Heuristic Optimization Methods for System Partitioning in HW/SW Co-Design

Nowadays, the design of embedded systems is confronted with the combination of complex signal processing algorithms on the one hand and a variety of computational intensive multimedia applications on the other hand, while time to product launch has been extremely reduced. Especially in the wireless domain those challenges are stacked with tough requirements on power consumption and chip size. Unfortunately, design productivity did not undergo a similar progression and therefore fails to cope with the heterogeneity of modern hardware architectures. Until now, electronic design automation do not provide for complete coverage of the design ow. In particular crucial design tasks as high level characterisation of algorithms, oating-point to xed-point conversion, automated hardware/software partitioning, and automated virtual prototyping are not suciently supported or completely absent. In recent years a consistent design framework named Open Tool Integration Environment (OTIE) has been established ...

Knerr, Bastian — Vienna University of Technology


Digital design and experimental validation of high-performance real-time OFDM systems

The goal of this Ph.D. dissertation is to address a number of challenges encountered in the digital baseband design of modern and future wireless communication systems. The fast and continuous evolution of wireless communications has been driven by the ambitious goal of providing ubiquitous services that could guarantee high throughput, reliability of the communication link and satisfy the increasing demand for efficient re-utilization of the heavily populated wireless spectrum. To cope with these ever-growing performance requirements, researchers around the world have introduced sophisticated broadband physical (PHY)-layer communication schemes able to accommodate higher bandwidth, which indicatively include multiple antennas at the transmitter and receiver and are capable of delivering improved spectral efficiency by applying interference management policies. The merging of Multiple Input Multiple Output (MIMO) schemes with the Orthogonal Frequency Division Multiplexing (OFDM) offers a flexible signal processing substrate to implement ...

Font-Bach, Oriol — Centre Tecnològic de Telecomunicacions de Catalunya (CTTC)


An Open Tool Integration Environment for Efficient Design of Embedded Systems in Wireless Communications

The design of embedded computer systems for modern wireless communication devices finds itself under increasing technological and commercial pressures. This design crisis is fueled by an unrelenting growth in algorithmic complexity, which by far outpaces the growth in design productivity, thus making it increasingly difficult to design entire embed- ded systems. On the other hand, the commercial reality in the wireless communications sector dictates ever shortening design cycles to achieve quicker time to market. This thesis examines the traditional design process of embedded systems for wireless communications, identifies the key bottlenecks which inhibit increased design productiv- ity, and proposes the Open Tool Integration Environment (OTIE) as an effective means of removing these bottlenecks. A flexible, scalable, robust, and secure implementation of OTIE is presented, based on a Single System Description (SSD), providing a single, central repository for all refinement information ...

Belanovic, P. — Vienna University of Technology


Identification of versions of the same musical composition by processing audio descriptions

Automatically making sense of digital information, and specially of music digital documents, is an important problem our modern society is facing. In fact, there are still many tasks that, although being easily performed by humans, cannot be effectively performed by a computer. In this work we focus on one of such tasks: the identification of musical piece versions (alternate renditions of the same musical composition like cover songs, live recordings, remixes, etc.). In particular, we adopt a computational approach solely based on the information provided by the audio signal. We propose a system for version identification that is robust to the main musical changes between versions, including timbre, tempo, key and structure changes. Such a system exploits nonlinear time series analysis tools and standard methods for quantitative music description, and it does not make use of a specific modeling strategy ...

Serra, Joan — Universitat Pompeu Fabra


Spatio-Temporal Speech Enhancement in Adverse Acoustic Conditions

Never before has speech been captured as often by electronic devices equipped with one or multiple microphones, serving a variety of applications. It is the key aspect in digital telephony, hearing devices, and voice-driven human-to-machine interaction. When speech is recorded, the microphones also capture a variety of further, undesired sound components due to adverse acoustic conditions. Interfering speech, background noise and reverberation, i.e. the persistence of sound in a room after excitation caused by a multitude of reflections on the room enclosure, are detrimental to the quality and intelligibility of target speech as well as the performance of automatic speech recognition. Hence, speech enhancement aiming at estimating the early target-speech component, which contains the direct component and early reflections, is crucial to nearly all speech-related applications presently available. In this thesis, we compare, propose and evaluate existing and novel approaches ...

Dietzen, Thomas — KU Leuven


Analysis of Multipath Mitigation Techniques for Satellite-based Positioning Applications

Multipath remains a dominant source of ranging errors in any Global Navigation Satellite System (GNSS), such as the Global Positioning System (GPS) or the developing European satellite navigation system Galileo. Multipath is undesirable in the context of GNSS, since the reception of multipath can create significant distortion to the shape of the correlation function used in the time delay estimate of a Delay Locked Loop (DLL) of a navigation receiver, leading to an error in the receiver's position estimate. Therefore, in order to mitigate the impact of multipath on a navigation receiver, the multipath problem has been approached from several directions, including the development of novel signal processing techniques. Many of these techniques rely on modifying the tracking loop discriminator (i.e., the DLL and its enhanced variants) in order to make it resistant to multipath, but their performance in severe ...

Bhuiyan, Mohammad Zahidul Hasan — Tampere University of Technology


Best Signal Selection with Automatic Delay Compensation in VoIP Environment

In the last decades, air traffic spread more and more in the world, connecting more and more places. At the same time, the need to manage all the flights correctly and securely increased. Air traffic authorities imposed and updated several standards for the air traffic management (ATM) system, keeping in pace with the growing traffic flow. To achieve this, special voice communication systems (VCS) were developed. They ensure the communication between the pilots and the operators from the ground control centers. When a communication is initiated between the aircraft’s pilot and the ground air traffic control operator, various systems are used. The pilot speaks through the aircraft’s radio station and the signal is received by several ground radio stations. Then, the signal from each ground radio station arrives on different paths to the control center. Here one of the received ...

Marinescu, Radu-Sebastian — University Politehnica of Bucharest


Deep Learning-based Speaker Verification In Real Conditions

Smart applications like speaker verification have become essential in verifying the user's identity for availing of personal assistants or online banking services based on the user's voice characteristics. However, far-field or distant speaker verification is constantly affected by surrounding noises which can severely distort the speech signal. Moreover, speech signals propagating in long-range get reflected by various objects in the surrounding area, which creates reverberation and further degrades the signal quality. This PhD thesis explores deep learning-based multichannel speech enhancement techniques to improve the performance of speaker verification systems in real conditions. Multichannel speech enhancement aims to enhance distorted speech using multiple microphones. It has become crucial to many smart devices, which are flexible and convenient for speech applications. Three novel approaches are proposed to improve the robustness of speaker verification systems in noisy and reverberated conditions. Firstly, we integrate ...

Dowerah Sandipana — Universite de Lorraine, CNRS, Inria, Loria


Learning Transferable Knowledge through Embedding Spaces

The unprecedented processing demand, posed by the explosion of big data, challenges researchers to design efficient and adaptive machine learning algorithms that do not require persistent retraining and avoid learning redundant information. Inspired from learning techniques of intelligent biological agents, identifying transferable knowledge across learning problems has been a significant research focus to improve machine learning algorithms. In this thesis, we address the challenges of knowledge transfer through embedding spaces that capture and store hierarchical knowledge. In the first part of the thesis, we focus on the problem of cross-domain knowledge transfer. We first address zero-shot image classification, where the goal is to identify images from unseen classes using semantic descriptions of these classes. We train two coupled dictionaries which align visual and semantic domains via an intermediate embedding space. We then extend this idea by training deep networks that ...

Mohammad Rostami — University of Pennsylvania


Automated audio captioning with deep learning methods

In the audio research field, the majority of machine learning systems focus on recognizing a limited number of sound events. However, when a machine interacts with real data, it must be able to handle much more varied and complex situations. To tackle this problem, annotators use natural language, which allows any sound information to be summarized. Automated Audio Captioning (AAC) was introduced recently to develop systems capable of automatically producing a description of any type of sound in text form. This task concerns all kinds of sound events such as environmental, urban, domestic sounds, sound effects, music or speech. This type of system could be used by people who are deaf or hard of hearing, and could improve the indexing of large audio databases. In the first part of this thesis, we present the state of the art of the ...

Labbé, Étienne — IRIT


OFDM Multi-User Communication Over Time-Variant Channels

Wireless broadband communications for users moving at vehicular speed is a cor- nerstone of future fourth generation (4G) mobile communication systems. We inves- tigate a multi-carrier (MC) code division multiple access (CDMA) system which is based on orthogonal frequency division multiplexing (OFDM). A spreading sequence is used in the frequency domain in order to distinguish individual users and to take advantage of the multipath diversity of the wireless channel. The transmission is block oriented. A block consists of OFDM pilot and OFDM data symbols. At pedestrian velocities the channel can be modelled as block fading. We ap- ply iterative multi-user detection and channel estimation. In iterative receivers soft symbols are derived from the output of an soft-input soft-output decoder. These soft symbols are used in order to reduce the interference from other users and to enhance the channel estimates. We ...

Zemen, T. — Vienna University of Technology


Constrained Non-negative Matrix Factorization for Vocabulary Acquisition from Continuous Speech

One desideratum in designing cognitive robots is autonomous learning of communication skills, just like humans. The primary step towards this goal is vocabulary acquisition. Being different from the training procedures of the state-of-the-art automatic speech recognition (ASR) systems, vocabulary acquisition cannot rely on prior knowledge of language in the same way. Like what infants do, the acquisition process should be data-driven with multi-level abstraction and coupled with multi-modal inputs. To avoid lengthy training efforts in a word-by-word interactive learning process, a clever learning agent should be able to acquire vocabularies from continuous speech automatically. The work presented in this thesis is entitled \emph{Constrained Non-negative Matrix Factorization for Vocabulary Acquisition from Continuous Speech}. Enlightened by the extensively studied techniques in ASR, we design computational models to discover and represent vocabularies from continuous speech with little prior knowledge of the language to ...

Sun, Meng — Katholieke Universiteit Leuven


Biometric Sample Quality and Its Application to Multimodal Authentication Systems

This Thesis is focused on the quality assessment of biometric signals and its application to multimodal biometric systems. Since the establishment of biometrics as an specific research area in late 90s, the biometric community has focused its efforts in the development of accurate recognition algorithms and nowadays, biometric recognition is a mature technology that is used in many applications. However, we can notice recent studies that demonstrate how performance of biometric systems is heavily affected by the quality of biometric signals. Quality measurement has emerged in the biometric community as an important concern after the poor performance observed in biometric systems on certain pathological samples. We first summarize the state-of-the-art in the biometric quality problem. We present the factors influencing biometric quality, which mainly have to do with four issues: the individual itself, the sensor used in the acquisition, the ...

Alonso-Fernandez, Fernando — Universidad Politecnica de Madrid


Sound Event Detection by Exploring Audio Sequence Modelling

Everyday sounds in real-world environments are a powerful source of information by which humans can interact with their environments. Humans can infer what is happening around them by listening to everyday sounds. At the same time, it is a challenging task for a computer algorithm in a smart device to automatically recognise, understand, and interpret everyday sounds. Sound event detection (SED) is the process of transcribing an audio recording into sound event tags with onset and offset time values. This involves classification and segmentation of sound events in the given audio recording. SED has numerous applications in everyday life which include security and surveillance, automation, healthcare monitoring, multimedia information retrieval, and assisted living technologies. SED is to everyday sounds what automatic speech recognition (ASR) is to speech and automatic music transcription (AMT) is to music. The fundamental questions in designing ...

[Pankajakshan], [Arjun] — Queen Mary University of London


Signal Processing Algorithms for CDMA-Based Wireless Communications

Wireless communication systems rely on a multiple-access technique, i.e., a mechanism to divide the common transmission medium among di erent users. Code-division multiple-access (CDMA) is a multiple-access technique that has received considerable attention in recent years. In a CDMA system, each user spreads his information-bearing signal into a wideband signal, using speci c code information. All users then transmit their wideband signal within the same frequency and time channel. This thesis deals with the development of receivers for various CDMA systems. Digital signal processing plays a central role in this development. In recent literature, so-called multi-user receivers have become very popular. These receivers take into account the full structure of the multi-user interfer- ence (MUI), i.e., the interference originating from the other users. However, they have a rather high computational complexity. In the rst part of this the- sis, we ...

Leus, Geert — Katholieke Universiteit Leuven

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