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Journal articles on the topic 'Impulse response functions'

Author: Grafiati

Published: 4 June 2021

Last updated: 25 July 2025

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1

Potter, Simon M. "Nonlinear impulse response functions." Journal of Economic Dynamics and Control 24, no. 10 (2000): 1425–46. http://dx.doi.org/10.1016/s0165-1889(99)00013-5.

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2

Montes‐Rojas, Gabriel. "Multivariate Quantile Impulse Response Functions." Journal of Time Series Analysis 40, no. 5 (2019): 739–52. http://dx.doi.org/10.1111/jtsa.12452.

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3

Tubiello, Francesco N., and Michael Oppenheimer. "Impulse-response functions and anthropogenic CO2." Geophysical Research Letters 22, no. 4 (1995): 413–16. http://dx.doi.org/10.1029/94gl03276.

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4

Breitung, Jörg, and Philip Hans Franses. "Impulse response functions for periodic integration." Economics Letters 55, no. 1 (1997): 35–40. http://dx.doi.org/10.1016/s0165-1765(97)00047-5.

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5

Wickens, Michael R., and Roberto Motto. "Estimating shocks and impulse response functions." Journal of Applied Econometrics 16, no. 3 (2001): 371–87. http://dx.doi.org/10.1002/jae.617.

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6

Herlufsen, Henrik, and Svend Gade. "Errors involved in computing impulse response functions via frequency response functions." Mechanical Systems and Signal Processing 6, no. 3 (1992): 193–206. http://dx.doi.org/10.1016/0888-3270(92)90023-c.

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7

Naka, Atsuyuki, and David Tufte. "Examining impulse response functions in cointegrated systems." Applied Economics 29, no. 12 (1997): 1593–603. http://dx.doi.org/10.1080/00036849700000035.

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8

Plagborg-M{ø}ller, Mikkel. "Bayesian inference on structural impulse response functions." Quantitative Economics 10, no. 1 (2019): 145–84. http://dx.doi.org/10.3982/qe926.

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9

Kozachenko, Yu V., and I. V. Rozora. "Cross-correlogram estimators of impulse response functions." Theory of Probability and Mathematical Statistics 93 (February 7, 2017): 79–91. http://dx.doi.org/10.1090/tpms/995.

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10

Jun Li, Hong Hao, and XINGYU FAN. "Structural Damage Identification with Extracted Impulse Response Functions and Optimal Sensor Locations." Electronic Journal of Structural Engineering 14, no. 1 (2015): 123–32. http://dx.doi.org/10.56748/ejse.141961.

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This paper presents a structural damage identification approach based on the time domain impulse response functions, which are extracted from the measured dynamic responses with the input available. The theoretical sensitivity of the impulse response function with respect to the system stiffness parameters considering the damping model is derived. The first-order sensitivity based model updating technique is performed for the iterative model updating. The initial structural finite element model and acceleration measurements from the damaged structure are required. Local damage is identified as

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11

Sulima, Mariusz. "Hilbert Transformation Impulse Response." Image Processing & Communications 19, no. 4 (2014): 27–35. http://dx.doi.org/10.1515/ipc-2015-0022.

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Abstract This work presents a new DHT impulse response function based on the proposed nonlinear equation system obtained as a result of combining the DHT and IDHT equation systems. In the case of input time series with selected characteristics, the DHT results obtained using this impulse response function are characterised by a higher accuracy compared to the DHT results obtained based on the convolution using other known DHT impulse response functions. The results are also characterised by a higher accuracy than the DHT results obtained using the popular indirect DHT method based on discrete

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12

Yoshii, K., L. E. Moore, and B. N. Christensen. "Effect of subthreshold voltage-dependent conductances on the transfer function of branched excitable cells and the conduction of synaptic potentials." Journal of Neurophysiology 59, no. 3 (1988): 706–16. http://dx.doi.org/10.1152/jn.1988.59.3.706.

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1. Impulse response functions were determined from complex point impedance and transfer functions from cultured NG-108 cells to simulate the propagation of a synaptic potential in response to the release of transmitter. In general, the flow of synaptic current has a much shorter duration than the normal membrane time constant, thereby making the use of impulse response functions useful approximations to synaptic events. 2. The resonance observed during the activation of the potassium conductance was reflected in the impulse response function as a pronounced damped oscillation. A comparison of

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13

Chang, Pao‐Li, and Shinichi Sakata. "Estimation of impulse response functions using long autoregression." Econometrics Journal 10, no. 2 (2007): 453–69. http://dx.doi.org/10.1111/j.1368-423x.2007.00216.x.

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14

O’Keefe, John. "Counting reflections in measured acoustic impulse response functions." Journal of the Acoustical Society of America 128, no. 4 (2010): 2465. http://dx.doi.org/10.1121/1.3508829.

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15

Kilian, Lutz. "Small-sample Confidence Intervals for Impulse Response Functions." Review of Economics and Statistics 80, no. 2 (1998): 218–30. http://dx.doi.org/10.1162/003465398557465.

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16

Burr, David C., and M. Concetta Morrone. "Impulse-response functions for chromatic and achromatic stimuli." Journal of the Optical Society of America A 10, no. 8 (1993): 1706. http://dx.doi.org/10.1364/josaa.10.001706.

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17

Frey, Douglas, Victor Coelho, and Rangaraj M. Rangayyan. "Acoustical Impulse Response Functions of Music Performance Halls." Synthesis Lectures on Speech and Audio Processing 9, no. 2 (2013): 1–110. http://dx.doi.org/10.2200/s00488ed1v01y201303sap012.

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18

Qu, Chun-Xu, Ting-Hua Yi, and Hong-Nan Li. "Modal identification for superstructure using virtual impulse response." Advances in Structural Engineering 22, no. 16 (2019): 3503–11. http://dx.doi.org/10.1177/1369433219862951.

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In civil engineering, structural modes are identified with the assumption of stationary white noise, which cannot be satisfied in practical engineering. This article proposes a new method, which contains the virtual impulse response and eigensystem realization algorithm. The formulation of virtual impulse response is derived from the inverse Fourier transform of the ratio of the cross-power to auto-power spectral density functions of the measurement responses, which is based on the concept of frequency response function. During the formulation derivation, a single point excitation is only cons

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19

Charaziak, Karolina K., and Alessandro Altoè. "Estimating cochlear impulse responses using frequency sweeps." Journal of the Acoustical Society of America 153, no. 4 (2023): 2251–61. http://dx.doi.org/10.1121/10.0017547.

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Cochlear mechanics tends to be studied using single-location measurements of intracochlear vibrations in response to acoustical stimuli. Such measurements, due to their invasiveness and often the instability of the animal preparation, are difficult to accomplish and, thus, ideally require stimulus paradigms that are time efficient, flexible, and result in high resolution transfer functions. Here, a swept-sine method is adapted for recordings of basilar membrane impulse responses in mice. The frequency of the stimulus was exponentially swept from low to high (upward) or high to low (downward) a

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20

Jayasuriya, S., and M. A. Franchek. "A Class of Transfer Functions With Non-Negative Impulse Response." Journal of Dynamic Systems, Measurement, and Control 113, no. 2 (1991): 313–15. http://dx.doi.org/10.1115/1.2896381.

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Presented in this note is a class of stable, minimum phase transfer functions whose impulse response is non-negative. A simple sufficiency criterion based on the relative locations of the poles and zeros characterizes the class. When the transfer function is in a factored form the sign of its impulse response may either be obtained by inspection or is inconclusive. A need for identifying such transfer functions was recently established by Jayasuriya (1989) who showed that a controller designed on the basis of maximizing a step input disturbance will reject a persistent disturbance bounded by t

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21

Mehta, Avinash, Munish Verma, Vijay K. Lamba, Susheel Kumar, and Sandeep Kumar. "ANALYSIS OF MODIFIED COSH WINDOW FUNCTION AND PERFORMANCE EVALUATION OF THE FIR FILTER DESIGNED USING WINDOWING TECHNIQUES." INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY 3, no. 2 (2012): 324–28. http://dx.doi.org/10.24297/ijct.v3i2c.2893.

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Filters are used in electronic circuits to remove the unwanted frequency components from desired signals. A digital filter basically provide high attenuation to the unwanted ones and offer very low or ideally zero attenuation to desired signal components when itâ€™s impulse response is adjusted as per requirement. For ideal filters, the length of such an impulse response is infinite and also the filter will be non-causal and unrealizable. So, we need to truncate this infinite impulse response to make it finite. For this truncation, we use window functions. Using window functions, we obtain a f

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22

Elko, Gary W., Jens Meyer, Steven Backer, Tomas Gaensler, Eric Diethorn, and Heinz Teutsch. "Lab tour and demo of software application developed to measure spatial and acoustic linear systems responses." Journal of the Acoustical Society of America 156, no. 4_Supplement (2024): A13. https://doi.org/10.1121/10.0034935.

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Over many years, we have developed a software system that measures the frequency and spatial responses of microphones and loudspeakers. The software runs on a Mac or PC and uses standard multichannel sound card hardware and MATLAB for the UI. The UI calls a special processing library that records and averages the acoustic impulse responses for up to 64 channels simultaneously. The software application called SAMH, measures averaged multichannel impulse responses using a chirp signal. SAMH can also control a rotator that allows measurements to be made in with a desired angular resolution to mea

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23

Murray, Drew A., and Robert J. McGough. "Numerical spatial impulse response calculations for a circular piston radiating in a lossy medium." Journal of the Acoustical Society of America 151, no. 5 (2022): 3104–15. http://dx.doi.org/10.1121/10.0009351.

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Exact analytical expressions for the spatial impulse response are available for certain transducer geometries. These exact expressions for the spatial impulse response, which are only available for lossless media, analytically evaluate the Rayleigh integral to describe the effect of diffraction in the time domain. To extend the concept of the spatial impulse response by including the effect of power law attenuation in a lossy medium, time-domain Green's functions for the Power Law Wave Equation, which are expressed in terms of stable probability density functions, are computed numerically and

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24

Vega-Bermudez, F., and K. O. Johnson. "SA1 and RA Receptive Fields, Response Variability, and Population Responses Mapped with a Probe Array." Journal of Neurophysiology 81, no. 6 (1999): 2701–10. http://dx.doi.org/10.1152/jn.1999.81.6.2701.

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SA1 and RA receptive fields, response variability, and population responses mapped with a probe array. Twenty-four slowly adapting type 1 (SA1) and 26 rapidly adapting (RA) cutaneous mechanoreceptive afferents in the rhesus monkey were studied with an array of independently controlled, punctate probes that covered an entire fingerpad. Each afferent had a receptive field (RF) on a single fingerpad and was studied at 73 skin sites (50 mm2). The entire array was lowered to 1.6 mm below the point of initial skin contact (the background indentation) before delivering single-probe indentations. SA1

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25

Kirchner, James W. "Impulse Response Functions for Nonlinear, Nonstationary, and Heterogeneous Systems, Estimated by Deconvolution and Demixing of Noisy Time Series." Sensors 22, no. 9 (2022): 3291. http://dx.doi.org/10.3390/s22093291.

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Impulse response functions (IRFs) are useful for characterizing systems’ dynamic behavior and gaining insight into their underlying processes, based on sensor data streams of their inputs and outputs. However, current IRF estimation methods typically require restrictive assumptions that are rarely met in practice, including that the underlying system is homogeneous, linear, and stationary, and that any noise is well behaved. Here, I present data-driven, model-independent, nonparametric IRF estimation methods that relax these assumptions, and thus expand the applicability of IRFs in real-world

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26

Kirchner, James W. "Impulse Response Functions for Nonlinear, Nonstationary, and Heterogeneous Systems, Estimated by Deconvolution and Demixing of Noisy Time Series." Sensors 22, no. 9 (2022): 3291. http://dx.doi.org/10.3390/s22093291.

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Impulse response functions (IRFs) are useful for characterizing systems’ dynamic behavior and gaining insight into their underlying processes, based on sensor data streams of their inputs and outputs. However, current IRF estimation methods typically require restrictive assumptions that are rarely met in practice, including that the underlying system is homogeneous, linear, and stationary, and that any noise is well behaved. Here, I present data-driven, model-independent, nonparametric IRF estimation methods that relax these assumptions, and thus expand the applicability of IRFs in real-world

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27

Fursov, V. A. "Constructing a quadratic-exponential FIR-filter with an extended frequency response midrange." Computer Optics 42, no. 2 (2018): 297–305. http://dx.doi.org/10.18287/2412-6179-2018-42-2-297-305.

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This article is concerned with synthesizing filter with finite impulse response (FIR-filters) employed to correct radially symmetric distortions such as defocusing. We propose a new parametric class of finite impulse response filters (FIR-filters) based on a model of the one-dimensional radially symmetric frequency response. In the proposed method, the one-dimensional frequency response is composed of quadratic and exponential functions. The two-dimensional impulse response of the filter is constructed by sampling one-dimensional impulse responses for all directions. The development consists i

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28

Yoo, Chul-Sang, Ha-Young Kim, and Joo-Young Park. "Analysis of Runoff Characteristics Using Multiple Impulse Response Functions." Journal of Korea Water Resources Association 43, no. 6 (2010): 571–81. http://dx.doi.org/10.3741/jkwra.2010.43.6.571.

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29

Zele, A. J., D. Cao, and J. Pokorny. "Dark-adapted rods alter cone temporal impulse response functions." Journal of Vision 6, no. 13 (2010): 68. http://dx.doi.org/10.1167/6.13.68.

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30

LEE, A. C. "Some restrictions of the non-causal impulse response functions." International Journal of Systems Science 20, no. 8 (1989): 1403–10. http://dx.doi.org/10.1080/00207728908910225.

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31

Blazhievska, Irina, and Vladimir Zaiats. "Estimation of impulse response functions in two-output systems." Communications in Statistics - Theory and Methods 49, no. 2 (2018): 257–80. http://dx.doi.org/10.1080/03610926.2018.1536210.

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32

Inoue, Atsushi, and Lutz Kilian. "Inference on impulse response functions in structural VAR models." Journal of Econometrics 177, no. 1 (2013): 1–13. http://dx.doi.org/10.1016/j.jeconom.2013.02.009.

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33

Chen, Kui Fu, and Yan Feng Li. "On the Integration Schemes of Retrieving Impulse Response Functions from Transfer Functions." Mathematical Problems in Engineering 2010 (2010): 1–9. http://dx.doi.org/10.1155/2010/143582.

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The numerical inverse Laplace transformation (NILM) makes use of numerical integration. Generally, a high-order scheme of numerical integration renders high accuracy. However, surprisingly, this is not true for the NILM to the transfer function. Numerical examples show that the performance of higher-order schemes is no better than that of the trapezoidal scheme. In particular, the solutions from high-order scheme deviate from the exact one markedly over the rear portion of the period of interest. The underlying essence is examined. The deviation can be reduced by decreasing the frequency-sampl

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34

Cromwell, Jeff B., and Michael J. Hannan. "The Utility of Impulse Response Functions in Regional Analysis: Some Critical Issues." International Regional Science Review 15, no. 2 (1993): 199–222. http://dx.doi.org/10.1177/016001769301500204.

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Regional scientists have long been interested in measuring the effects of various external and internal stimuli on a regional economy. Measuring the actual size and timing of exogenous and endogenous impacts has been of special interest, as numerical or estimation techniques allow regional actors (governments, business, and others) to make policy-type probability statements and actions in response to changes to these stimuli. Recently, the use of vector autoregressive (VAR) models and, consequently, impulse response functions has become increasingly popular. This paper will closely examine the

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35

Rozora, I. V., and A. O. Melnyk. "Construction of goodness-of-fit criteria for the type of impulse response function." Science, technologies, innovation, no. 2(22) (2022): 52–60. http://dx.doi.org/10.35668/2520-6524-2022-2-07.

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The article is devoted to the study of the impulse response function, its estimation and properties, square-Gaussian random variables and processes, the rate of convergence of the unknown impulse response function, testing the hypothesis about the type of impulse response function, building a simulation model. The study showed that the pulse response function is the output signal of the system during signal processing, when the input signal is a short pulse. In a more general form, the impulse response function describes the response or output of the system as a function of time. Also, the imp

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36

van der Valk, Paul L. C., and Daniel J. Rixen. "An Impulse Based Substructuring method for coupling impulse response functions and finite element models." Computer Methods in Applied Mechanics and Engineering 275 (June 2014): 113–37. http://dx.doi.org/10.1016/j.cma.2014.03.003.

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37

Lütkepohl, Helmut, and D. S. Poskitt. "Estimating Orthogonal Impulse Responses via Vector Autoregressive Models." Econometric Theory 7, no. 4 (1991): 487–96. http://dx.doi.org/10.1017/s0266466600004722.

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Impulse response functions from time series models are standard tools for analyzing the relationship between economic variables. The asymptotic distribution of orthogonalized impulse responses is derived under the assumption that finite order vector autoregressive (VAR) models are fitted to time series generated by possibly infinite order processes. The resulting asymptotic distributions of forecast error variance decompositions are also given.

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38

Khalaf, Lynda, and Beatriz Peraza López. "Simultaneous Indirect Inference, Impulse Responses and ARMA Models." Econometrics 8, no. 2 (2020): 12. http://dx.doi.org/10.3390/econometrics8020012.

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A two-stage simulation-based framework is proposed to derive Identification Robust confidence sets by applying Indirect Inference, in the context of Autoregressive Moving Average (ARMA) processes for finite samples. Resulting objective functions are treated as test statistics, which are inverted rather than optimized, via the Monte Carlo test method. Simulation studies illustrate accurate size and good power. Projected impulse-response confidence bands are simultaneous by construction and exhibit robustness to parameter identification problems. The persistence of shocks on oil prices and retur

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Gunn, Roger N., Steve R. Gunn, and Vincent J. Cunningham. "Positron Emission Tomography Compartmental Models." Journal of Cerebral Blood Flow & Metabolism 21, no. 6 (2001): 635–52. http://dx.doi.org/10.1097/00004647-200106000-00002.

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The current article presents theory for compartmental models used in positron emission tomography (PET). Both plasma input models and reference tissue input models are considered. General theory is derived and the systems are characterized in terms of their impulse response functions. The theory shows that the macro parameters of the system may be determined simply from the coefficients of the impulse response functions. These results are discussed in the context of radioligand binding studies. It is shown that binding potential is simply related to the integral of the impulse response functio

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40

Nair, Veena J., Athri S. S, and Jishnu R. "SLEEP - THE MOST NEGLECTED IMPULSE OF PRESENT AGE." International Ayurvedic Medical Journal p4, no. 05 (2020): 2433–36. http://dx.doi.org/10.46607/iamj11p4052020.

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A good night sleep is required for wellbeing of every organism. Humans though considered as an intelligent among living beings, seldom understand the importance of sleep impulse and ignore it. This ignorance has paved way for many health issues. Impulses are generated for maintenance of body and must be managed at proper time. Sleep impulse is essential for various brain functions, production of various hormone like growth hormone, cognitive power, good immune response etc. Today in highly competitive world human have forgotten his body needs. Earlier handful of persons suffered from sleep dis

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41

Rahman, Syed Mustafizur, M. Rezaul Islam, and Mumnunul Keramat. "Seismic Imaging by Impulse Response for Studying Crustal Structure of the Central Tibet." Journal of Scientific Research 1, no. 1 (2008): 61–71. http://dx.doi.org/10.3329/jsr.v1i1.1082.

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Time-shifted source functions along with unwanted events produce the composite seismic trace. The time-shift varies according to the travel path of the source, which is reflected back from an interface. The arrival times of the reflected waves have been estimated as time-shifted sources in a technique with the application of Fourier transformation of composite seismic trace and source functions. Accurate time-shifts and amplitude coefficients are determined using the technique in the composite seismic traces. A very small time-shift has also been shown resolved. The technique is applied to IND

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42

Yoshimura, K. "A novel type of mechanoreception by the flagella of Chlamydomonas." Journal of Experimental Biology 199, no. 2 (1996): 295–302. http://dx.doi.org/10.1242/jeb.199.2.295.

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A novel type of mechanosensory mechanism is found in Chlamydomonas reinhardtii. When a cell is captured with a suction pipette and a negative pressure is applied, the cell produces repetitive Ca2+ impulses at a frequency of 0.5-1.0 Hz. The impulse frequency increases with the applied pressure. The impulses are produced when the flagella are sucked into the pipette but not when the cell body is sucked in leaving the flagella outside the pipette. Cells with short flagella produce impulses of small amplitude. Thus, the site where the cell senses mechanical stimuli and generates the impulse curren

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43

McCracken, K. G., M. L. Oristaglio, and G. W. Hohmann. "A comparison of electromagnetic exploration systems." GEOPHYSICS 51, no. 3 (1986): 810–18. http://dx.doi.org/10.1190/1.1442133.

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Electromagnetic (EM) exploration systems fall into three distinct classes, (1) frequency domain, (2) impulse response, and (3) step response, and have overall frequency responses that approximate [Formula: see text], [Formula: see text], and [Formula: see text]. To examine further these three classes, the transfer function of a frequency‐domain system, and the step and impulse response functions of ideal time‐domain EM systems (TEM), are derived in terms of a single set of target‐specific parameters. The inductive time constants of practical exploration targets extend over three orders of magn

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44

Sheefeni, Johannes, and Matthew Ocran. "Exchange rate pass-through to domestic prices in Namibia: SVAR evidence." Journal of Economic and Financial Sciences 7, no. 1 (2014): 89–102. http://dx.doi.org/10.4102/jef.v7i1.132.

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This article investigates exchange rate pass-through to domestic prices in Namibia. The study covers the period of 1993:Q1 – 2011:Q4, and employed the impulse response functions and variance decompositions obtained from a structural vector autoregressive model. The results from the impulse response functions show that there is a high and long-lasting effect from changes in exchange rates to inflation in Namibia, or high exchange rate pass-through into domestic inflation. The results from the forecast error variance decompositions also reflect that changes in the price level evolve endogenously

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45

Liu, Hsi-Ping. "Calculation of zero-offset vertical seismic profiles generated by a horizontal point force acting on the surface of an anelastic half-space." Bulletin of the Seismological Society of America 80, no. 4 (1990): 832–56. http://dx.doi.org/10.1785/bssa0800040832.

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Abstract Impulse responses including near-field terms have been obtained in closed form for the zero-offset vertical seismic profiles generated by a horizontal point force acting on the surface of an anelastic half-space. The method is based on the correspondence principle. Through transformation of variables, the Fourier transform of the elastic impulse response is put in a form such that the Fourier transform of the corresponding anelastic impulse response can be expressed as elementary functions and their definite integrals involving distance, angular frequency, phase velocities, and attenu

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46

Hatemi-J, Abdulnasser, and Youssef El-Khatib. "The nexus of trade-weighted dollar rates and the oil prices: an asymmetric approach." Journal of Economic Studies 47, no. 7 (2020): 1579–89. http://dx.doi.org/10.1108/jes-06-2019-0266.

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PurposeThis paper investigates the dynamic relationship between the trade-weighted dollar exchange rates and the oil prices in the world market. Monthly data during 1980–2017 are used for this purpose.Design/methodology/approachThe symmetric and asymmetric generalized impulse response functions are estimated for these important economic indicators.FindingsThe empirical findings show that if the dollar rate increases (i.e. the dollar depreciates), the oil price will increase. The reverse relationship is also supported empirically meaning that an increase in the oil price will results in a signi

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47

Bruder, Stefan, and Michael Wolf. "Balanced Bootstrap Joint Confidence Bands for Structural Impulse Response Functions." Journal of Time Series Analysis 39, no. 5 (2018): 641–64. http://dx.doi.org/10.1111/jtsa.12289.

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48

Panopoulou, Ekaterini, and Theologos Pantelidis. "Integration at a cost: evidence from volatility impulse response functions." Applied Financial Economics 19, no. 11 (2009): 917–33. http://dx.doi.org/10.1080/09603100802112300.

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49

Mourjopoulos, J. "On the variation and invertibility of room impulse response functions." Journal of Sound and Vibration 102, no. 2 (1985): 217–28. http://dx.doi.org/10.1016/s0022-460x(85)80054-7.

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50

Hafner, C. M., and H. Herwartz. "Structural analysis of portfolio risk using beta impulse response functions." Statistica Neerlandica 52, no. 3 (1998): 336–55. http://dx.doi.org/10.1111/1467-9574.00088.

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