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Search results for: ANALYSIS OF NONSTATIONARY SIGNALS
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Chirp-rate estimation of FM signals in the time-frequency domain
PublicationNovel dynamic representations of a complex signal in the time-frequency domain including: a channelized instantaneous complex frequency (CICF), a complex local group delay (CLGD) and a channelized instantaneous chirp-rate (CICR) are introduced. The proposed approach is based on the use of the gradient of the short-time Fourier transform complex phase. An interpretation of the newly-introduced distributions especially of the CICR...
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Fast Basis Function Estimators for Identification of Nonstationary Stochastic Processes
PublicationThe problem of identification of a linear nonsta-tionary stochastic process is considered and solved using theapproach based on functional series approximation of time-varying parameter trajectories. The proposed fast basis func-tion estimators are computationally attractive and yield resultsthat are better than those provided by the local least squaresalgorithms. It is shown that two...
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Parametric impulsive noise detector for corrupted audio signals based on hidden Markow model
PublicationThe paper addresses the problem of impulsive noise detection for audio signals. A structure of threshold parameter detectors using modelingof signals was introduced. the algorithm of the noise detection, based on discrete-time hidden Markow model (HMM)of whitened audio signal is elaborated
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Suppression of distortions in signals received from Doppler sensor for vehicle speed measurement
PublicationDoppler sensors are commonly used for movement detection and speed measurement. However, electromagnetic interference and imperfections in sensor construction result in degradation of the signal to noise ratio. As a result, detection of signals reflected from moving objects becomes problematic. The paper proposes an algorithm for reduction of distortions and noise in the signal received from a simple, dual-channel type of a Doppler...
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Radio reception signals II 2023/2024
e-Learning CoursesKurs będzie narzędziem pomocniczym przy realizacji laboratorium z tego przedmiotu.
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Data Analysis 2023/24
e-Learning CoursesData Analysisdr inż. Karol Flisikowski, prof. PG - winter semester 2023/24
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Enhanced voice user interface employing spatial filtration of signals from acoustic vector sensor
PublicationSpatial filtration of sound is introduced to enhance speech recognition accuracy in noisy conditions. An acoustic vector sensor (AVS) is employed. The signals from the AVS probe are processed in order to attenuate the surrounding noise. As a result the signal to noise ratio is increased. An experiment is featured in which speech signals are disturbed by babble noise. The signals before and after spatial filtration are processed...
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Elimination of clicks from archive speech signals using sparse autoregressive modeling
PublicationThis paper presents a new approach to elimination of impulsivedisturbances from archive speech signals. The proposedsparse autoregressive (SAR) signal representation is given ina factorized form - the model is a cascade of the so-called formantfilter and pitch filter. Such a technique has been widelyused in code-excited linear prediction (CELP) systems, as itguarantees model stability. After detection of noise pulses usinglinear...
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Application of the Fractional Fourier Transform for dispersion compensation in signals from a fiber-based Fabry-Perot interferometer
PublicationOptical methods of measurement do not require contact of a probe and the object under study, and thus have found use in a broad range of applications such as nondestructive testing (NDT), where noninvasive measurement is crucial. Measuring the refractive index of a material can give a valuable insight into its composition. Low‑coherence radiation sources enable measurement of the sample’s properties across a wide spectrum, while...
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Comparison of Methods for Real and Imaginary Motion Classification from EEG Signals
PublicationA method for feature extraction and results of classification of EEG signals obtained from performed and imagined motion are presented. A set of 615 features was obtained to serve for the recognition of type and laterality of motion using 8 different classifications approaches. A comparison of achieved classifiers accuracy is presented in the paper, and then conclusions and discussion are provided. Among applied algorithms the...
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Simulation of incremental encoder signals
PublicationPrzedstawiono generator sygnału impulsowego do symulacji sygnału z przetwornika obrotowo-impulsowego w stanach przejściowych. Omówiono algorytmy wyznaczenia przedziałów międzyimpulsowych dla trzech rodzajów zmian prędkości obrotowej: liniowej, wykładniczej oraz sinusoidalnej. Przeanalizowano błędy kwantowania wynikające z cyfrowej realizacji generatora.
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Komputerowo wspomagana analiza elastycznych siłowników elektrostatycznych dla potrzeb implementacji w systemach mechatroniki
PublicationPrzeprowadzone badania naukowe rozpoczęto od szczegółowej analizy układu mechatronicznego dłoni robotycznych, powstałych na przestrzeni ostatnich 40 lat, w celu dokładnego rozpoznania ich głównych wymogów konstrukcyjnych i ograniczeń systemowych. Z uwagi na brak dostępnych narzędzi do symulacji omawianych siłowników, w rozprawie opracowano uniwersalne narzędzie – program do analizy numerycznej. U jego podstawy założono wykorzystanie...
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Reception of Radio Signals II 2024/2025
e-Learning CoursesKurs będzie narzędziem pomocniczym przy realizacji laboratorium z tego przedmiotu.
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Sparse vector autoregressive modeling of audio signals and its application to the elimination of impulsive disturbances
PublicationArchive audio files are often corrupted by impulsive disturbances, such as clicks, pops and record scratches. This paper presents a new method for elimination of impulsive disturbances from stereo audio signals. The proposed approach is based on a sparse vector autoregressive signal model, made up of two components: one taking care of short-term signal correlations, and the other one taking care of long-term correlations. The method...
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Locally-adaptive Kalman smoothing approach to identification of nonstationary stochastic systems
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Macroeconomic analysis
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Market analysis
e-Learning CoursesKurs przeznaczony dla studentów studiów stacjonarnych Inżynierii Danych, I stopnia, semestr 7 (zimowy) w roku akademickim 2021/2022.
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Financial Analysis
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Decision analysis
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Detection and Direction-of-Arrival Estimation of Weak Spread Spectrum Signals Received with Antenna Array
PublicationThis paper presents a method for the joint detection and direction of arrival (DOA) estimation of low probability of detection (LPD) signals. The proposed approach is based on using the antenna array to receive spread-spectrum signals hidden below the noise floor. Array processing exploits the spatial correlation between phase-delayed copies of the signal and allows us to evaluate the parameter used to make the decision about the...
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New First - Path Detector for LTE Positioning Reference Signals
PublicationIn today's world, where positioning applications reached a huge popularity and became virtually ubiquitous, there is a strong need for determining a device location as accurately as possible. A particularly important role in positioning play cellular networks, such as Long Term Evolution (LTE). In the LTE Observed Time Difference of Arrival (OTDOA) positioning method, precision of device location estimation depends on accuracy...
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Direct modulation for conventional matrix converters using analytical signals and barycentric coordinates
PublicationThis paper proposes the generalized direct modulation for Conventional Matrix Converters (CMC) using the concept of analytical signals and barycentric coordinates. The paper proposes a novel approach to the Pulse Width Modulation (PWM) duty cycle computing, which allows faster prototyping of direct control algorithms. The explanation of the new idea using analytical considerations demonstrating the principles of direct voltage...
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Propagation of initially sawtooth periodic and impulsive signals in a quasi-isentropic magnetic gas
PublicationThe characteristics of propagation of sawtooth periodic and impulsive signals at a transducer are analytically studied in this work. A plasma under consideration is motionless and uniform at equilibrium, and its perturbations are described by a system of ideal magnetohydrodynamic equations. Some generic heating/cooling function, which in turn depends on equilibrium thermodynamic parameters, may destroy adiabaticity of a flow and...
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Investigations of the Methods of Time Delay Measurement of Stochastic Signals Using Cross-correlation with the Hilbert Transform
PublicationThe article presents the results of simulation studies of four methods of estimating time delay for random signals using cross-correlation with the Hilbert Transform. Selected models of mutually delayed stochastic signals were used in the simulations, corresponding to the signals obtained from scintillation detectors in radioisotope measurements of liquid-gas two-phase flow. Standard deviations of the values of the individual functions...
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Global Optimization for Recovery of Clipped Signals Corrupted With Poisson-Gaussian Noise
PublicationWe study a variational formulation for reconstructing nonlinearly distorted signals corrupted with a Poisson-Gaussian noise. In this situation, the data fidelity term consists of a sum of a weighted least squares term and a logarithmic one. Both of them are precomposed by a nonlinearity, modelling a clipping effect, which is assumed to be rational. A regularization term, being a piecewise rational approximation of the ℓ0 function...
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Rough Set-Based Classification of EEG Signals Related to Real and Imagery Motion
PublicationA rough set-based approach to classification of EEG signals registered while subjects were performing real and imagery motions is presented in the paper. The appropriate subset of EEG channels is selected, the recordings are segmented, and features are extracted, based on time-frequency decomposition of the signal. Rough set classifier is trained in several scenarios, comparing accuracy of classification for real and imagery motion....
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Comparison of Classification Methods for EEG Signals of Real and Imaginary Motion
PublicationThe classification of EEG signals provides an important element of brain-computer interface (BCI) applications, underlying an efficient interaction between a human and a computer application. The BCI applications can be especially useful for people with disabilities. Numerous experiments aim at recognition of motion intent of left or right hand being useful for locked-in-state or paralyzed subjects in controlling computer applications....
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Systematic Literature Review for Emotion Recognition from EEG Signals
PublicationResearchers have recently become increasingly interested in recognizing emotions from electroencephalogram (EEG) signals and many studies utilizing different approaches have been conducted in this field. For the purposes of this work, we performed a systematic literature review including over 40 articles in order to identify the best set of methods for the emotion recognition problem. Our work collects information about the most...
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Systematic Literature Review for Emotion Recognition from EEG Signals
PublicationResearchers have recently become increasingly interested in recognizing emotions from electroencephalogram (EEG) signals and many studies utilizing different approaches have been conducted in this field. For the purposes of this work, we performed a systematic literature review including over 40 articles in order to identify the best set of methods for the emotion recognition problem. Our work collects information about the most...
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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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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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Physics augmented classification of fNIRS signals
PublicationBackground. Predictive classification favours performance over semantics. In traditional predictive classification pipelines, feature engineering is often oblivious to the underlying phenomena. Hypothesis. In applied domains such as functional Near Infrared Spectroscopy (fNIRS), the exploitation of physical knowledge may improve the discriminative quality of our observation set. Aims. Give exemplary evidence that intervening the...
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Localization of impulsive disturbances in archive audio signals using predictive matched filtering
PublicationThe problem of elimination of impulsive disturbances from archive audio signals is considered and its new solution, called predictive matched filtering, is proposed. The new approach is based on the observation that a large percentage of noise pulses corrupting archive audio recordings have highly repetitive shapes that match several typical “patterns”, called click templates. To localize noise pulses, click templates can be correlated...
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The influence of accumulation area and the length of pedestrian route on functioning of roundabouts with traffic signals
Publicationtraffic volumes. This kind of intersection is commonly used in the centres of Polish cities on multilane roads and fairly common in the case of tram lines running through a central island. The increase of traffic flow volumes on left turn and U-turn has made this type of roundabout difficult to operate. Small storage areas around central islands are critical places that significantly influence the capacity of this kind of intersection....
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Decision analysis (l/lab) winter 2020/21
e-Learning CoursesDecision analysis (l/lab)_winter 2020/21
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Deep neural networks for data analysis
e-Learning CoursesThe aim of the course is to familiarize students with the methods of deep learning for advanced data analysis. Typical areas of application of these types of methods include: image classification, speech recognition and natural language understanding. Celem przedmiotu jest zapoznanie studentów z metodami głębokiego uczenia maszynowego na potrzeby zaawansowanej analizy danych. Do typowych obszarów zastosowań tego typu metod należą:...
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Wave propagation signals in concrete beams under 3-point bending
Open Research DataThe DataSet contains the results of the mechanical behaviour of a concrete beams with dimensions 40 x 40 x 160 cm3under the 3-point bending. The beams were made of concrete with the following ingredients: CEM I 42.5R (450 kg/m3), water (177 kg/m3), sand 0-2 (675 kg/m3) and gravel 2-8 (675 kg/m3). The bending test was performed using a Zwick/Roell Z10...
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Application of Complementary Signals in Built-In Self Testers for Mixed-Signal Embedded Electronic Systems
PublicationThis paper concerns the implementation of shape-designed complementary signals (CSs), matched to the frequency characteristic of the circuit under test, in built-in self testers (BISTs), dedicated to mixed-signal embedded electronic systems for testing their analog sections. The essence of the proposed method and solution of CS BIST is low-cost realization on the base of hardware and software resources of microcontrollers used...
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Position Estimation in Mixed Indoor-Outdoor Environment Using Signals of Opportunity and Deep Learning Approach
PublicationTo improve the user's localization estimation in indoor and outdoor environment a novel radiolocalization system using deep learning dedicated to work both in indoor and outdoor environment is proposed. It is based on the radio signatures using radio signals of opportunity from LTE an WiFi networks. The measurements of channel state estimators from LTE network and from WiFi network are taken by using the developed application....
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A novel method of local chirp-rate estimation of LFM chirp signals in the time-frequency domain
PublicationIn the paper, novel dynamic representations of a complex signal in the time-frequency domain are introduced. The proposed approach is based on using the gradient of the short-time Fourier transform complex phase. A channelized instantaneous complex frequency (CICF) and a complex local group delay (CLGD) are included in the presented signal representations. An application of the newly-introduced distributions is demonstrated by...
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METHODS OF QUANTITATIVE ANALYSIS (TEAM PROJECT) (2022/2023)
e-Learning CoursesMETHODS OF QUANTITATIVE ANALYSIS (TEAM PROJECT) - Economic Analytics, Lecture and Lab, Winter Semester 2022/2022. Teacher: dr Piotr Paradowski
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A method of identification of RTS components in noise signals
PublicationW artykule przedstawiono oryginalną metodę wydzielania szumu RTS (Random Telegraph Signal) - dwupoziomowego lub wielopoziomowego - z sygnału szumowego. Podstawą oceny jakości metody jest założenie, że wartości chwilowe szumu RTS mają rozkład niegaussowski natomiast pozostała część sygnału ma rozkład gaussowski.Algorytm identyfikacji wielopoziomowych szumów RTS w sygnałach szumowych małej częstotliwości oparty został na aproksymacji...
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Application of nonlinearity measures to chemical sensor signals
PublicationSzumy rezystancji sensorów gazu zawierają istotną informację, która może być przedstawiona nie tylko przez ich gęstość widmową mocy. Analiza tych szumów za pomocą różnych miar nieliniowości może prowadzić do znacznego wzrostu selektywności i czułości czujników gazu. Stwierdzono, że dla dostępnych na rynku czujników gazu zastosowanie funkcji bispektrum dostarcza dodatkowej informacji, potrzebnej do detekcji różnych gazów. Analizując...
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Adaptive filter for reconstruction of stereo audio signals.
PublicationArtykuł poświęcony jest omówieniu metody rekonstrukcji zakłóconych impulsowo sygnałów stereofonicznych. W pracy zdefiniowano model sygnału stereofonicznego i przedstawiono zaprojektowany dla tego modelu filtr Kalmana. Przedstawiono modyfikacje filtru, w wyniku których algorytm dokonuje rekonstrukcji zakłóconego impulsowo sygnału w jednym kanale z wykorzystaniem dodatkowej informacji zawartej w niezakłóconych próbkach sygnału pochodzącego...
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Selected aspects of modern X-ray structural analysis 2024
e-Learning CoursesSelected Aspects of Modern X-ray Structural Analysis
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Selected Aspects of Modern X-ray Structural Analysis 2023
e-Learning CoursesSelected Aspects of Modern X-ray Structural Analysis
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Signals of the 5G Standalone Radio Interface
Open Research DataThe research work conducted within the scope of NATO-STO (North Atlantic Treaty Organization – Science and Technology Organization) IST-187 group assumed investigation of the 5G gNodeB performance. The downlink (DL) signals of the FDD (Frequency Division Duplex) 5G-Standalone station were registered in isolated and controlled laboratory conditions....
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Distortion of speech signals in the listening area: its mechanism and measurements
PublicationThe paper deals with a problem of the influence of the number and distribution of loudspeakers in speech reinforcement systems on the quality of publicly addressed voice messages, namely on speech intelligibility in the listening area. Linear superposition of time-shifted broadband waves of a same form and slightly different magnitudes that reach a listener from numerous coherent sources, is accompanied by interference effects...
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Technika odbioru radiowego (Reception of Radio Signals) - 2023/2024
e-Learning CoursesZajęcia przeznaczone są dla studentów 1. semestru studiów II stopnia. Celem przedmiotu jest zapoznanie z teorią i praktycznymi zagadnieniami z odbioru radiowego ze szczególnym uwzględnieniem odbiorników cyfrowych.
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Fundamentals of microscopic analysis
e-Learning Courses