate, and interpret the response behaviors of so called fuzzy structures. A formalism is developed to describe the response behavior of a master structure to which an ensemble of appendages are attached.
G. Maidanik, J. Dickey
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Estimating shocks and impulse response functions

Journal of Applied Econometrics, 2001
AbstractThis paper examines the issue of how to identify the shocks in a cointegrated VAR when the following assumptions are made: the variables can be classified as endogenous or exogenous, there are as many cointegrating relations as endogenous variables, the cointegrating vectors are identified and they contain at least one exogenous variable. It is
Wickens, M.R., Motto, R.
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Impulse Response Function

2008
Sims (1980) questioned the way classical simultaneous equations models were specified and identified. He argued in particular that the exogeneity assumptions for some of the variables are often problematic. As an alternative he advocated the use of vector autoregressive (VAR) models for macroeconometric analysis. These models have the form where y t = (
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Continuous Function Modeling of Head-Related Impulse Response

IEEE Signal Processing Letters, 2015
A continuous function model is developed for efficient head-related impulse response (HRIR) representation. In this model, HRIR is modeled as the response of an IIR filter via common factor decomposition analysis, where HRIRs at the same azimuth but different elevations share the same IIR pole part and HRIRs at the same elevation but different ...
Zhixin Wang, Cheung-Fat Chan
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Small-sample Confidence Intervals for Impulse Response Functions [PDF]

open access: possibleReview of Economics and Statistics, 1998
Bias-corrected bootstrap confidence intervals explicitly account for the bias and skewness of the small-sample distribution of the impulse response estimator, while retaining asymptotic validity in stationary autoregressions. Monte Carlo simulations for a wide range of bivariate models show that in small samples bias-corrected bootstrap intervals tend ...
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The Impulse, Frequency Response and Transfer Functions

International Journal of Electrical Engineering & Education, 1984
Three mathematical characterisations of linear systems are discussed with the aim of clarifying their interrelations and role in predicting responses to given stimuli.
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