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    Wyświetlanie 1-13 z 13
    Tytuł:
    Algorytm identyfikacji składowych sinusoidalnych złożonego sygnału na podstawie jego losowo pobranych próbek
    Sinusoidal signal components identification algorithm based on limited number of its random samples
    Autorzy:
    Kardasz, P.
    Powiązania:
    https://bibliotekanauki.pl/articles/377152.pdf
    Data publikacji:
    2013
    Wydawca:
    Politechnika Poznańska. Wydawnictwo Politechniki Poznańskiej
    Tematy:
    sygnał złożony
    składowe sinusoidalne złożonego sygnału
    Compressed Sensing
    identyfikacja parametrów sygnału
    algorytm identyfikacji
    Opis:
    W artykule przedstawiono algorytm estymacji parametrów składowych sinusoidalnych złożonego sygnału, na podstawie ograniczonej liczby losowo pobranych próbek tego sygnału. Działanie algorytmu zostało zbadane na przykładach kilku sygnałów, które stanowią sumę składowych sinusoidalnych o różnych amplitudach i częstotliwościach. Wyniki eksperymentu pokazują, że proponowany algorytm jest w stanie zidentyfikować i określić parametry składowych sinusoidalnych badanego sygnału o największej amplitudzie. Wyniki działania badanego algorytmu mogą stanowić punkt wyjścia dla bardziej zaawansowanych metod identyfikacji składowych takiego sygnału, takich jak algorytmy ewolucyjne. W artykule zostało zbadane zachowanie się proponowanego algorytmu i dokładność otrzymanych wyników w zależności od parametrów i liczby próbek użytych w procedurze identyfikacji składowych sygnału. Zostały również zarysowane kierunki dalszych badań nad udoskonaleniem algorytmu.
    The paper presents an algorithm for sinusoidal signal components estimation based on a limited number of random samples of this signal. The algorithm was tested on several examples of signals that are the sum of sinusoidal components having different amplitudes and frequencies. The experimental results show that the proposed algorithm is able to identify and determine the parameters of sinusoidal components of the test signal with the highest amplitudes. The results of the test algorithm can provide a starting point for more advanced ways to identify components of such signals, such as evolutionary algorithms. The behavior of the proposed algorithm, and the accuracy of the results obtained, depending on the parameters used and the number of samples to reconstruct the signal was tested. The directions for further research to improve the algorithm are outlined.
    Źródło:
    Poznan University of Technology Academic Journals. Electrical Engineering; 2013, 76; 197-203
    1897-0737
    Pojawia się w:
    Poznan University of Technology Academic Journals. Electrical Engineering
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    An unscented transformation approach to stochastic analysis of measurement uncertainty in magnet resonance imaging with applications in engineering
    Autorzy:
    Rauh, Andreas
    John, Kristine
    Wüstenhagen, Carolin
    Bruschewski, Martin
    Grundmann, Sven
    Powiązania:
    https://bibliotekanauki.pl/articles/1838185.pdf
    Data publikacji:
    2021
    Wydawca:
    Uniwersytet Zielonogórski. Oficyna Wydawnicza
    Tematy:
    magnet resonance imaging
    compressed sensing
    stochastic uncertainty
    unscented transformation
    rezonans magnetyczny
    próbkowanie oszczędne
    niepewność stochastyczna
    Opis:
    In the frame of stochastic filtering for nonlinear (discrete-time) dynamic systems, the unscented transformation plays a vital role in predicting state information from one time step to another and correcting a priori knowledge of uncertain state estimates by available measured data corrupted by random noise. In contrast to linearization-based techniques, such as the extended Kalman filter, the use of an unscented transformation not only allows an approximation of a nonlinear process or measurement model in terms of a first-order Taylor series expansion at a single operating point, but it also leads to an enhanced quantification of the first two moments of a stochastic probability distribution by a large signal-like sampling of the state space at the so-called sigma points which are chosen in a deterministic manner. In this paper, a novel application of the unscented transformation technique is presented for the stochastic analysis of measurement uncertainty in magnet resonance imaging (MRI). A representative benchmark scenario from the field of velocimetry for engineering applications which is based on measured data gathered at an MRI scanner concludes this contribution.
    Źródło:
    International Journal of Applied Mathematics and Computer Science; 2021, 31, 1; 73-83
    1641-876X
    2083-8492
    Pojawia się w:
    International Journal of Applied Mathematics and Computer Science
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Application of the compress sensing theory for improvement of the TOF resolution in a novel J-PET instrument
    Autorzy:
    Raczyński, L.
    Moskal, P.
    Kowalski, P.
    Wiślicki, W.
    Bednarski, T.
    Białas, P.
    Czerwiński, E.
    Gajos, A.
    Kapłon, Ł.
    Kochanowski, A.
    Korcyl, G.
    Kowal, J.
    Kozik, T.
    Krzemień, W.
    Kubicz, E.
    Niedźwiecki, S.
    Pałka, M.
    Rudy, Z.
    Salabura, P.
    Gupta-Sharma, N.
    Silarski, M.
    Słomski, A.
    Smyrski, J.
    Strzelecki, A.
    Wieczorek, A.
    Zieliński, M.
    Zoń, N.
    Powiązania:
    https://bibliotekanauki.pl/articles/146280.pdf
    Data publikacji:
    2016
    Wydawca:
    Instytut Chemii i Techniki Jądrowej
    Tematy:
    compressed sensing
    positron emission tomography
    time-of-flight
    Opis:
    Nowadays, in positron emission tomography (PET) systems, a time of fl ight (TOF) information is used to improve the image reconstruction process. In TOF-PET, fast detectors are able to measure the difference in the arrival time of the two gamma rays, with the precision enabling to shorten signifi cantly a range along the line-of-response (LOR) where the annihilation occurred. In the new concept, called J-PET scanner, gamma rays are detected in plastic scintillators. In a single strip of J-PET system, time values are obtained by probing signals in the amplitude domain. Owing to compressive sensing (CS) theory, information about the shape and amplitude of the signals is recovered. In this paper, we demonstrate that based on the acquired signals parameters, a better signal normalization may be provided in order to improve the TOF resolution. The procedure was tested using large sample of data registered by a dedicated detection setup enabling sampling of signals with 50-ps intervals. Experimental setup provided irradiation of a chosen position in the plastic scintillator strip with annihilation gamma quanta.
    Źródło:
    Nukleonika; 2016, 61, 1; 35-39
    0029-5922
    1508-5791
    Pojawia się w:
    Nukleonika
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Compressed sensing in MRI : mathematical preliminaries and basic examples
    Autorzy:
    Błaszczyk, Ł.
    Powiązania:
    https://bibliotekanauki.pl/articles/146500.pdf
    Data publikacji:
    2016
    Wydawca:
    Instytut Chemii i Techniki Jądrowej
    Tematy:
    compressed sensing
    magnetic resonance imaging
    sampling theory
    sparsity
    Opis:
    In magnetic resonance imaging (MRI), k-space sampling, due to physical restrictions, is very time- -consuming. It cannot be much improved using classical Nyquist-based sampling theory. Recent developments utilize the fact that MR images are sparse in some representations (i.e. wavelet coeffi cients). This new theory, created by Candès and Romberg, called compressed sensing (CS), shows that images with sparse representations can be recovered from randomly undersampled k-space data, by using nonlinear reconstruction algorithms (i.e. l1-norm minimization). Throughout this paper, mathematical preliminaries of CS are outlined, in the form introduced by Candès. We describe the main conditions for measurement matrices and recovery algorithms and present a basic example, showing that while the method really works (reducing the time of MR examination), there are some major problems that need to be taken into consideration.
    Źródło:
    Nukleonika; 2016, 61, 1; 41-43
    0029-5922
    1508-5791
    Pojawia się w:
    Nukleonika
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Damped Zero-Pseudorandom Noise OFDM Systems
    Autorzy:
    Esmaiel, H.
    Powiązania:
    https://bibliotekanauki.pl/articles/225983.pdf
    Data publikacji:
    2018
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    time reversal
    TR
    channel estimation
    CE
    compressed sensing
    CS
    orthogonal frequency division multiplexing
    OFDM
    Opis:
    This paper proposed a new OFDM scheme called damped zero-pseudorandom noise orthogonal frequency division multiplexing (DZPN-OFDM) scheme. In the proposed scheme, ZPN-OFDM non-zero part is damped to reduce its energy, thus the mutual interference power in-between the data and training blocks with conservative the pseudo-noise conventional properties required for channel estimation or synchronization. The motivation of this paper is the OFDM long guard interval working in wide dispersion channels, whereas a significant energy is wasted when the conventional ZPN-OFDM is used as well as the BER performance is also degraded. Moreover, the proposed scheme doesn’t duplicate the guard interval to solve the ZPN-OFDM spectrum efficiency loss problem. Both detailed performance analysis and simulation results show that the proposed DZPNOFDM scheme can, indeed, offer significant bit error rate, spectrum efficiency and energy efficiency improvement.
    Źródło:
    International Journal of Electronics and Telecommunications; 2018, 64, 4; 433-438
    2300-1933
    Pojawia się w:
    International Journal of Electronics and Telecommunications
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    High-resolution Direction of Arrival Estimation Method Based on Sparse Arrays with Minimum Number of Elements
    Autorzy:
    Mohammed, Jafar Ramadhan
    Powiązania:
    https://bibliotekanauki.pl/articles/1839475.pdf
    Data publikacji:
    2021
    Wydawca:
    Instytut Łączności - Państwowy Instytut Badawczy
    Tematy:
    compressed sensing
    direction of arrival
    DOA
    estimation
    sparse array
    Opis:
    Regular fully filled antenna arrays have been widely used in direction of arrival (DOA) estimation. However, practical implementation of these arrays is rather complex and their resolutions are limited to the beamwidth of the array pattern. Therefore, higher resolution and simpler methods are desirable. In this paper, the compressed sensing method is first applied to an initial fully filled array to randomly select the most prominent and effective elements which are used to form the sparse array. To keep the dimension of the sparse array equal to that of the fully filled array, the first and the last elements were excluded from the sparseness process. In addition, some constraints on the sparse spectrum are applied to increase estimation accuracy. The optimization problem is then solved iteratively using the iterative reweighted l1 norm. Finally, a simple searching algorithm is used to detect peaks in the spectrum solution that correspond to the directions of the arriving signals. Compared with the existing scanned beam methods, such as the minimum variance distortionless response (MVDR) technique, and with subspace approaches, such as multiple signal classification (MUSIC) and ESPIRT algorithms, the proposed sparse array method offers better performance even with a lower number of array elements and in severely noisy environments. Effectiveness of the proposed sparse array method is verified via computer simulations.
    Źródło:
    Journal of Telecommunications and Information Technology; 2021, 1; 8-14
    1509-4553
    1899-8852
    Pojawia się w:
    Journal of Telecommunications and Information Technology
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    High-resolution Direction of Arrival Estimation Method Based on Sparse Arrays with Minimum Number of Elements
    Autorzy:
    Mohammed, Jafar Ramadhan
    Powiązania:
    https://bibliotekanauki.pl/articles/1839489.pdf
    Data publikacji:
    2021
    Wydawca:
    Instytut Łączności - Państwowy Instytut Badawczy
    Tematy:
    compressed sensing
    direction of arrival
    DOA
    estimation
    sparse array
    Opis:
    Regular fully filled antenna arrays have been widely used in direction of arrival (DOA) estimation. However, practical implementation of these arrays is rather complex and their resolutions are limited to the beamwidth of the array pattern. Therefore, higher resolution and simpler methods are desirable. In this paper, the compressed sensing method is first applied to an initial fully filled array to randomly select the most prominent and effective elements which are used to form the sparse array. To keep the dimension of the sparse array equal to that of the fully filled array, the first and the last elements were excluded from the sparseness process. In addition, some constraints on the sparse spectrum are applied to increase estimation accuracy. The optimization problem is then solved iteratively using the iterative reweighted l1 norm. Finally, a simple searching algorithm is used to detect peaks in the spectrum solution that correspond to the directions of the arriving signals. Compared with the existing scanned beam methods, such as the minimum variance distortionless response (MVDR) technique, and with subspace approaches, such as multiple signal classification (MUSIC) and ESPIRT algorithms, the proposed sparse array method offers better performance even with a lower number of array elements and in severely noisy environments. Effectiveness of the proposed sparse array method is verified via computer simulations.
    Źródło:
    Journal of Telecommunications and Information Technology; 2021, 1; 8-14
    1509-4553
    1899-8852
    Pojawia się w:
    Journal of Telecommunications and Information Technology
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Least Support Orthogonal Matching Pursuit Algorithm with Prior Information
    Autorzy:
    Tawfic, I. Sh.
    Kayhan, S. K.
    Powiązania:
    https://bibliotekanauki.pl/articles/108778.pdf
    Data publikacji:
    2014
    Wydawca:
    Społeczna Akademia Nauk w Łodzi
    Tematy:
    Compressed sensing
    Least Support Orthogonal Matching Pursuit
    Partial Knowing Support, signal reconstruction
    Restricted Isometry Property
    Opis:
    This paper proposes a new fast matching pursuit technique named Partially Known Least Support Orthogonal Matching Pursuit (PKLS-OMP) which utilizes partially known support as a prior knowledge to reconstruct sparse signals from a limited number of its linear projections. The PKLS-OMP algorithm chooses optimum least part of the support at each iteration without need to test each candidate independently and incorporates prior signal information in the recovery process. We also derive sufficient condition for stable sparse signal recovery with the partially known support. Result shows that inclusion of prior information weakens the condition on the sensing matrices and needs fewer samples for successful reconstruction. Numerical experiments demonstrate that PKLS-OMP performs well compared to existing algorithms both in terms of reconstruction performance and execution time.
    Źródło:
    Journal of Applied Computer Science Methods; 2014, 6 No. 2; 111-134
    1689-9636
    Pojawia się w:
    Journal of Applied Computer Science Methods
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Linear and Planar Array Pattern Nulling via Compressed Sensing
    Autorzy:
    Mohammed, Jafar Ramadhan
    Thaher, Raad H.
    Abdulqader, Ahmed Jameel
    Powiązania:
    https://bibliotekanauki.pl/articles/1839322.pdf
    Data publikacji:
    2021
    Wydawca:
    Instytut Łączności - Państwowy Instytut Badawczy
    Tematy:
    compressed sensing
    convex optimization
    iterative re-weighted l1- norm minimization
    linear array
    planar array
    Opis:
    An optimization method based on compressed sensing is proposed for uniformly excited linear or planar antenna arrays to perturb excitation of the minimum number of array elements in such a way that the required number of nulls is obtained. First, the spares theory is relied upon to formulate the problem and then the convex optimization approach is adopted to find the optimum solution. The optimization process is further developed by using iterative re-weighted l1- norm minimization, helping select the least number of the sparse elements and impose the required constraints on the array radiation pattern. Furthermore, the nulls generated are wide enough to cancel a whole specific sidelobe. Simulation results demonstrate the effectiveness of the proposed method and the required nulls are placed with a minimum number of perturbed elements. Thus, in practical implementations of the proposed method, a highly limited number of attenuators and phase shifters is required compared to other, conventional methods.
    Źródło:
    Journal of Telecommunications and Information Technology; 2021, 3; 50-55
    1509-4553
    1899-8852
    Pojawia się w:
    Journal of Telecommunications and Information Technology
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    On the application of compressive sampling techniques to high throughput data in computational genomics
    Autorzy:
    Hernández-Lemus, H.
    Powiązania:
    https://bibliotekanauki.pl/articles/375726.pdf
    Data publikacji:
    2011
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    compressive sampling
    compressed sensing
    computational genomics
    Opis:
    With the advent of high throughput experiments in genomics and proteomics, the researcher in computational data analysis is faced with new challenges, both with regards to the computational capacities and also in the probabilistic/statistical methodology fields; in order to handle such massive amounts of data in a systematic coherent way. In this paper we describe the basic aspects of the mathematical theory and the computational implications of a recently developed technique called Compressive Sampling, as well as some possible applications within the scope of Computational Genomics, and Computational Biology in general. The central idea behind this work is that most of the information sampled from the experiments turns out to be discarded (for being non-useful) in the final stages of biological analysis, hence it would be better if we could find an algorithm to remove selectively such information in order to get rid of the computational burden associated with processing and analyzing such huge amounts of data. Here we show that a possible algorithm for doing so it is precisely Compressive Sampling. As a working example, we will consider the data-analysis of whole-genome microarray gene expression for 1191 individuals within a breast cancer project.
    Źródło:
    Theoretical and Applied Informatics; 2011, 23, 3-4; 177-192
    1896-5334
    Pojawia się w:
    Theoretical and Applied Informatics
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Recognition of the numbers in the Polish language
    Autorzy:
    Plichta, A.
    Gąciarz, T.
    Krzywdziński, T.
    Powiązania:
    https://bibliotekanauki.pl/articles/308844.pdf
    Data publikacji:
    2013
    Wydawca:
    Instytut Łączności - Państwowy Instytut Badawczy
    Tematy:
    Automatic Speech Recognition
    compressed sensing
    Sparse Classification
    Opis:
    Automatic Speech Recognition is one of the hottest research and application problems in today’s ICT technologies. Huge progress in the development of the intelligent mobile systems needs an implementation of the new services, where users can communicate with devices by sending audio commands. Those systems must be additionally integrated with the highly distributed infrastructures such as computational and mobile clouds, Wireless Sensor Networks (WSNs), and many others. This paper presents the recent research results for the recognition of the separate words and words in short contexts (limited to the numbers) articulated in the Polish language. Compressed Sensing Theory (CST) is applied for the first time as a methodology of speech recognition. The effectiveness of the proposed methodology is justified in numerical tests for both separate words and short sentences.
    Źródło:
    Journal of Telecommunications and Information Technology; 2013, 4; 70-78
    1509-4553
    1899-8852
    Pojawia się w:
    Journal of Telecommunications and Information Technology
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Semi-PROPELLER Compressed Sensing Image Reconstruction with Enhanced Resolution in MRI
    Autorzy:
    Malczewski, K.
    Powiązania:
    https://bibliotekanauki.pl/articles/226988.pdf
    Data publikacji:
    2015
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    MRI
    super-resolution
    compressed sensing
    Opis:
    Magnetic Resonance Imaging (MRI) reconstruction algorithm using semi-PROPELLER compressed sensing is presented in this paper. It is exhibited that introduced algorithm for estimating data shifts is feasible when super- resolution is applied. The offered approach utilizes compressively sensed MRI PROPELLER sequences and improves MR images spatial resolution in circumstances when highly undersampled k-space trajectories are applied. Compressed sensing (CS) aims at signal and images reconstructing from significantly fewer measurements than were traditionally thought necessary. It is shown that the presented approach improves MR spatial resolution in cases when Compressed Sensing (CS) sequences are used. The application of CS in medical modalities has the potential for significant scan time reductions, with visible benefits for patients and health care economics. These methods emphasize on maximizing image sparsity on known sparse transform domain and minimizing fidelity. This diagnostic modality struggles with an inherently slow data acquisition process. The use of CS to MRI leads to substantial scan time reductions [7] and visible benefits for patients and economic factors. In this report the objective is to combine Super-Resolution image enhancement algorithm with both PROPELLER sequence and CS framework. The motion estimation algorithm being a part of super resolution reconstruction (SRR) estimates shifts for all blades jointly, utilizing blade-pair correlations that are both strong and more robust to noise.
    Źródło:
    International Journal of Electronics and Telecommunications; 2015, 61, 2; 211-217
    2300-1933
    Pojawia się w:
    International Journal of Electronics and Telecommunications
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Simulation of the Operation of a Single Pixel Camera with Compressive Sensing in the Long-Wave Infrared
    Symulacja działania kamery jedno-pikselowej z oszczędnym próbkowaniem w paśmie dalekiej podczerwieni
    Autorzy:
    Szajewska, Anna
    Powiązania:
    https://bibliotekanauki.pl/articles/2068635.pdf
    Data publikacji:
    2021
    Wydawca:
    Sieć Badawcza Łukasiewicz - Przemysłowy Instytut Automatyki i Pomiarów
    Tematy:
    single pixel camera
    compressed sensing
    infrared measurements
    thermal camera
    kamera jedno-pikselowa
    oszczędne próbkowanie
    pomiary w podczerwieni
    kamera termowizyjna
    Opis:
    Imaging with the use of a single pixel camera and based on compressed sensing (CS) is a new and promising technology. The use of CS allows reconstruction of images in various spectrum ranges depending on the spectrum sensibility of the used detector. During the study image reconstruction was performed in the LWIR range based on a thermogram from a simulated single pixel camera. For needs of reconstruction CS was used. A case analysis showed that the CS method may be used for construction of infrared-based observation single pixel cameras. This solution may also be applied in measuring cameras. Yet the execution of a measurement of radiation temperature requires calibration of results obtained by CS reconstruction. In the study a calibration method of the infrared observation camera was proposed and studies were carried out of the impact exerted by the number of measurements made on the quality of reconstruction. Reconstructed thermograms were compared with reference images of infrared radiation. It has been ascertained that the reduction of the reconstruction error is not directly in proportion to the number of collected samples being collected. Based on a review of individual cases it has been ascertained that apart from the number of collected samples, an important factor that affects the reconstruction fidelity is the structure of the image as such. It has been proven that estimation of the error for reconstructed thermograms may not be based solely on the quantity of executed measurements.
    Obrazowanie kamerą jednopikselową z użyciem CS (compressed sensing) jest nową i obiecującą technologią. Za pomocą CS można rekonstruować obrazy w różnych zakresach widmowych zależnie od czułości spektralnej użytego detektora. W pracy wykonano rekonstrukcję obrazu w zakresie LWIR (Long-Wave Infrared) na podstawie termogramu z zasymulowanej kamery jednopikselowej. Do rekonstrukcji użyto CS. Na podstawie analizy przypadków stwierdzono, że metodę CS można wykorzystać do budowania kamer obserwacyjnych jednopikselowych na podczerwień. Możliwe jest również zastosowanie tego rozwiązania w kamerach pomiarowych. Aby wykonać pomiar temperatury radiacyjnej należy dokonać kalibracji wyników uzyskanych na drodze rekonstrukcji CS. W badaniu zaproponowano sposób kalibracji kamery pomiarowej na podczerwień oraz zbadano wpływ liczby pomiarów na jakość rekonstrukcji. Zrekonstruowane termogramy porównano z referencyjnymi obrazami promieniowania podczerwonego. Stwierdzono, że redukcja błędu rekonstrukcji nie jest wprost proporcjonalna do zwiększanej liczby pobieranych próbek. Na podstawie analizy przypadków zaobserwowano, że poza liczbą pobieranych próbek, istotnym czynnikiem mającym wpływającym na wierność rekonstrukcji jest struktura samego obrazu. Dowiedziono, że szacowanie błędu dla zrekonstruowanych termogramów nie może być oparte tylko na liczbie wykonywanych pomiarów.
    Źródło:
    Pomiary Automatyka Robotyka; 2021, 25, 2; 53--60
    1427-9126
    Pojawia się w:
    Pomiary Automatyka Robotyka
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
      Wyświetlanie 1-13 z 13

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