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Detection and extraction of periodic noises in audio and biomedical signals using Kalman filter
, Article Signal Processing ; Volume 88, Issue 8 , August , 2008 , Pages 2114-2121 ; 01651684 (ISSN) ; Farsi, A ; Ghaed, M. H ; Karimi Ghartemani, M ; Sharif University of Technology
2008
Abstract
This paper studies the subject of adaptive noise cancelation using the Kalman filtering technique to achieve high precision and fast convergence. It is shown that the Kalman filter can successfully be designed to detect and extract periodic noises which may be constituted of different sinusoidal components with possibly unknown and/or time-varying frequencies. This highlights the feature of Kalman filter in synthesizing periodic noises in the time-domain which is not possible using Fourier-based methods such as DFT. Usefulness of the method is discussed in the context of two examples: active cancelation of periodic noises from audio waveforms and filtering of electrocardiogram measurements....
Active power filter control in three-phase four-wire systems using space vector modulation
, Article 2006 International Conference on Power Electronics, Drives and Energy Systems, PEDES '06, New Delhi, 12 December 2006 through 15 December 2006 ; 2006 ; 078039772X (ISBN); 9780780397729 (ISBN) ; Rahimi, M ; Sharif University of Technology
2006
Abstract
In this paper, by extending Space Vector Modulation (SVM) technique to three-phase four-wire systems, a new strategy is developed for the control of Active Power Filters (APFs). It is shown that the conventional SVM method cannot compensate for the current in the neutral wire in a three-phase four wire system. Simulations have been performed using PSCAD/EMTDC software. Simulation results are provided to prove the ability of the proposed technique in compensating the zero-sequence current. ©2006 IEEE
A neural network aided adaptive second-order gaussian filter for tracking maneuvering targets
, Article ICTAI 2005: 17th IEEE International Conference on Tools with Artificial Intelligence, ICTAI'05, Hong Kong, 14 November 2005 through 16 November 2005 ; Volume 2005 , 2005 , Pages 439-446 ; 10823409 (ISSN); 0769524885 (ISBN); 9780769524887 (ISBN) ; Langary, D ; Sharif University of Technology
2005
Abstract
The adaptive capability of filters is known to be increased by incorporating a neural network into the filtering procedure. In this paper, an adaptive algorithm for tracking maneuvering targets based on neural networks is proposed. This algorithm is implemented with two filters based on the current statistical model and a multilayer feedforward neural network. The two filters track the same maneuvering target in parallel and the neural network automatically considers all the state information of the two filters and adaptively adjusts the process variance of one of them to achieve better performance in different target maneuver tracking. Simulations results show that the proposed adaptive...
Harmonic filter design consideration for a Tire-Rubber factory
, Article 5th IASTED International Conference on Power and Energy Systems, EuroPES 2005, Benalmadena, 15 June 2005 through 17 June 2005 ; 2005 , Pages 380-383 ; 14827891 (ISSN) ; Mokhtari, H ; Hamza M. H ; IASTED ; Sharif University of Technology
2005
Abstract
Increase in the number of non-linear loads has increased harmonic pollution in industries, resulting in lower power factor and more losses. Harmonics may also lead to adverse conditions in cases they match a resonance frequency existing in the system. To alleviate the problems of harmonics, tuned harmonic filters are used. However, design and installation of passive elements in power systems or industries requires special attentions due to the possible resonances that may occur. In this paper, a Tire-Rubber company is analyzed for a filter installation. Harmonic analysis is performed, and site measurements are examined. Cautions to be taken for design consideration are then discussed
Electric arc furnace power quality improvement using shunt active filter and series inductor
, Article IEEE TENCON 2004 - 2004 IEEE Region 10 Conference: Analog and Digital Techniques in Electrical Engineering, Chiang Mai, 21 November 2004 through 24 November 2004 ; Volume D , 2004 , Pages D105-D108 ; Parniani, M ; IEEE Region 10 ; Sharif University of Technology
2004
Abstract
This paper presents an investigation of power quality problems arising from electric arc furnace (EAF) operation, and the required compensating system capabilities. It also proposes a compensation system using a shunt active filter and a series inductor. A shunt active filter compensates for the reactive power and the current harmonics of the highly varying load. Reference signals for the compensation logic are obtained from the instantaneous current vector components on a rotating reference frame. Due to noninteger harmonics on voltages at the point of common coupling, conventional methods for the inverter dc bus voltage regulation fail to perform properly. Hence, a new method is introduced...
Mitigation of electric arc furnace disturbances using the unified power quality conditioner
, Article IECON 2004 - 30th Annual Conference of IEEE Industrial Electronics Society, Busan, 2 November 2004 through 6 November 2004 ; Volume 2 , 2004 , Pages 1469-1474 ; Parniani, M ; Mokhtari, H ; Sharif University of Technology
2004
Abstract
This paper discusses the application of unified power quality conditioner (UPQC) for improving power quality of a system supplying an electric arc furnace (EAF). The UPQC comprises a combined series and shunt active filters sharing a common DC link. It is used to mitigate voltage disturbances and compensate for reactive power, harmonics and interharmonics. A novel control strategy of the UPQC is presented. Since voltages at the point of common coupling (PCC) contain low frequency interharmonics, conventional methods can not be used for extracting voltage reference signals. In the proposed method, voltage references are extracted using active power processing to generate sinusoidal waveforms....
Speech modeling and voiced/unvoiced/mixed/silence speech segmentation with fractionally gaussian noise based models
, Article Proceedings - IEEE International Conference on Acoustics, Speech, and Signal Processing, Montreal, Que, 17 May 2004 through 21 May 2004 ; Volume 1 , 2004 , Pages I613-I616 ; 15206149 (ISSN) ; Shamsollahi, M. B ; Sharif University of Technology
2004
Abstract
The ARMA filtered fractionally differenced Gaussian Noise (FdGn) model and a new AR Filtered FdGn Added up model are applied to speech signal and performance of their parameters on speech Unvoiced/Voiced/Mixed/Silence classification is evaluated against Zero Crossing Rate (ZCR) feature. For parameter estimation of AR filtered FdGn model two methods were applied: iterative Maximum Likelihood (ML) method of Tewfik and a new computationally efficient Linear Minimum Square Error (LMSE) algorithm Also for parameters estimation of new Added up model two approaches were implemented: an Expectation-Maximization (EM) based approach and an iterative MSE approach. The described models and methods were...
A novel two frequency MTI radar
, Article Proceedings of the IEEE Radar Conference, Philadelphia, PA, 26 April 2004 through 29 April 2004 ; 2004 , Pages 589-591 ; Norouzi, Y ; Nayebi, M. M ; Sharif University of Technology
2004
Abstract
The paper introduced a new design for two-frequency MTI radar is introduced. The suggested system can change its frequencies, in each pulse. Therefore, the system is very resistive to electronic war. The analytical results of our calculation show that the system has very high blind speed and in realistic situations, it increases signal to noise ratio, although it widens clutter bandwidth and detects some spurious targets
ECG beat classification based on a cross-distance analysis
, Article 6th International Symposium on Signal Processing and Its Applications, ISSPA 2001, Kuala Lumpur, 13 August 2001 through 16 August 2001 ; Volume 1 , 2001 , Pages 234-237 ; 0780367030 (ISBN); 9780780367036 (ISBN) ; Nayebi, K ; Sharif University of Technology
IEEE Computer Society
2001
Abstract
This paper presents a multi-stage algorithm for QRS complex classification into normal and abnormal categories using an unsupervised sequential beat clustering and a cross-distance analysis algorithm. After the sequential beat clustering, a search algorithm based on relative similarity of created classes is used to detect the main normal class. Then other classes are labeled based on a distance measurement from the main normal class. Evaluated results on the MIT-BIH ECG database exhibits an error rate less than 1% for normal and abnormal discrimination and 0.2% for clustering of 15 types of arrhythmia existing on the MIT-BIH database. © 2001 IEEE
Spacecraft attitude and system identification via marginal modified unscented Kalman filter utilizing the sun and calibrated three-axis-magnetometer sensors
, Article Scientia Iranica ; Vol. 21, issue. 4 , 2014 , p. 1451-1460 ; Pourtakdoust, S. H ; Sharif University of Technology
Abstract
This paper deals with the problems of attitude determination, parameter identification and reference sensor calibration simultaneously. An LEO satellite's attitude, inertia tensor as well as calibration parameters of Three-Axis-Magnetometer (TAM) including scale factors, misalignments and biases along three body axes are estimated during a maneuver designed to satisfy the condition of persistency of excitation. The advanced nonlinear estimation algorithm of Unscented Kalman Filter (UKF) is a good choice for nonlinear estimation problem of attitude determination, but its computational cost is considerably larger than the widespread low accurate Extended Kalman Filter. Reduced Sigma Point...
Auxiliary unscented particle cardinalized probability hypothesis density
, Article 2013 21st Iranian Conference on Electrical Engineering, ICEE 2013, Mashhad ; 2013 ; 9781467356343 (ISBN) ; Behnia, F ; Sharif University of Technology
2013
Abstract
The probability hypothesis density (PHD) filter has been recently introduced by Mahler as a relief for the intractable computation of the optimal Bayesian multi-target filtering. It propagates the posterior intensity of the random finite set (RFS) of targets in time. Despite serving as a powerful decluttering algorithm, PHD filter still has the problem of large variance of the estimated expected number of targets. The cardinalized PHD (CPHD) filter overcomes this problem through jointly propagating the posterior intensity and the posterior cardinality distribution. Unfortunately, the particle filter implementation of the CPHD filter suffers from lack of an efficient method for boosting its...
Spacecraft attitude and system identification using marginal reduced UKF utilizing the sun and calibrated TAM sensors
, Article Applied Mechanics and Materials, 21 November 2012 through 22 November 2012 ; Volume 225 , November , 2012 , Pages 417-422 ; 16609336 (ISSN) ; 9783037855065 (ISBN) ; Pourtakdoust, S. H ; Sharif University of Technology
2012
Abstract
This paper deals with attitude determination, parameter identification and reference sensor calibration simultaneously. A LEO satellite's attitude, inertia tensor as well as calibration of Three-Axis-Magnetometer (TAM) are estimated during a maneuver designed to satisfy persistency of excitation condition. For this purpose, kinematic and kinetic state equations of spacecraft motion are augmented for the determination of inertia tensor and TAM calibration parameters including scale factors, misalignments and biases along three body axes. Attitude determination is a nonlinear estimation problem. Unscented Kalman Filter (UKF) as an advanced nonlinear estimation algorithm with good performance...
Mixed analog-digital crossbar-based hardware implementation of sign-sign LMS adaptive filter
, Article Analog Integrated Circuits and Signal Processing ; Volume 66, Issue 1 , 2011 , Pages 41-48 ; 09251030 (ISSN) ; Bagheri Shouraki, S ; Sharif University of Technology
Abstract
Recently announcement of a physical realization of a fundamental circuit element called memristor by researchers at Hewlett Packard (HP) has attracted so much interest worldwide. Combination of this newly found element with crossbar interconnect technology, opened a new field in designing configurable or programmable electronic systems which can have applications in signal processing and artificial intelligence. In this paper, based on the simple memristor crossbar structure, we will propose a new mixed analog-digital circuit as a hardware implementation of the sign-sign least mean square (LMS) adaptive filter algorithm. In this proposed hardware, any multiplication and addition is performed...
Direct coupled resonator filters realized by gap waveguide technology
, Article IEEE Transactions on Microwave Theory and Techniques ; Volume 63, Issue 10 , August , 2015 , Pages 3445-3452 ; 00189480 (ISSN) ; Banai, A ; Sharif University of Technology
Institute of Electrical and Electronics Engineers Inc
2015
Abstract
Novel types of narrow band filters based on the newly introduced gap waveguide technology are presented in this paper. The proposed filters have a central frequency of 35 GHz with approximately 1% fractional bandwidth. The filter resonators are composed of two separate plates and are manufactured by milling metallic blocks. The gap between the two metallic plates eliminates the need for electrical contact between them. This feature allows the resonators to be stacked in different layers. The filtering function is realized by producing a coupling between the stacked resonators. The measurement results of the manufactured filters are in good agreement with full-wave simulations, even without...
Ambient data-based online electromechanical mode estimation by error-feedback lattice RLS filter
, Article IEEE Transactions on Power Systems ; Volume 33, Issue 4 , July , 2018 , Pages 3745-3756 ; 08858950 (ISSN) ; Parniani, M ; Aminifar, F ; Sharif University of Technology
Institute of Electrical and Electronics Engineers Inc
2018
Abstract
This paper proposes a novel error-feedback lattice recursive least-squares (EF-LRLS) filter for online estimation of power system oscillatory modes. The EF-LRLS filter is applied to ambient data provided by phasor measurement units to identify the autoregressive (AR) model parameters. This filter has a modular structure; accordingly, if the length of the filter equals $N$, it identifies AR(1) to ${m{AR(}}N)$ models concurrently. In the proposed method, removing very low and high frequencies and resampling steps are fulfilled in an online fashion. This adaptive filter has less computational complexity than standard RLS filter, making it an appropriate choice for online system identification....
An N-Path filter design methodology with harmonic rejection, power reduction, foldback elimination, and spectrum shaping
, Article IEEE Transactions on Circuits and Systems I: Regular Papers ; Volume 67, Issue 12 , 2020 , Pages 4494-4506 ; Banaeikashani, A ; Behmanesh, B ; Atarodi, S. M ; Sharif University of Technology
Institute of Electrical and Electronics Engineers Inc
2020
Abstract
In this paper, an adaptive design methodology for synthesizing a harmonic free N-path filter with reduced frequency folding is presented. System level analysis of proposed architecture shows that by adding a few extra paths with proper weights to a conventional N-path filter, several characteristics such as harmonic rejection, power reduction, foldback elimination and spectrum shaping can be achieved. The designed filter is reconfigurable to be a band-pass filter (BPF) or a band-reject filter (notch), based on the requirements. By using the nth harmonic of Local Oscillator (LO) signal, instead of the fundamental harmonic, the required input clock frequency in N-phase clock generator is...
A nonlinear Bayesian filtering framework for ECG denoising
, Article IEEE Transactions on Biomedical Engineering ; Volume 54, Issue 12 , November , 2007 , Pages 2172-2185 ; 00189294 (ISSN) ; Shamsollahi, M. B ; Jutten, C ; Clifford, G. D ; Sharif University of Technology
2007
Abstract
In this paper, a nonlinear Bayesian filtering framework is proposed for the filtering of single channel noisy electrocardiogram (ECG) recordings. The necessary dynamic models of the ECG are based on a modified nonlinear dynamic model, previously suggested for the generation of a highly realistic synthetic ECG. A modified version of this model is used in several Bayesian filters, including the Extended Kalman Filter, Extended Kalman Smoother, and Unscented Kalman Filter. An automatic parameter selection method is also introduced, to facilitate the adaptation of the model parameters to a vast variety of ECGs. This approach is evaluated on several normal ECGs, by artificially adding white and...
A robust kalman filter-based approach for SoC estimation of lithium-ION batteries in smart homes
, Article Energies ; Volume 15, Issue 10 , 2022 ; 19961073 (ISSN) ; Habibifar, R ; Wang, Z ; Sharif University of Technology
MDPI
2022
Abstract
Battery energy systems are playing significant roles in smart homes, e.g., absorbing the uncertainty of solar energy from root-top photovoltaic, supplying energy during a power outage, and responding to dynamic electricity prices. For the safe and economic operation of batteries, an optimal battery-management system (BMS) is required. One of the most important features of a BMS is state-of-charge (SoC) estimation. This article presents a robust central-difference Kalman filter (CDKF) method for the SoC estimation of on-site lithium-ion batteries in smart homes. The state-space equations of the battery are derived based on the equivalent circuit model. The battery model includes two RC...
A filtering technique for three-phase power systems
, Article IEEE Transactions on Instrumentation and Measurement ; Volume 58, Issue 2 , 2009 , Pages 389-396 ; 00189456 (ISSN) ; Karimi, H ; Bakhshai, A. R ; Sharif University of Technology
Abstract
A novel filter for use in three-phase power systems is introduced. When the input to the filter is a balanced three-phase set of signals, the filter suppresses noise and distortions and extracts a smooth three-phase fundamental component. When the input signal to the filter is unbalanced, it extracts the fundamental positive-sequence component of the input signal. The filter also estimates the magnitude, phase angle, and frequency of the signal and adaptively follows the variations in all these three variables. The characteristics of the filter, including its mathematical equations, stability analysis, steady state, and dynamic responses, are discussed in this paper. The filter highly...
Ambient data-based online electromechanical mode estimation by error-feedback lattice RLS filter
, Article IEEE Transactions on Power Systems ; 2017 ; 08858950 (ISSN) ; Parniani, M ; Aminifar, F ; Sharif University of Technology
Abstract
This paper proposes a novel error-feedback lattice recursive least-squares (EF-LRLS) filter for online estimation of power system oscillatory modes. The EF-LRLS filter is applied to ambient data provided by phasor measurement units to identify the autoregressive (AR) model parameters. This filter has a modular structure; accordingly, if the length of the filter equals N, it identifies AR(1) to AR(N) models concurrently. In the proposed method, removing very low and high frequencies and re-sampling steps are fulfilled in an online fashion. This adaptive filter has less computational complexity than standard RLS filter, making it an appropriate choice for online system identification. The...