Tesis sobre el tema "Multi-dimensional graph signal processing"
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GRASSI, FRANCESCO. "Statistical and Graph-Based Signal Processing: Fundamental Results and Application to Cardiac Electrophysiology". Doctoral thesis, Politecnico di Torino, 2018. http://hdl.handle.net/11583/2710580.
Texto completoLarkin, Kieran Gerard. "Topics in Multi dimensional Signal Demodulation". Thesis, The University of Sydney, 2000. http://hdl.handle.net/2123/367.
Texto completoLarkin, Kieran Gerard. "Topics in Multi dimensional Signal Demodulation". University of Sydney. Physics, 2001. http://hdl.handle.net/2123/367.
Texto completoLarkin, Kieran Gerard. "Topics in multi-dimensional signal demodulation". Connect to full text, 2000. http://hdl.handle.net/2123/367.
Texto completoTitle from title screen (viewed Apr. 23, 2008). Submitted in fulfilment of the requirements for the degree of Doctor of Philosophy to the School of Physics, Faculty of Science. Includes bibliography. Also available in print form.
Costa, João Paulo Carvalho Lustosa da. "Parameter estimation techniques for multi-dimensional array signal processing". Aachen Shaker, 2010. http://d-nb.info/1000960765/04.
Texto completoRandeny, Tharindu D. "Multi-Dimensional Digital Signal Processing in Radar Signature Extraction". University of Akron / OhioLINK, 2015. http://rave.ohiolink.edu/etdc/view?acc_num=akron1451944778.
Texto completoAbewardana, Wijenayake Chamith K. "Multi-dimensional Signal Processing And Circuits For Advanced Electronically Scanned Antenna Arrays". University of Akron / OhioLINK, 2014. http://rave.ohiolink.edu/etdc/view?acc_num=akron1415358304.
Texto completoGianto, Gianto. "Multi-dimensional Teager-Kaiser signal processing for improved characterization using white light interferometry". Thesis, Strasbourg, 2018. http://www.theses.fr/2018STRAD026/document.
Texto completoThe use of white light interference fringes as an optical probe in microscopy is of growing importance in materials characterization, surface metrology and medical imaging. Coherence Scanning Interferometry (CSI, also known as White Light Scanning Interferometry, WSLI) is well known for surface roughness and topology measurement [1]. Full-Field Optical Coherence Tomography (FF-OCT) is the version used for the tomographic analysis of complex transparent layers. Both techniques generally make use of some sort of fringe scanning along the optical axis and the acquisition of a stack of xyz images. Image processing is then used to identify the fringe envelopes along z at each pixel in order to measure the positions of either a single surface or of multiple scattering objects within a layer.In CSI, the measurement of surface shape generally requires peak or phase extraction of the mono dimensional fringe signal. Most of the methods are based on an AM-FM signal model, which represents the variation in light intensity measured along the optical axis of an interference microscope [2]. We have demonstrated earlier [3, 4] the ability of 2D approaches to compete with some classical methods used in the field of interferometry, in terms of robustness and computing time. In addition, whereas most methods only take into account the 1D data, it would seem advantageous to take into account the spatial neighborhood using multidimensional approaches (2D, 3D, 4D), including the time parameter in order to improve the measurements.The purpose of this PhD project is to develop new n-D approaches that are suitable for improved characterization of more complex surfaces and transparent layers. In addition, we will enrich the field of study by means of heterogeneous image processing from multiple sensor sources (heterogeneous data fusion). Applications considered will be in the fields of materials metrology, biomaterials and medical imaging
Carvalho, Lustosa da Costa Joao P. [Verfasser]. "Parameter Estimation Techniques for Multi-Dimensional Array Signal Processing / Joao P Carvalho Lustosa da Costa". Aachen : Shaker, 2010. http://d-nb.info/112254653X/34.
Texto completoVorhies, John T. "Low-complexity Algorithms for Light Field Image Processing". University of Akron / OhioLINK, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=akron1590771210097321.
Texto completoSteinwandt, Jens Verfasser], Martin [Akademischer Betreuer] [Haardt, Marius [Gutachter] Pesavento y Sergiy A. [Gutachter] Vorobyov. "Advanced array signal processing algorithms for multi-dimensional parameter estimation / Jens Steinwandt ; Gutachter: Marius Pesavento, Sergiy A. Vorobyov ; Betreuer: Martin Haardt". Ilmenau : TU Ilmenau, 2019. http://d-nb.info/1177298449/34.
Texto completoCheema, Sher Ali Verfasser], Martin [Akademischer Betreuer] [Haardt, Mario [Gutachter] Huemer y Eduard Axel [Gutachter] Jorswieck. "Advanced signal processing concepts for multi-dimensional communication systems / Sher Ali Cheema ; Gutachter: Mario Huemer, Eduard Axel Jorswieck ; Betreuer: Martin Haardt". Ilmenau : TU Ilmenau, 2018. http://d-nb.info/1178128989/34.
Texto completoCheng, Yao [Verfasser], Martin [Akademischer Betreuer] Haardt, Ruyet Didier [Gutachter] Le y Ana Isabel [Gutachter] Pérez-Neira. "Advanced multi-dimensional signal processing for wireless systems / Yao Cheng ; Gutachter: Didier Le Ruyet, Ana Isabel Pérez-Neira ; Betreuer: Martin Haardt". Ilmenau : TU Ilmenau, 2016. http://d-nb.info/1178170934/34.
Texto completoSteinwandt, Jens [Verfasser], Martin [Akademischer Betreuer] Haardt, Marius [Gutachter] Pesavento y Sergiy A. [Gutachter] Vorobyov. "Advanced array signal processing algorithms for multi-dimensional parameter estimation / Jens Steinwandt ; Gutachter: Marius Pesavento, Sergiy A. Vorobyov ; Betreuer: Martin Haardt". Ilmenau : TU Ilmenau, 2019. http://d-nb.info/1177298449/34.
Texto completoPulipati, Sravan Kumar. "Electronically-Scanned Wideband Digital Aperture Antenna Arrays using Multi-Dimensional Space-Time Circuit-Network Resonance". University of Akron / OhioLINK, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=akron1499440141479455.
Texto completoZaylaa, Amira. "Analyse et extraction de paramètres de complexité de signaux biomédicaux". Thesis, Tours, 2014. http://www.theses.fr/2014TOUR3315/document.
Texto completoThe analysis of biomedical time series derived from nonlinear dynamic systems is challenging due to the chaotic nature of these time series. Only few classical parameters can be detected by clinicians to opt the state of patients and fetuses. Though there exist valuable complexity invariants such as multi-fractal parameters, entropies and recurrence plot, they were unsatisfactory in certain cases. To overcome this limitation, we propose in this dissertation new entropy invariants, we contributed to multi-fractal analysis and we developed signal-based (unbiased) recurrence plots based on the dynamic transitions of time series. Principally, we aim to improve the discrimination between healthy and distressed biomedical systems, particularly fetuses by processing the time series using our techniques. These techniques were either validated on Lorenz system, logistic maps or fractional Brownian motions modeling chaotic and random time series. Then the techniques were applied to real fetus heart rate signals recorded in the third trimester of pregnancy. Statistical measures comprising the relative errors, standard deviation, sensitivity, specificity, precision or accuracy were employed to evaluate the performance of detection. Elevated discernment outcomes were realized by the high-order entropy invariants. Multi-fractal analysis using a structure function enhances the detection of medical fetal states. Unbiased cross-determinism invariant amended the discrimination process. The significance of our techniques lies behind their post-processing codes which could build up cutting-edge portable machines offering advanced discrimination and detection of Intrauterine Growth Restriction prior to fetal death. This work was devoted to Fetal Heart Rates but time series generated by alternative nonlinear dynamic systems should be further considered
Xu, Yanli. "Une mesure de non-stationnarité générale : Application en traitement d'images et du signaux biomédicaux". Thesis, Lyon, INSA, 2013. http://www.theses.fr/2013ISAL0090/document.
Texto completoThe intensity variation is often used in signal or image processing algorithms after being quantified by a measurement method. The method for measuring and quantifying the intensity variation is called a « change measure », which is commonly used in methods for signal change detection, image edge detection, edge-based segmentation models, feature-preserving smoothing, etc. In these methods, the « change measure » plays such an important role that their performances are greatly affected by the result of the measurement of changes. The existing « change measures » may provide inaccurate information on changes, while processing biomedical images or signals, due to the high noise level or the strong randomness of the signals. This leads to various undesirable phenomena in the results of such methods. On the other hand, new medical imaging techniques bring out new data types and require new change measures. How to robustly measure changes in theos tensor-valued data becomes a new problem in image and signal processing. In this context, a « change measure », called the Non-Stationarity Measure (NSM), is improved and extended to become a general and robust « change measure » able to quantify changes existing in multidimensional data of different types, regarding different statistical parameters. A NSM-based change detection method and a NSM-based edge detection method are proposed and respectively applied to detect changes in ECG and EEG signals, and to detect edges in the cardiac diffusion weighted (DW) images. Experimental results show that the NSM-based detection methods can provide more accurate positions of change points and edges and can effectively reduce false detections. A NSM-based geometric active contour (NSM-GAC) model is proposed and applied to segment the ultrasound images of the carotid. Experimental results show that the NSM-GAC model provides better segmentation results with less iterations that comparative methods and can reduce false contours and leakages. Last and more important, a new feature-preserving smoothing approach called « Nonstationarity adaptive filtering (NAF) » is proposed and applied to enhance human cardiac DW images. Experimental results show that the proposed method achieves a better compromise between the smoothness of the homogeneous regions and the preservation of desirable features such as boundaries, thus leading to homogeneously consistent tensor fields and consequently a more reconstruction of the coherent fibers
Teng, Sin Yong. "Intelligent Energy-Savings and Process Improvement Strategies in Energy-Intensive Industries". Doctoral thesis, Vysoké učení technické v Brně. Fakulta strojního inženýrství, 2020. http://www.nusl.cz/ntk/nusl-433427.
Texto completoVlok, Jacobus David. "Sparse graph codes on a multi-dimensional WCDMA platform". Diss., 2007. http://upetd.up.ac.za/thesis/available/etd-07042007-155428.
Texto completoEdussooriya, Chamira Udaya Shantha. "Low-Complexity Multi-Dimensional Filters for Plenoptic Signal Processing". Thesis, 2015. http://hdl.handle.net/1828/6894.
Texto completoGraduate
0544
Chang, Yu-Chu y 張佑竹. "Vector Quantization and its Application to multi-dimensional Digital Signal Processing". Thesis, 1995. http://ndltd.ncl.edu.tw/handle/46496766224358760087.
Texto completoSrinivasan, Sabeshan. "Object tracking in distributed video networks using multi-dimensional signatures /". 2006. http://www.library.umaine.edu/theses/pdf/SrinivasanSX2006.pdf.
Texto completoSu, Hung y 蘇弘. "Multi-dimensional Histogram-based Watermarking Scheme for Resisting Geometric and Signal Processing Attacks". Thesis, 2004. http://ndltd.ncl.edu.tw/handle/22594619266851566270.
Texto completo國立中山大學
資訊工程學系研究所
92
Many digital watermarking schemes have been proposed for copyright protection recently due to the rapid growth of multimedia data distribution. Robustness is one of the crucial important issues in watermarking. But, most of traditional digital watermarking schemes is normally not to resist both geometric distortion and signal processing attacks well. There are two different types of solutions to resisting geometrical attacks: nonblind and blind methods. With the noblind approach, due to availability of the original image, the problem can be resolved with a good solution by elective search between the geometrically attacked and unattacked image. The blind solution, which does not use the original image in watermark extraction, is obviously more challenging. In this research, we propose a blind watermarking scheme which based on histogram property. So that, we propose a novel scheme to define the lattice structure of color space of host image for embedding watermark data. We utilize the histograms of various properties that calculated from the host image, and partition each histogram space into several divisions with dynamic interval. The number of pixels of each division is equal. And then we embed watermark data by modifying distribution of each division. The experimented results present the algorithm is robust to resist common geometric attacks and high quality JPEG compression at the same time.
Sevcenco, Ioana Speranta. "Multi-dimensional digital signal integration with applications in image, video and light field processing". Thesis, 2018. https://dspace.library.uvic.ca//handle/1828/9915.
Texto completoGraduate
Amini, Ladan. "Développement de Graphe de Connectivité Différentiel pour Caractérisation des Régions Cérébrales Impliquées dans l'Epilepsie". Phd thesis, 2010. http://tel.archives-ouvertes.fr/tel-00559915.
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