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Separable autoregressive moving average graph-temporal filters
2016 24th European Signal Processing Conference (EUSIPCO), 2016Despite their widespread use for the analysis of graph data, current graph filters are designed for graph signals that do not change over time, and thus they cannot simultaneously process time and graph frequency content in an adequate manner. This work presents ARMA2D, an autoregressive moving average graph-temporal filter that captures jointly the ...
Elvin Isufi +3 more
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A note on Kalman filtering for the seasonal moving average model
Biometrika, 1984We show that if we apply the Kalman filter to a pure seasonal moving average model with no missing observations, then, by using a result of the second author [ibid. 66, 59-65 (1979; Zbl 0411.62059)], we can obtain significant computational savings.
Kohn, Robert, Ansley, Craig F.
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On some efficient algorithms for moving-average filtering
[1992] Proceedings of the 35th Midwest Symposium on Circuits and Systems, 2003A new approach to moving-average filtering is proposed based on a model of an input mixture as a finite sum of sinusoidal segments. The correspondent filter is particularly efficient when processing very short-duration mixtures. Among its advantages are high precision of useful signal recovery and relative simplicity of construction. Algorithms and the
V. Lyandres, S. Briskin
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Harmonic Identification Methods Based on Moving Average Filters for Active Power Filters
2008 IEEE Industry Applications Society Annual Meeting, 2008Harmonic detection is very important in the control of active power filters (APFs). This paper presents a technique for harmonic identification, based on moving average filters (MVAs) and heterodyning, very suitable for digital implementation. The approach of fundamental component identification is contributed both for single-phase and three-phase ...
Francisco D. Freijedo +3 more
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A statistical approach for optimal order adjustment of a moving average filter
2018 IEEE/ION Position, Location and Navigation Symposium (PLANS), 2018The moving average (MA) filter is a smoothing filter well-known in the digital signal processing community. The MA filter has only one configuration parameter, N, which is the order of the filter and is used to adjust the smoothing effect of an MA filter.
Rodrigo Gonzalez, Carlos Adrián Catania
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Moving Average Hybrid FIR Filter in Ultrasound Image Processing
18th International Conference on Electronics, Communications and Computers (conielecomp 2008), 2008In this work, we present a novel technique for ultrasound image processing (2D signals). The moving average hybrid FIR filter (MAH-FIR) which it work with two different FIR filter, the moving average (MA) and median hybrid (FMH) filters. We experimented with continuous linear regression function and Lagrange multiplier to obtain the approximation of ...
Luis Javier Morales-Mendoza +4 more
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Evaluation of Apparent Noise on CT Images Using Moving Average Filters
Journal of Digital Imaging, 2021This study aims to devise a simple method for evaluating the magnitude of texture noise (apparent noise) observed on computed tomography (CT) images scanned at a low radiation dose and reconstructed using iterative reconstruction (IR) and deep learning reconstruction (DLR) algorithms, and to evaluate the apparent noise in CT images reconstructed using ...
Keisuke Fujii 0005 +5 more
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The Journal of the Acoustical Society of America, 1981
A moving-average notch filter with a well-defined phase characteristic for use in eliminating oscillation frequencies in a sound amplification system, wherein this moving-average filter is designed to have an output Y K in accordance with the system equation ##EQU1## where b 1 are the weighting coefficients, X K-i are input samples, and K is a ...
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A moving-average notch filter with a well-defined phase characteristic for use in eliminating oscillation frequencies in a sound amplification system, wherein this moving-average filter is designed to have an output Y K in accordance with the system equation ##EQU1## where b 1 are the weighting coefficients, X K-i are input samples, and K is a ...
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Autoregressive moving average graph filters a stable distributed implementation
2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2017We present a novel implementation strategy for distributed autoregressive moving average (ARMA) graph filters. Differently from the state of the art implementation, the proposed approach has the following benefits: (i) the designed filter coefficients come with stability guarantees, (ii) the linear convergence time can now be controlled by the filter ...
Elvin Isufi, Andreas Loukas, Geert Leus
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Fast computation of moving average and related filters in octagonal windows
Pattern Recognition Letters, 1997Abstract A method is proposed for efficiently computing moving average filters in regular octagonal windows, as approximations to circular windows. The algorithm requires thirteen operations per pixel irrespective of window size and is faster than existing Fourier-based and recursive methods for all but the smallest windows.
Chris A. Glasbey, R. Jones
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