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Every day we share our personal information with digital systems which are constantly exposed to threats. Security-oriented disciplines of signal processing have then received increasing attention in the last decades: multimedia forensics, digital watermarking, biometrics, network intrusion detection, steganography and steganalysis are just a few examples. Even though each of these fields has its own peculiarities, they all have to deal with a common problem: the presence of adversaries aiming at making the system fail. It is the purpose of Adversarial Signal Processing to lay the basis of a general theory that takes into account the impact of an adversary on the design of effective signal processing tools. By focusing on the most prominent problem of Adversarial Signal Processing, namely binary detection or Hypothesis Testing, we contribute to the above mission with a general theoretical framework for the binary detection ...

This thesis puts a focus on the analysis of key aspects of low-complexity Ultra Wideband (UWB) localizations systems. It is well known that UWB allows for highly robust and accurate ranging even in multipath intensive environments. On the other hand, the huge bandwidth leads to very challenging receiver designs and so low complexity and low power consumption are not achieveable for common receiver structures. The energy detector is a promising alternative. But in contrast to high-complexity coherent receivers, their performance is strongly dependent on the system parameters of the air interface protocol. IEEE 802.15.4a is a UWB standard with high-precision localization capability (better than 1m). The standard defines many system parameters, whose impact on the ranging and localization performance is studied in the thesis. These parameters have also a significant impact on the maximum allowed transmit energy, which limits the ...

This thesis is concerned with the problem of broadband angle of arrival (AoA) estimation for sensor arrays. There is a rich theory of narrowband solutions to the AoA problem, which typically involves the covariance matrix of the received data and matrix factorisations such as the eigenvalue decomposition (EVD) to reach optimality in various senses. For broadband arrays, such as found in sonar, acoustics or other applications where signals do not fulfil the narrowband assumption, working with phase shifts between different signals — as sufficient in the narrowband case — does not suffice and explicit lags need to be taken into account. The required space-time covariance matrix of the data now has a lag dimension, and classical solutions such as those based on the EVD are no longer directly applicable. There are a number of existing broadband AoA techniques, which are ...

Relaying, i.e., multihop communication via so-called relay nodes, has emerged as an advanced technology for economically realizing long transmission ranges and high data rates in wireless systems. The focus of this thesis is on multihop multiuser systems where signals are modulated with orthogonal frequency-division multiplexing or multiple access, i.e., OFDM(A), and relays are infrastructure-based network nodes. In general, the thesis contributes by investigating how to operate relay links optimally under spectrum, transmit power and processing capability limitations, as well as how to improve signal processing in relays by exploiting other advanced concepts such as multiantenna techniques, spectrum reuse, transmit power adaptation, and new options for multicarrier protocol design. The first theme is the design and analysis of duplexing modes which define how a relay link reuses allocated frequency bands in each hop. Especially, the full-duplex relaying mode is promoted as ...

The subject of the thesis is the emergence and analysis of visual texture microstructure for efficient modeling, descriptive feature extraction and image representation. Main objectives are the problems of image texture modeling and analysis in Computer Vision systems, with emphasis on the subproblems of texture detection, segmentation and separation in images. Advanced modeling and analysis methods are developed in parallel directions: a) Multiband models of narrowband components and spatial modulations, b) Energy methods for texture feature extraction, c) Variational techniques of image decomposition and texture separation. The proposed methods are applied on a database of digitized soilsection images to quantify and evaluate the biological quality of soils and in different types and collections of natural images. The developed model is the common ground to approach texture in its different forms and applications. In total, a complete system for texture processing ...

This work is focused on the processing of multichannel and multisource audio signals. From an audio mixture of several audio sources recorded in a reverberant room, we wish to es- timate the acoustic responses (a.k.a. mixing filters) between the sources and the microphones. To solve this inverse problem one need to take into account additional hypotheses on the nature of the acoustic responses. Our approach consists in first identifying mathematically the neces- sary hypotheses on the acoustic responses for their estimation and then building cost functions and algorithms to effectively estimate them. First, we considered the case where the source signals are known. We developed a method to estimate the acoustic responses based on a convex regularization which exploits both the temporal sparsity of the filters and the exponentially decaying envelope. Real-world experi- ments confirmed the effectiveness of this method ...

Data acquisition is a necessary first step in digital signal processing applications such as radar, wireless communications and array processing. Traditionally, this process is performed by uniformly sampling signals at a frequency above the Nyquist rate and converting the resulting samples into digital numeric values through high-resolution amplitude quantization. While the traditional approach to data acquisition is straightforward and extremely well-proven, it may be either impractical or impossible in many modern applications due to the existing fundamental trade-off between sampling rate, amplitude quantization precision, implementation costs, and usage of physical resources, e.g. bandwidth and power consumption. Motivated by this fact, system designers have recently proposed exploiting sparse and few-bit quantized sampling instead of the traditional way of data acquisition in order to reduce implementation costs and usage of physical resources in such applications. However, before transition from the tradition data ...

In this doctoral thesis several scale-free texture segmentation procedures based on two fractal attributes, the Hölder exponent, measuring the local regularity of a texture, and local variance, are proposed.A piecewise homogeneous fractal texture model is built, along with a synthesis procedure, providing images composed of the aggregation of fractal texture patches with known attributes and segmentation. This synthesis procedure is used to evaluate the proposed methods performance.A first method, based on the Total Variation regularization of a noisy estimate of local regularity, is illustrated and refined thanks to a post-processing step consisting in an iterative thresholding and resulting in a segmentation.After evidencing the limitations of this first approach, deux segmentation methods, with either "free" or "co-located" contours, are built, taking in account jointly the local regularity and the local variance.These two procedures are formulated as convex nonsmooth functional minimization problems.We ...

This thesis treats efficient estimation algorithms for the epipolar geometry, the model underlying two views of the same scene or object. The epipolar geometry is computed from image correspondences that are found by local feature matching. These correspondences are used to calculate the fundamental matrix, which is the mathematical representation of the epipolar geometry. Since there are outliers among the correspondences, the fundamental matrix is usually calculated by the robust RANSAC (RANdom SAmple Consensus) algorithm which is very well suited for this purpose. A disadvantage of the algorithm, however, is that it shows a considerable complexity for higher outlier ratios. This hampers its application in vision algorithms dealing with many views. In this thesis we investigate techniques for faster fundamental matrix estimation using RANSAC. The first approach that is taken is the computation of inlier probabilities for the correspondences, that ...

In the modern world, we are increasingly surrounded by computation devices with communication links and one or more microphones. Such devices are, for example, smartphones, tablets, laptops or hearing aids. These devices can work together as nodes in an acoustic sensor network (ASN). Such networks are a growing platform that opens the possibility for many practical applications. ASN based speech enhancement, source localization, and event detection can be applied for teleconferencing, camera control, automation, or assisted living. For this kind of applications, the awareness of auditory objects and their spatial positioning are key properties. In order to provide these two kinds of information, novel methods have been developed in this thesis. Information on the type of auditory objects is provided by a novel real-time sound classification method. Information on the position of human speakers is provided by a novel localization ...

Broadband wireless communication is a very fast growing communication area. Multicarrier modulation techniques like Orthogonal Frequency Division Multiplexing (OFDM), Biorthogonal Frequency Division Multiplexing (BFDM), Pulse Shaping (PS) and Multi-Carrier Spread Spectrum (MCSS) have recently been introduced as robust techniques against intersymbol interference (ISI) and noise, compared to single carrier communication systems over fast fading multipath communication channels. Therefore, multicarrier modulation techniques have been considered as a candidate for new generation, high data rate broadband wireless communication systems and have been adopted as the related standards. Several examples are the European digital audio broadcasting (DAB) and digital video broadcasting (DVB), the IEEE standands for wireless local area networks (WLAN), 802.11a, and wireless metropolitan area networks (WMAN), 802.16a. However, Doppler frequency shifts, phase offset, local oscillator frequency shifts, and multi-path fading severely degrade the performance of multicarrier communication systems. For fast-varying channels, ...

In Broadband Wireless Access systems the efficient use of the resources is crucial from many points of views. From the operator point of view, the bandwidth is a scarce, valuable, and expensive resource which must be exploited in an efficient manner while the Quality of Service (QoS) provided to the users is guaranteed. On the other hand, a tight delay and link quality constraints are imposed on each data flow hence the user experiences the same quality as in fixed networks. During the last few years many techniques have been developed in order to increase the spectral efficiency and the throughput. Among them, the use of multiple antennas at the transmitter and the receiver (exploiting spatial multiplexing) with the joint optimization of the medium access control layer and the physical layer parameters. In this Ph.D. thesis, different adaptive techniques for ...

Copy Number Alterations (CNA)s are hallmarks of cancer, which are gains or losses in copies of Deoxyribonucleic Acid (DNA) sections. Nowadays, CNAs are routinely measured by different techniques for diagnostic and prognostic purposes. The array-Comparative Genomic Hybridization (aCGH), Array-Single Nucleotide Polymorphism (aSNP) and Next Generation Sequencing (NGS) are examples of technologies that enable cost-efficient high resolution detection of CNAs. Intensive noise as well as technical and biological biases inherent to modern technologies of CNAs probing often cause inconsistency between the estimates provided by different methods. Efficient and accurate detection of the breakpoint positions in heterogeneous cancer samples measured under such conditions is a challenging practical and methodological problem. Despite the necessity of accurate CNA estimates, there is no much information regarding the estimation errors. Based on studies of the confidence limits for noisy stepwise signals, an efficient algorithm has been ...

It takes more time to think of a silent scene, action or event than finding one that emanates sound. Not only speaking or playing music but almost everything that happens is accompanied with or results in one or more sounds mixed together. This makes acoustic event detection (AED) one of the most researched topics in audio signal processing nowadays and it will probably not see a decline anywhere in the near future. This is due to the thirst for understanding and digitally abstracting more and more events in life via the enormous amount of recorded audio through thousands of applications in our daily routine. But it is also a result of two intrinsic properties of audio: it doesn’t need a direct sight to be perceived and is less intrusive to record when compared to image or video. Many applications such ...