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Search results for: biomedical signal processing
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A fast time-frequency multi-window analysis using a tuning directional kernel
PublicationIn this paper, a novel approach for time-frequency analysis and detection, based on the chirplet transform and dedicated to non-stationary as well as multi-component signals, is presented. Its main purpose is the estimation of spectral energy, instantaneous frequency (IF), spectral delay (SD), and chirp rate (CR) with a high time-frequency resolution (separation ability) achieved by adaptive fitting of the transform kernel. We...
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Polynomial windows with low sidelobes’ level
PublicationSome of the main advantages of polynomial windows are their low computational complexity and ability to easily change their frequency response modifying the values of their coefficients in the time domain. Kulkarni presented the coefficients obtained for such windows with fastest possible decaying sidelobes...
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Karhunen-Loeve-based approach to tracking of rapidly fading wireless communication channels
PublicationWhen parameters of wireless communication channels vary at a fast rate, simple estimation algorithms, such as weighted least squares (WLS) or least mean squares (LMS) algorithms, cannot estimate them with the accuracy needed to secure the reliable operation of the underlying communication systems. In cases like this, the local basis function (LBF) estimation technique can be used instead, significantly increasing the achievable...
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Matrix-based robust joint fingerprinting and decryption method for multicast distribution of multimedia
PublicationThis paper addresses the problem of unauthorized redistribution of multimedia content by malicious users (pirates). The solution proposed here is a new joint fingerprinting and decryption method which meets the requirements for both imperceptibility and robustness of fingerprints and scalability in terms of design and distribution of fingerprinted multimedia content. The proposed method uses a simple block cipher based on matrix...
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Adaptive identification of sparse underwater acoustic channels with a mix of static and time-varying parameters
PublicationWe consider identification of sparse linear systems with a mix of static and time-varying parameters. Such systems are typical in underwater acoustics (UWA), for instance, in applications requiring identi- fication of the acoustic channel, such as UWA communications, navigation and continuous-wave sonar. The recently proposed fast local basis function (fLBF) algorithm provides high performance when identi- fying time-varying systems....
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Reversible data hiding in encrypted DICOM images using sorted binary sequences of pixels
PublicationIn this paper, a novel reversible data hiding method for encrypted DICOM images is proposed. The method utilizes binary decomposition of the input data paired with a sorting process of the obtained binary sequences to ensure efficient data embedding in each predefined data block for specific most significant bit (MSB) planes while exploiting the properties of run-length encoding. The proposed scheme is lossless, and based on the...
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Finite-window RLS algorithms
PublicationTwo recursive least-squares (RLS) adaptive filtering algorithms are most often used in practice, the exponential and sliding (rectangular) window RLS algorithms. This popularity is mainly due to existence of low-complexity versions of these algorithms. However, these two windows are not always the best choice for identification of fast time-varying systems, when the identification performance is most important. In this paper, we...
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Increasing accuracy of frequency estimation by decimation. W: [CD-ROM]EUSIPCO 2002. XI European Signal Processing Conference. Toulouse, France, September 3-6, 2002. [B.m.]: New Medias**2002 [4 s. 3 rys. bibliogr. 6 poz.] Page numbers in the proceedings: Volume 3, s. 135-138. Zwiększanie dokładności estymacji częstotliwości poprzez decymację.
PublicationArtykuł rozważa problem estymacji częstotliwości zaszumionego, sinusoidalne-go sygnału zespolonego. Częstotliwość wyznaczana jest w oparciu o autoregre-syjny model sygnału. W pracy wykazano, że wprowadzenie decymacji sygnału po-zwala na redukcję rzędu modelu autoregresyjnego, a tym samym powoduje znacz=ne zmniejszenie złożoności obliczeniowej metody.
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Improving listeners' experience for movie playback through enhancing dialogue clarity in soundtracks
PublicationThis paper presents a method for improving users' quality of experience through processing of movie soundtracks. The dialogue clarity enhancement algorithms were introduced for detecting dialogue in movie soundtrack mixes and then for amplifying the dialogue components. The front channel signals (left, right, center) are analyzed in the frequency domain. The selected partials in the center channel signal, which yield high disparity...
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Iterative learning approach to active noise control of highly autocorrelated signals with applications to machinery noise
PublicationThis paper discusses the design and application of iterative learning control (ILC) and repetitive control (RC) for high modal density systems. Typical examples of these systems are structural and acoustical systems considered in active structural acoustic control (ASAC) and active noise control (ANC) applications. The application of traditional ILC and RC design techniques, which are based on a parametric system model, on systems...
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Localization of impulsive disturbances in audio signals using template matching
PublicationIn this paper, a new solution to the problem of elimination of impulsive disturbances from audio signals, based on the matched filtering technique, is proposed. The new approach stems from the observation that a large proportion of noise pulses corrupting audio recordings have highly repetitive shapes that match several typical “patterns”. In many cases a representative set of exemplary pulse waveforms can be extracted from the...
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Self-tuning adaptive frequency tracker
PublicationAn automatic gain tuning algorithm is proposed for a recently introduced adaptive notch filter. Theoretical analysis and simulations show that, under Gaussian random-walk type assumptions, the proposed extension is capable of adjusting adaptation gains of the filter so as to minimize the mean-squared frequency tracking error without prior knowledge of the true frequency trajectory. A simplified one degree of freedom version of...
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Parallel frequency tracking with built-in performance evaluation
PublicationThe problem of estimation of instantaneous frequency of a nonstationary complex sinusoid (cisoid) buried in wideband noise is considered. The proposed approach employs a bank of adaptive notch filters, extended with a nontrivial performance assessment mechanism which automatically chooses the best performing filter in the bank. Additionally, a computationally attractive method of implementing the bank is proposed. The new structure...
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Identification of nonstationary multivariate autoregressive processes– Comparison of competitive and collaborative strategies for joint selection of estimation bandwidth and model order
PublicationThe problem of identification of multivariate autoregressive processes (systems or signals) with unknown and possibly time-varying model order and time-varying rate of parameter variation is considered and solved using parallel estimation approach. Under this approach, several local estimation algorithms, with different order and bandwidth settings, are run simultaneously and compared based on their predictive performance. First,...
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Full wavefield processing by using FCN for delamination detection
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Deep learning based segmentation using full wavefield processing for delamination identification: A comparative study
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Statistically efficient smoothing algorithm for time-varying frequency estimation
PublicationThe problem of extraction/elimination of a nonstationary sinusoidal signal from noisy measurements is considered. This problem is usually solved using adaptive notch filtering (ANF) algorithms. It is shown that the accuracy of frequency estimates can be significantly increased if the results obtained from ANF are backward-time filtered by an appropriately designed lowpass filter. The resulting adaptive notch smoothing (ANS) algorithm...
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Damage localisation in a stiffened plate structure using a propagating wave
PublicationThe paper presents an application of changes in propagating waves for damage detection in a stiffened aluminium plate. The experimental investigation was conducted on an aluminium plate with riveted two L-shape stiffeners. The wave has been excited with a piezoelectric transducer and measured with the Laser Scanning Doppler Vibrometer. Recorded signals were analysed using the special signal processing techniques developed for damage...
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The instantaneous frequency rate spectogram
PublicationAn accelerogram of the instantaneous phase of signal components referred to as an instantaneous frequency rate spectrogram (IFRS) is presented as a joint time-frequency distribution. The distribution is directly obtained by processing the short-time Fourier transform (STFT) locally. A novel approach to amplitude demodulation based upon the reassignment method is introduced as a useful by-product. Additionally, an estimator of energy...
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Generalized adaptive notch smoothers for real-valued signals and systems
PublicationSystems with quasi-periodically varying coefficients can be tracked using the algorithms known as generalized adaptive notch filters (GANFs). GANF algorithms can be considered an extension, to the system case, of classical adaptive notch filters (ANFs). We show that estimation accuracy of the existing algorithms, as well as their robustness to the choice of design parameters, can be considerably improved by means of compensating...
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New Algorithms for Adaptive Notch Smoothing
PublicationThe problem of extraction/elimination of a nonstationary complex sinusoidal signal buried in noise is considered. This problem is usually solved using adaptive notch filtering (ANF)algorithms. It is shown that accuracy of signal estimation can be increased if the results obtained from ANF are further processed using a cascade of appropriately designed filters. The resulting adaptive notch smoothing (ANS) algorithms can be employed...
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A modified method of vibration surveillance by using the optimal control at energy performance index
PublicationA method of vibration surveillance by using the optimal control at energy performance index has been creatively modified. The suggested original modification depends on consideration of direct relationship between the measured acceleration signal and the optimal control command. The paper presents the results of experiments and Hardware- in-the-loop simulations of a new active vibration reduction algorithm based on the energy...
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New semi-causal and noncausal techniques for detection of impulsive disturbances in multivariate signals with audio applications
PublicationThis paper deals with the problem of localization of impulsive disturbances in nonstationary multivariate signals. Both unidirectional and bidirectional (noncausal) detection schemes are proposed. It is shown that the strengthened pulse detection rule, which combines analysis of one-step-ahead signal prediction errors with critical evaluation of leave-one-out signal interpolation errors, allows one to noticeably improve detection results...
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Dynamic mass measurement in checkweighers using a discrete time-variant low-pass filter
PublicationConveyor belt type checkweighers are complex mechanical systems consisting of a weighing sensor (strain gauge load cell, electrodynamically compensated load cell), packages (of different shapes, made of different materials) and a transport system (motors, gears, rollers). Disturbances generated by the vibrating parts of such a system are reflected in the signal power spectra in a form of strong spectral peaks, located usually in...
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A simple way of increasing estimation accuracy of generalized adaptive notch filters
PublicationGeneralized adaptive notch filters are used for identification/tracking of quasi-periodically varying dynamic systems and can be considered an extension, to the system case, of classical adaptive notch filters. It is shown that frequency biases, which arisein generalized adaptive notch filtering algorithms, can be significantly reduced by incorporating in the adaptive loop an appropriately chosen decision delay. The resulting performance...
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Generalized adaptive notch smoothing revisited
PublicationThe problem of identification of quasi-periodically varying dynamic systems is considered. This problem can be solved using generalized adaptive notch filtering (GANF) algorithms. It is shown that the accuracy of parameter estimates can be significantly increased if the results obtained from GANF are further processed using a cascade of appropriately designed filters. The resulting generalized adaptive notch smoothing (GANS) algorithm...
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On DoA estimation for rotating arrays using stochastic maximum likelihood approach
PublicationThe flexibility needed to construct DoA estimators that can be used with rotating arrays subject to rapid variations of the signal frequency is offered by the stochastic maximum likelihood approach. Using a combination of analytic methods and Monte Carlo simulations, we show that for low and moderate source correlations the stochastic maximum likelihood estimator that assumes noncorrelated sources has accuracy comparable to the...
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Chirp Rate and Instantaneous Frequency Estimation: Application to Recursive Vertical Synchrosqueezing
PublicationThis letter introduces new chirp rate and instantaneous frequency estimators designed for frequency-modulated signals. These estimators are first investigated from a deterministic point of view, then compared together in terms of statistical efficiency. They are also used to design new recursive versions of the vertically synchrosqueezed short-time Fourier transform, using a previously published method (D. Fourer, F. Auger, and...
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Frequency Guided Generalized Adaptive Notch Filtering - Tracking Analysis and Optimization
PublicationGeneralized adaptive notch filters (GANFs) are estimators of coefficients of quasi-periodically time-varying systems, encountered e.g., in RF applications when Doppler effect takes place. Current state of the art GANFs can deliver highly accurate estimates of system variations’ frequency, but underperform in terms of accuracy of system coefficient estimates. The paper proposes a novel multistage GANF with improved coefficient...
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Active Control of Highly Autocorrelated Machinery Noise in Multivariate Nonminimum Phase Systems
PublicationIn this paper, a novel multivariate active noise control scheme, designed to attenuate disturbances with high autocorrelation characteristics and preserve background signals, is proposed. The algorithm belongs to the class of feedback controllers and, unlike the popular feedforward FX-LMS approach, does not require availability of a reference signal. The proposed approach draws its inspiration from the iterative learning control...
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An Ultra-Low-Energy Analog Comparator for A/D Converters in CMOS Image Sensors
PublicationThis paper proposes a new solution of an ultra-low-energy analog comparator, dedicated to slope analog-to-digital converters (ADC), particularly suited for CMOS image sensors (CISs) featuring a large number of ADCs. For massively parallel imaging arrays, this number may be as high as tens-hundreds of thousands ADCs. As each ADC includes an analog comparator, the number of these comparators in CIS is always high. Detailed analysis...
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A three-dimensional periodic beam for vibroacoustic isolation purposes
PublicationThis paper presents results of investigations on a three-dimensional (3-D) isotropic periodic beam. The beam can represent a vibroacoustic isolator of optimised dynamic characteristics in the case of its longitudinal, flexural and torsional behaviour. The optimisation process concerned both the widths as well as the positions of particular frequency band gaps that are present in the frequency spectrum of the beam. Since the dynamic...
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On Noncausal Identification of Nonstationary Multivariate Autoregressive Processes
PublicationThe problem of identification of nonstationary multivariate autoregressive processes using noncausal local estimation schemes is considered and a new approach to joint selection of the model order and the estimation bandwidth is proposed. The new selection rule, based on evaluation of pseudoprediction errors, is compared with the previously proposed one, based on the modified Akaike’s final prediction error criterion.
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Variable Fractional Delay Filter Design Using a Symmetric Window
PublicationIn this paper a numerically efficient method for designing a nearly optimal variable fractional delay (VFD) filter based on a simple and well-known window method is presented. In the proposed method a single window extracted from the optimal filter with fixed fractional delay (FD) is divided into even and odd part. Subsequently, the odd part is discarded and symmetric even part of the extracted window is used to design a family...
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Systematic approach to binary classification of images in video streams using shifting time windows
Publicationin the paper, after pointing out of realistic recordings and classifications of their frames, we propose a new shifting time window approach for improving binary classifications. We consider image classification in tewo steps. in the first one the well known binary classification algorithms are used for each image separately. In the second step the results of the previous step mare analysed in relatively short sequences of consecutive...
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Damage identification by wavelet analysis
PublicationW pracy omówiono metodę identyfikacji rodzaju nieciagłości w 1 wymiarowych elementach konstrukcji wykorzystującą pomiar propagacji fali sprężystej i jej analizę metodą transformacji falkowej.
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Damage identification by wavelet analysis
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Tracking analysis of a generalized adaptive notch filter
PublicationUogólniony adaptacyjny filtr wycinający służy do identyfikacji obiektów zmieniających się w sposób pseudookresowy. W pracy przedstawiono analizę własności śledzących takiego filtru a także omówiono zasady jego strojenia.
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Generalized adaptive notch filter with a self-optimization capability
PublicationW pracy przedstawiono samonastrajalny wariant tzw. uogólnionego adaptacyjnego filtru wycinającego. Automatycznym strojeniem objęte są dwa współczynniki wzmocnienia adaptacji, odpowiedzialne za śledzenie amplitud i częstotliwości parametrów identyfikowanego obiektu.
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Research and applications of active bearings: A state-of-the-art review
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Deep learning super-resolution for the reconstruction of full wavefield of Lamb waves
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Towards homoscedastic nonlinear cointegration for structural health monitoring
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Predicting the seismic collapse capacity of adjacent SMRFs retrofitted with fluid viscous dampers in pounding condition
PublicationSevere damages of adjacent structures due to structural pounding during earthquakes have emphasized the need to use some seismic retrofit strategy to enhance the structural performance. The purpose of this paper is to study the influence of using linear and nonlinear Fluid Viscous Dampers (FVDs) on the seismic collapse capacities of adjacent structures prone to pounding and proposing modification factors to modify the median...
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On tracking properties of real-valued generalized adaptive notch filters
PublicationGeneralized adaptive notch filters (GANFs) are used for identification/tracking of quasi-periodically varying dynamic systems and can be considered an extension, to the system case, of classical adaptive notch filters. The paper presents results of local performance analysis of a real-valued GANF algorithm, i.e., algorithm designed to track parameters of a real-valued system. This is an extension of the previous work which focused...
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Toward Wide-Band High-Resolution Analog-to-Digital Converters Using Hybrid Filter Bank Architecture
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Fast algorithms for identyfication of periodiccaly varying systems.
PublicationPraca dotyczy identyfikacji obiektów o parametrach zmieniających się w sposób okresowy. Zaproponowane algorytmy śledzenia parametrów cechują się niską złożonością obliczeniową, typową dla podejścia gradientowego a zarazem wysoką jakością śledzenia typową dla złożonych algorytmów opartych na metodzie funkcji bazowych.
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Fast recursive basis function estimators for identification of time-varying processes
PublicationW pracy wprowadzono nową kategorię filtrów adaptacyjnych opartych na metodzie funkcji bazowych i wykorzystujących koncepcję postfiltracji. Proponowane algorytmy pozwalają połączyć niską złożoność obliczeniową i dobre właściwości śledzące.
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Synthesis and biological evaluation of 2,7-Dihydro-3H-dibenzo[de,h]cinnoli- ne-3,7-done derivatives a novel group of anticancer agents active on a multidrug resistance cell line.
PublicationZsyntezowano serię pochodnych pirydazonu z jednym lub dwoma łańcuchami bocznymi w różnych pozycjach chromoforu tetracyklicznego. Związki wykazały aktywność cytoksyczną na mysią białaczkę L1210 i ludzką k562 oraz na linii komórkowej oporności krzyżowej MDR (k562/DX). Dwa najbardziej aktywne związki przetestowano in vivo na mysiej białaczce P388. Wykazały one aktywność przeciwnowotworową porównywalną z aktywnością Mitoxantronu.
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Comments on “Closed Form Variable Fractional Time Delay Using FFT”
PublicationIn this letter drawbacks of the aforementioned paper are pointed out. The proposed approach is improved with minor modifications of the discrete frequency response. This allows for design of fractional delay filters which are close to optimal and can be efficiently implemented in the frequency domain using the sliding DFT based structure. Alternatively, the derived equivalent closed form formulae for offset windows can be used...
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Prediction of maximum tensile stress in plain-weave composite laminates with interacting holes via stacked machine learning algorithms: A comparative study
PublicationPlain weave composite is a long-lasting type of fabric composite that is stable enough when being handled. Open-hole composites have been widely used in industry, though they have weak structural performance and complex design processes. An extensive number of material/geometry parameters have been utilized for designing these composites, thereby an efficient computational tool is essential for that purpose. Different Machine Learning...