Statistical signal processing of spectrometric data: study of the pileup correction for energy spectra applied to Gamma spectrometry

The main objective of $\gamma$ spectrometry is to characterize the radioactive elements of an unknown source by studying the energy of the emitted $\gamma$ photons. When a photon interacts with a detector, its photonic energy is converted into an electrical pulse, whose integral energy is measured. The histogram obtained by collecting the energies can be used to identify radionucleides and measure their activity. However, at high counting rates, perturbations which are due to the stochastic aspect of the temporal signal can cripple the identification of the radioactive elements. More specifically, since the detector has a finite resolution, close arrival times of photons which can be modeled as an homogeneous Poisson process cause pileups of individual pulses. This phenomenon distorts energy spectra by introducing multiple fake spikes and prolonging artificially the Compton continuum, which can mask spikes of low intensity. The ...

Trigano, Thomas — Télécom Paris Tech


Three dimensional shape modeling: segmentation, reconstruction and registration

Accounting for uncertainty in three-dimensional (3D) shapes is important in a large number of scientific and engineering areas, such as biometrics, biomedical imaging, and data mining. It is well known that 3D polar shaped objects can be represented by Fourier descriptors such as spherical harmonics and double Fourier series. However, the statistics of these spectral shape models have not been widely explored. This thesis studies several areas involved in 3D shape modeling, including random field models for statistical shape modeling, optimal shape filtering, parametric active contours for object segmentation and surface reconstruction. It also investigates multi-modal image registration with respect to tumor activity quantification. Spherical harmonic expansions over the unit sphere not only provide a low dimensional polarimetric parameterization of stochastic shape, but also correspond to the Karhunen-Lo´eve (K-L) expansion of any isotropic random field on the unit sphere. Spherical ...

Li, Jia — University of Michigan


Advanced Signal Processing Concepts for Multi-Dimensional Communication Systems

The widespread use of mobile internet and smart applications has led to an explosive growth in mobile data traffic. With the rise of smart homes, smart buildings, and smart cities, this demand is ever growing since future communication systems will require the integration of multiple networks serving diverse sectors, domains and applications, such as multimedia, virtual or augmented reality, machine-to-machine (M2M) communication / the Internet of things (IoT), automotive applications, and many more. Therefore, in the future, the communication systems will not only be required to provide Gbps wireless connectivity but also fulfill other requirements such as low latency and massive machine type connectivity while ensuring the quality of service. Without significant technological advances to increase the system capacity, the existing telecommunications infrastructure will be unable to support these multi-dimensional requirements. This poses an important demand for suitable waveforms with ...

Cheema, Sher Ali — Technische Universität Ilmenau


Monitoring Infants by Automatic Video Processing

This work has, as its objective, the development of non-invasive and low-cost systems for monitoring and automatic diagnosing specific neonatal diseases by means of the analysis of suitable video signals. We focus on monitoring infants potentially at risk of diseases characterized by the presence or absence of rhythmic movements of one or more body parts. Seizures and respiratory diseases are specifically considered, but the approach is general. Seizures are defined as sudden neurological and behavioural alterations. They are age-dependent phenomena and the most common sign of central nervous system dysfunction. Neonatal seizures have onset within the 28th day of life in newborns at term and within the 44th week of conceptional age in preterm infants. Their main causes are hypoxic-ischaemic encephalopathy, intracranial haemorrhage, and sepsis. Studies indicate an incidence rate of neonatal seizures of 2‰ live births, 11‰ for preterm ...

Cattani Luca — University of Parma (Italy)


Progressive visualization of incomplete sonar-data sets: from sea-bottom interpolation and segmentation to geometry extraction

This thesis describes a visualization pipeline for sonar profiling data that show reflections of multiple sediments in the sea bottom and that cover huge survey areas with many gaps. Visualizing such data is not trivial, because they may be noisy and because data sets may be very large. The developed techniques are: (1) Quadtree interpolation for estimating new sediment reflections, at all gaps in the longitude-latitude plane. The quadtree is used for guiding the 3D interpolation process: gaps become small at low spatial resolutions, where they can be filled by interpolating between available reflections. In the interpolation, the reflection data are cross correlated in order to construct continuity of multiple, sloping reflections. (2) Segmentation and boundary refinement in an octree in order to detect sediments in the sonar data. In the refinement, coarse boundaries are reclassified by filtering the data ...

Loke, Robert Edward — Delft University of Technology


Nonlinear processing of non-Gaussian stochastic and chaotic deterministic time series

It is often assumed that interference or noise signals are Gaussian stochastic processes. Gaussian noise models are appealing as they usually result in noise suppression algorithms that are simple: i.e. linear and closed form. However, such linear techniques may be sub-optimal when the noise process is either a non-Gaussian stochastic process or a chaotic deterministic process. In the event of encountering such noise processes, improvements in noise suppression, relative to the performance of linear methods, may be achievable using nonlinear signal processing techniques. The application of interest for this thesis is maritime surveillance radar, where the main source of interference, termed sea clutter, is widely accepted to be a non-Gaussian stochastic process at high resolutions and/or at low grazing angles. However, evidence has been presented during the last decade which suggests that sea clutter may be better modelled as a ...

Cowper, Mark — University Of Edinburgh


Signal processing of FMCW Synthetic Aperture Radar data

In the field of airborne earth observation there is special attention to compact, cost effective, high resolution imaging sensors. Such sensors are foreseen to play an important role in small-scale remote sensing applications, such as the monitoring of dikes, watercourses, or highways. Furthermore, such sensors are of military interest; reconnaissance tasks could be performed with small unmanned aerial vehicles (UAVs), reducing in this way the risk for one's own troops. In order to be operated from small, even unmanned, aircrafts, such systems must consume little power and be small enough to fulfill the usually strict payload requirements. Moreover, to be of interest for the civil market, cost effectiveness is mandatory. Frequency Modulated Continuous Wave (FMCW) radar systems are generally compact and relatively cheap to purchase and to exploit. They consume little power and, due to the fact that they are ...

Meta, Adriano — Delft University of Technology


Selected Topics in Inertial and Visual Sensor Fusion: Calibration, Observability Analysis and Applications

Recent improvements in the development of inertial and visual sensors allow building small, lightweight, and cheap motion capture systems, which are becoming a standard feature of smartphones and personal digital assistants. This dissertation describes developments of new motion sensing strategies using the inertial and inertial-visual sensors. The thesis contributions are presented in two parts. The first part focuses mainly on the use of inertial measurement units. First, the problem of sensor calibration is addressed and a low-cost and accurate method to calibrate the accelerometer cluster of this unit is proposed. The method is based on the maximum likelihood estimation framework, which results in a minimum variance unbiased estimator.Then using the inertial measurement unit, a probabilistic user-independent method is proposed for pedestrian activity classification and gait analysis.The work targets two groups of applications including human activity classificationand joint human activity and ...

Panahandeh Ghazaleh — KTH Royal Institute of Technology


Non-rigid Registration-based Data-driven 3D Facial Action Unit Detection

Automated analysis of facial expressions has been an active area of study due to its potential applications not only for intelligent human-computer interfaces but also for human facial behavior research. To advance automatic expression analysis, this thesis proposes and empirically proves two hypotheses: (i) 3D face data is a better data modality than conventional 2D camera images, not only for being much less disturbed by illumination and head pose effects but also for capturing true facial surface information. (ii) It is possible to perform detailed face registration without resorting to any face modeling. This means that data-driven methods in automatic expression analysis can compensate for the confounding effects like pose and physiognomy differences, and can process facial features more effectively, without suffering the drawbacks of model-driven analysis. Our study is based upon Facial Action Coding System (FACS) as this paradigm ...

Savran, Arman — Bogazici University


Perception and Production of Greek Vowels by Egyptian Arabic Learners of Greek as a Second Language

The purpose of the thesis is the investigation of the perception and production of the Cypriot Greek vowels by Egyptian Arab learners of Greek as a second language (L2). The particular group of adult learners has been taught Greek through formal education settings (schools, universities) living as well permanently in a country where Greek is dominant. Moreover, the study aims to show the effect of the pedagogical intervention (vowel instruction/training) on the perception and production of the Greek vowels by the adult L2 learners. The thesis employs the theoretical hypotheses of two models: the Speech Learning Model (SLM) and the Perceptual Assimilation Model (PAM). The present study constitutes the first cross-linguistic study which examines the perception and production of Greek segments by learners with Arabic first language (L1) background while the studies provided by the bibliography regarding the acquisition of ...

Georgios P. Georgiou — University of Cyprus


Novel Methods in H.264/AVC (Inter Prediction, Data Hiding, Bit Rate Transcoding)

H.264 Advanced Video Coding has become the dominant video coding standard in the market, within a few years after the first version of the standard was completed by the ISO/IEC MPEG and the ITU-T VCEG groups in May 2003. That happened mainly due to the great coding efficiency of H.264. Compared to MPEG-2, the previous dominant standard, the H.264 compression ratio is about twice as higher for the same video quality. That makes H.264 ideal for a numerous of applications, such as video broadcasting, video streaming and video conferencing. However, the H.264 efficiency is achieved at the expense of the codec¢s complexity. H.264 complexity is about four times that of MPEG-2. As a consequence, many video coding issues, which have been addressed in previous standards, need to be re-considered. For example the H.264 encoding of a video in real time ...

Kapotas, Spyridon — Hellenic Open University


Development of an automated neonatal EEG seizure monitor

Brain function requires a continuous flow of oxygen and glucose. An insufficient supply for a few minutes during the first period of life may have severe consequences or even result in death. This happens in one to six infants per 1000 live term births. Therefore, there is a high need for a method which can enable bedside brain monitoring to identify those neonates at risk and be able to start the treatment in time. The most important currently available technology to continuously monitor brain function is electroEncephaloGraphy (or EEG). Unfortunately, visual EEG analysis requires particular skills which are not always present round the clock in the Neonatal Intensive Care Unit (NICU). Even if those skills are available it is laborsome to manually analyse many hours of EEG. The lack of time and skill are the main reasons why EEG is ...

Deburchgraeve, Wouter — KU Leuven


Deep Learning for Event Detection, Sequence Labelling and Similarity Estimation in Music Signals

When listening to music, some humans can easily recognize which instruments play at what time or when a new musical segment starts, but cannot describe exactly how they do this. To automatically describe particular aspects of a music piece – be it for an academic interest in emulating human perception, or for practical applications –, we can thus not directly replicate the steps taken by a human. We can, however, exploit that humans can easily annotate examples, and optimize a generic function to reproduce these annotations. In this thesis, I explore solving different music perception tasks with deep learning, a recent branch of machine learning that optimizes functions of many stacked nonlinear operations – referred to as deep neural networks – and promises to obtain better results or require less domain knowledge than more traditional techniques. In particular, I employ ...

Schlüter, Jan — Department of Computational Perception, Johannes Kepler University Linz


Statistical methods using hydrodynamic simulations of stellar atmospheres for detecting exoplanets in radial velocity data

When the noise affecting time series is colored with unknown statistics, a difficulty for periodic signal detection is to control the true significance level at which the detection tests are conducted. This thesis investigates the possibility of using training datasets of the noise to improve this control. Specifically, for the case of regularly sampled observations, we analyze the performances of various detectors applied to periodograms standardized using the noise training datasets. Emphasis is put on sparse detection in the Fourier domain and on the limitation posed by the necessary finite size of the training sets available in practice. We study the resulting false alarm and detection rates and show that the proposed standardization leads, in some cases, to powerful constant false alarm rate tests. Although analytical results are derived in an asymptotic regime, numerical results show that the theory accurately ...

Sulis Sophia — Université Côte d’Azur


Device-to-Device Wireless Communications

Device-to-Device (D2D) is one of the important proposed solutions to increase the capacity, offload the traffic, and improve the energy effciency in next generation cellular networks. D2D communication is known as a direct communication between two users without using cellular infrastructure networks. Despite of large expected bene fits in terms of capacity in D2D, the coexistence of D2D and cellular networks in the same spectrum creates new challenges in interference management and network design. To limit the interference power control schemes on cellular networks and D2D networks are typically adopted. Even though power control is introduced to limit the interference level, it does not prevent cellular and D2D users from experiencing coverage limitation when sharing the same radio resources. Therefore, the design of such networks requires the availability of suitable methods able to properly model the eff ect of interference ...

Alhalabi, Ashraf S.A. — Universita Degli Sudi di Bologna

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