Engineering Education and Research Using MATLAB

MATLAB is a software package used primarily in the field of engineering for signal processing, numerical data analysis, modeling, programming, simulation, and computer graphic visualization. In the last few years, it has become widely accepted as an efficient tool, and, therefore, its use has significantly increased in scientific communities and academic institutions. This book consists of 20 chapters presenting research works using MATLAB tools. Chapters include techniques for programming and developing Graphical User Interfaces (GUIs), dynamic systems, electric machines, signal and image processing, power electronics, mixed signal circuits, genetic programming, digital watermarking, control systems, time-series regression modeling, and artificial neural networks

Réflectométrie appliquée à la détection de défauts non francs dans les torons de câbles

Ces travaux de thèse portent sur la détection de défauts non francs dans des structures filaires particulières : les lignes de transmission a multiconducteurs (MTL), aussi appelées torons de câbles. Couramment employées pour le diagnostic de réseaux filaires, les méthodes par réflectométrie ne sont, pour l'heure, pas suffisamment performantes pour détecter de tels défauts. Par ailleurs, elles n'ont, en général, été étudiées et développées que pour des lignes simples, ou les phénomènes de couplages électromagnétiques entre les conducteurs (diaphonie) ne sont pas présents. Ces derniers sont cependant porteurs d'information supplémentaire sur l'état du câble. Les utiliser permettrait d'accroître la sensibilité de détection aux défauts. L'objectif est de proposer une nouvelle méthode de réflectométrie, tirant profit des signaux de diaphonie pour détecter les défauts non francs. Une telle méthode présente également l'avantage d'être adaptée aux structures en toron. Après avoir étudié l'impact d'un défaut non franc sur les paramètres caractéristiques d'une MTL et sur les signaux de diaphonie, une méthode, la "Cluster Time Frequency Domain Reflectometry ", a pu être proposée. Il s'agit d'un procédé en trois étapes. Des mesures par réflectométrie temporelle sont tout d'abord réalisées à l'entrée de la ligne à diagnostiquer. Tous les signaux présents, y compris ceux de diaphonie, sont enregistrés. Un traitement temps-fréquence leur est ensuite appliqué afin d'amplifier la présence d'éventuels défauts. Enfin, un algorithme de clustering, spécifiquement développé pour le diagnostic filaire, est utilisé de manière a bénéficier de l'ensemble de l'information disponibleResearch works presented in this thesis rely on detecting soft faults (incipient faults) in specic wiring structures : multiconductor transmission lines (MTL), also known as bundles of wires. Reflectometry methods, often used for the diagnosis of wiring networks, aren't for now efficient enough at detecting such defects. Besides, they have been designed for single lines only, where electromagnetic coupling between conductors (crosstalk) is not to be considered. However such phenomenon can provide more information about the state of the cable. Using this information could enable us to detect soft faults more easily. Our goal is to propose a new reflectometry method, which takes advantage of crosstalk signals in order to detect incipient faults. Such a tool has also the advantage of being well-adapted to bundles of cables. Thanks to the preliminary study of the impact of soft faults on the characteristic parameters of a MTL and on crosstalk signals, a method called "Cluster Time Frequency Domain Reflectometry ", has been proposed. It is a three step process. Firts temporal reflectometry measurements are made at the beginning of the line under test. All the available signals, even crosstalk ones, are recorded. A time-frequency process is then applied on them, in order to amplify the presence of defects. Finally, a clustering algorithm, that has been specically developed for wiring diagnosis, is used to benefit from the whole available informationPARIS-EST-Université (770839901) / SudocSudocFranceF

Advances in Image Processing, Analysis and Recognition Technology

For many decades, researchers have been trying to make computers’ analysis of images as effective as the system of human vision is. For this purpose, many algorithms and systems have previously been created. The whole process covers various stages, including image processing, representation and recognition. The results of this work can be applied to many computer-assisted areas of everyday life. They improve particular activities and provide handy tools, which are sometimes only for entertainment, but quite often, they significantly increase our safety. In fact, the practical implementation of image processing algorithms is particularly wide. Moreover, the rapid growth of computational complexity and computer efficiency has allowed for the development of more sophisticated and effective algorithms and tools. Although significant progress has been made so far, many issues still remain, resulting in the need for the development of novel approaches

Analysis of speech and other sounds

This thesis comprises a study of various types of signal processing techniques, applied to the tasks of extracting information from speech, cough, and dolphin sounds. Established approaches to analysing speech sounds for the purposes of low data rate speech encoding, and more generally to determine the characteristics of the speech signal, are reviewed. Two new speech processing techniques, shift-and-add and CLEAN (which have previously been applied in the field of astronomical image processing), are developed and described in detail. Shift-and-add is shown to produce a representation of the long-term "average" characteristics of the speech signal. Under certain simplifying assumptions, this can be equated to the average glottal excitation. The iterative deconvolution technique called CLEAN is employed to deconvolve the shift-and-add signal from the speech signal. Because the resulting "CLEAN" signal has relatively few non-zero samples, it can be directly encoded at a low data rate. The performance of a low data rate speech encoding scheme that takes advantage of this attribute of CLEAN is examined in detail. Comparison with the multi-pulse LP C approach to speech coding shows that the new method provides similar levels of performance at medium data rates of about 16kbit/s. The changes that occur in the character of a person's cough sounds when that person is afflicted with asthma are outlined. The development and implementation of a micro-computer-based cough sound analysis system, designed to facilitate the ongoing study of these sounds, is described. The system performs spectrographic analysis on the cough sounds. A graphical user interface allows the sound waveforms and spectra to be displayed and examined in detail. Preliminary results are presented, which indicate that the spectral content of cough sounds are changed by asthma. An automated digital approach to studying the characteristics of Hector's dolphin vocalisations is described. This scheme characterises the sounds by extracting descriptive parameters from their time and frequency domain envelopes. The set of parameters so obtained from a sample of click sequences collected from free-ranging dolphins is analysed by principal component analysis. Results are presented which indicate that Hector's dolphins produce only a small number of different vocal sounds. In addition to the statistical analysis, several of the clicks, which are assumed to be used for echo-location, are analysed in terms of their range-velocity ambiguity functions. The results suggest that Hector's dolphins can distinguish targets separated in range by about 2cm, but are unable to separate targets that differ only in their velocity