The aim of this work is to design and create a robust speech activity detector that is able to detect speech in different languages, in a noise environment and with music on background. I decided to solve this problem by using a neural network as a classification model that assigns one of the four possible classes - silence, speech, music, or noise to the input of audio recording. The resulting tool is able to detect the speech in at least 12 languages. Speech with musical background up to 88 % accuracy and system success on noisy data reaches from 84 % (5 dB SNR) to 88 % (20 dB SNR). This tool can be used for speech activity detection in various research areas of speech processing. The main contribution is the elimination of music, which when not eliminated, significantly increases the error rate of systems for speaker identification or speech recognition.

The diploma thesis „Mechanisms modelling of multi access into mobile wireless network“ is focusing the wireless network. The diploma thesis contains basic network topology of wireless standard 802.11g and utilizes key identificators of mobile node in dependency on the distance and collision controlling function for simulation purposes. In the next part of this thesis is created LTE mobile network topology, which serves for finding key identificators. In the last part is created offload topology containing both - 802.11g and LTE network. As the result are implemented offloading algorithms, which ensure data traffic switching based on comparing 802.11g and LTE key identificators. Automatically generated and shown figures providing the key statistics are the main output of this thesis.

Wireless communications systems are used today in a variety of milieux, with a recurring theme: users and applications regularly require higher throughput. Multiple antennas enable higher throughput and/or more robust performance than single-antenna communications, with no increase in power or frequency bandwidth. Systems are required which achieve the full potential of this "space-time" communication channel under the significant challenges of time-varying fading, multiple users, and the choice of appropriate coding schemes. This dissertation is focused on solutions to these problems. For the single-user case, there are many well-known coding techniques available; in the first part of this dissertation, the performance of two of these methods are analyzed. Trained and differential modulation are simple coding techniques for single-user time-varying channels. The performance of these coding methods is characterized for a channel having a constant specular component plus a time-varying diffuse component. A first- order auto-regressive model is used to characterize diffuse channel coefficients that vary from symbol to symbol, and is shown to lead to an effective SNR that decreases with time. A lower bound on the capacity of trained modulation is found for the specular/diffuse channel. This bound is maximized over the training length, training frequency, training signal, and training power. Trained modulation is shown to have higher capacity than differential coding, despite the effective SNR penalty of trained modulation versus differential methods. The second part of the dissertation considers the multi-user, multi-antenna channel, for which capacity-approaching codes were previously unavailable. Precoding with the channel inverse is shown to provide capacity that approaches a constant as the number of users and antennas simultaneously increase. To overcome this limitation, a simple encoding algorithm is introduced that operates close to capacity at sum-rates of tens of bits/channel-use. The algorithm is a variation on channel inversion that regularizes the inverse and uses a "sphere encoder" to perturb the data to reduce the energy of the transmitted signal. Simulation results are presented which support our analysis and algorithm development.

Due to the advancement in technology and the increase in the amount of data beingtransferred through wireless channels, many developments in the techniques and speedof data transfer have been observed in the past few decades. The current trend incellular technology is transforming from 4G to 5G. So, to meet future requirements,it is highly necessary to have further improvements in technology like modulationtechniques, Channel access methods, etc. Many top research institutes around the worldare investing heavily in research and development of 5G.Radio waves have been used for a very long time in mobile phone communication,but providers are experimenting with broadcasting on millimeter waves which usehigher frequencies ranging from 6GHz to 300GHz. Data characteristics like power,SNR, interference, etc. need to be evaluated for these high frequencies. As 5G is still ininitial phases of development, there are not many testing tools to check and evaluateits performance. A testbed is a testing tool which is used for conducting rigorous,transparent, and replicable testing, experimenting and evaluating the performance ofthese propagated data at these high frequencies.The thesis work evaluates the implementation structures of the 5G testbed @15GHzand its performance in indoor and outdoor scenarios. It also talks about the methods ofsignal generation through Matlab and it’s transmission at 15GHz using Xilinx FPGAand Analog devices’ FMCOMMS5 transceiver. This data is then transmitted andreceived by patch antennas provided by Ericsson AB. Various techniques were used inorder to improve the signal, like using RF hardware components and software modules.Different channel sounding techniques were used in order to achieve the synchronizationbetween the transmitter and the receiver node in order to measure the properties ofthe channel. All of the experiments were performed by implementing a single-inputsingle-output system (SISO) module of the 5G testbed. This SISO system can be easilytransformed into a multiple-input-multiple-output system (MIMO) by replicating theoriginal SISO system.The result shares some interesting findings on the readiness of the 5G testbed for aiiiivbetter understanding of the future technology. It is concluded that this testbed providessomewhat a reliable platform to test the performance of the 5G technology. / Tack vare teknikutveckling och ökning i mängden data som sänds trådlöst, hardatatakterna ökat enormt under de senaste decennierna. Den senaste trended inomtrådlös kommunikationärövergången från 4G till 5G. För att möte framtida krav,finns det därför behov av ytterligare teknologiutveckling, t ex i modulationstekniker och kanalaccessmetoder. Många forskningsinstitut runt om i världen investerar därför i forskning och utveckling av 5G.Radiovågor har använts under väldigt lång tid för mobil kommunikation, men tillverkare och operatörer experimenterar med sändningar i millimetervågsområdet, som använder högre frekvenser i området från 6GHz till 300GHz. Egenskaper såsom effektdämpning, SNR, interferens, osv, behöver utvärderas för dessa högre frekvenser. Eftersom utvecklingen av 5G fortfarande är i en tidig fas, finns inte så många testverktygtillgängliga för prestandautvärdering. En testbädd är ett testverktyg som användsför att utföra rigorös, transparent och upprepningsbar testning, experimentering och prestandautvärdering av data som har sänts vid dessa höga frekvenser.Denna rapport utvärderar implementationsstrukturer för en 5G-testbädd vid 15GHz,och dess prestanda i inomoch utomhusscenarier. Den beskriver även metoder försignalgenerering via Matlab och sändning vid 15GHz mha Xilinx FPGA och Analog devices’ FMCOMMS5 radiomoduler. Signalen sänds sedan via patch-antenner från Ericsson AB. Olika metoder användes för att förbättra signalen, både med radiofrekvens hårdvara och mjukvarumoduler. Olika kanalmätningsmetoder har använts för att nå synkronisering mellan sändaroch mottagarnoderna, för att mäta kanalegenskaper. Alla experimenten utfördes genom att implementera en SISO-modul (en sändarresp. mottagarantenn) av 5G-testbädden. Detta SISO-system kan enkelt utökas till ett MIMO system (flera sändaroch mottagarantenner) genom att replikera SISO-systemet.Resultaten visar att 5G-testbädden är redo att användas för att nå bättre förståelse av framtida teknologin. Slutsatsen är att testbädden erbjuder en tämligen påliglig plattformför att utvärdera prestanda för 5G-teknologi.

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ITC/USA 2011 Conference Proceedings / The Forty-Seventh Annual International Telemetering Conference and Technical Exhibition / October 24-27, 2011 / Bally's Las Vegas, Las Vegas, Nevada / This paper concentrates on aircraft specific issues and impacts of utilizing a "C" band telemetry system on a new or existing instrumentation system.

Radars have been under steady development to track, identify, image, and classify targets. Modern radar systems, with the help of embedded systems, have additional comprehensive signal processing capabilities. They can extract useful information from very noisy data, e.g. interference from the environment and unwanted echoes which is collectively known as clutter in radar terms. Concerning the healthcare industry, radar applications for detection of vital signs, i.e. breathing and heart rate, have been extensively developed during the last few decades. Modern radar systems are expected to be a large part of non-intrusive monitoring in the coming smart home industry, where vital signs need to be monitored in the currently aging population. The research presented here is to break new ground in the radar-based healthcare technology, enabling detection of cold-induced shivering to such level that the micro-shivering can be clearly identified. To simplify the radar software optimization, a commercially available radar kit with demo application and a muscle model system using a vibration generator is used. The model is quantified through precise measurements. A simulated human body vital sign plus shivering is applied. By optimizing the radar software, the shivering amplitude and frequency are measured.

L'eau fait partie intégrante de la vie sur notre planète et joue un rôle important dans les études pour évaluer l'impact du changement climatique. La recherche des ressources en eau est donc très importante pour la communauté scientifique du "climat" non seulement en surveillant de près le budget régional et mondial des ressources en eau, mais aussi pour comprendre les changements dans la fréquence et l'intensité des événements météorologiques ponctuels. Cela est particulièrement vrai pour les phénomènes météorologiques extrêmes, qui ont de grands impacts socio-économiques. L'impact des tempêtes tropicales plus ou plus intenses, des méga-neiges ou des coupes de poussières est l'un des principaux domaines de la recherche climatique. Le but de mon travail de recherche est de fournir des moyens d'évaluer l'impact des changements climatiques sur les ressources en eau et de trouver des outils flexibles permettant une gestion durable de l'eau. Des études récentes ont montré que l'on peut tirer parti des ondes émises en continu par les constellations du système mondial de navigation par satellite (GNSS) pour mesurer l'humidité du sol. Cette technique de télédétection opportuniste, connue sous le nom de réflectométrie GNSS (GNSS-R), consiste à comparer l'interférence des ondes réfléchies par le sol et celles provenant directement des satellites. Dans ma thèse, je me suis concentré sur la base GNSS-R sur le rapport signal-sur-bruit (SNR) enregistré par un récepteur GNSS conventionnel avec une unique antenne pour récupérer les variations d'humidité du sol. Beaucoup d'études ont montré l'efficacité de la méthode sur les sols argileux, et j'ai démontré dans ma thèse qu'elle était tout aussi efficace sur les sols sableux à condition d'appliquer la méthode du déroulement de phase. Cette méthode que je propose a été appliquée avec succès pour déterminer les variations locales d'humidité du sol: (1) 100% du sable dans le terrain de jeu de volleyball (Toulouse, France); et (2) >85% de sable dans la zone critique sahélienne de Dahra (Sénégal). En outre, la mesure précise et continue des niveaux d'eau des rivières est un élément important de la gestion des ressources en eau, afin d'obtenir une estimation continue du débit de la rivière dans le monde. La précision de la technique GNSS-R pour l'altimétrie fluviale est son pas d'échantillonnage élevé permet de suivre les événements hydrologiques extrêmes. Deux méthodes, les moindres carrés et la technique "Larson", ont été appliquées avec succès pour déterminer les variations des hauteurs au Vietnam: (1) sur la fleuve Rouge (21 ° 2'44.04 "N, 105 ° 51'48.86" E) où les événements et changements morphologiques associés aux événements hydrologiques (tempête tropicale) en 2016; et (2) sur le delta du Mékong (9 ° 31'38.63 "N, 106 ° 12'2.01" E) où les eaux continentales interagissent avec les eaux océanique. Mon travail montre que le GNSS-R est une alternative puissante et un complément significatif aux techniques actuelles de mesure de la gestion des ressources en eau en établissant un lien entre les différentes résolutions temporelles et spatiales actuellement obtenues par les outils conventionnels (in-situ capteurs, télédétection radar, etc.). Cette technique présente le grand avantage d'être basic sur le réseau pérenne du constatation GNSS et peut donc être utilisé sur n'importe quelle station GNSS. Par conséquent, en implantant une chaîne de traitement SNR, on peut automatiquement suivre les variations des environnementaux fondamentaux, i.e. la hauteur de la rivière, la pente locale de la surface de l'eau, les zones inondées, les variations d'humidité du sol et même la hauteur de végétation. / Water is an integral part of life on our planet and it plays an important role in climatic changes. Water resources research is, therefore, very important for the climate communities to not only closely monitor the regional and global water supply budget, but to also understand changes in frequency of occurrence and strength of individual weather events. This is especially true for extreme weather events, which have great societal and economic impacts. Whether we will have more or more intense tropical storms, mega-snow events, or dust-bowls in the near or far future climate. This is one of the key focus areas of climate research. The aim of my PhD work is to provide some answers to assess the impact of future climate change threats on water resources. And we are trying to find the adaptive tools needed for sustainable water resources management. In an effort to optimize water resource management, it is crucial to improve soil moisture situation awareness. With the advent of remote sensing, soil moisture is systematically monitored at the global scale but at the expense of the temporal and/or spatial resolution. Recent studies suggested to take advantage of continuously emitted waves by the Global Navigation Satellite System (GNSS) constellations, to retrieve soil moisture. This opportunistic remote sensing technique, known as GNSS Reflectometry (GNSS-R), consists in comparing the interference of reflected waves by the ground and those which come directly from satellites. In my thesis, I focused on GNSS-R technique base on the signal-to-noise ratio (SNR) recorded by conventional GNSS receiver with single antenna to retrieve soil moisture variations. Previous studies show the efficiency of this methodology for clay soil and I demonstrate for the first time, it's efficiency for sandy soil using Unwrapping phase method. This method that I propose has been successfully applied to determine local soil moisture variations of : (1) 100% of sand in Volleyball playground (Toulouse, France); and (2) >85% of sand in the Sahelian critical zone of Dahra (Senegal). In addition, accurate and continuous measurement of river water levels is an important element in water resource management, to obtain an ongoing estimate of the river's flow around the world. The accuracy of GNSS-R technique for river altimetry is useful for detection of extreme hydrological events and to show the competition between continental and oceanic water near coastal area. The two methods, Least Square and "Larson" methods, has been successfully applied to determine local variations in Vietnam of: (1) the Red river (21°02'44.04"N, 105°51'48.86"E) to identify flood events and morphological changes associated to the hydrological events (tropical storm) in 2016; and (2) the Mekong river delta (9°31'38.63"N, 106°12'2.01"E) where continental water interacts with oceanic water. My work shows that GNSS-R is a powerful alternative and a significant complement to the current measurement techniques for managing water resource by establishing a link between the different temporal and spatial resolutions currently achieved by conventional tools (in-situ sensors, remote sensing radar, etc.). This technique has a great advantage based on already-developed and sustainable GNSS satellites networks and can be applied to any GNSS geodetic station. Therefore, by installing a processing chain of the SNR acquisitions, we are able to monitor various environmental parameters i.e. height river, local slope of water surface, flooded areas, soil moisture variations and even vegetation/plant height.

La stimulation à haute fréquence (SHF) du noyau subthalamique (NST) permet de traiter l'ensemble des symptômes moteurs de la maladie de Parkinson (MP), qui n'apparaissent que lorsque 70 % des neurones dopaminergiques de la SNc ont dégénéré. En outre, les mécanismes in fine qui permettent de retarder l'apparition des symptômes moteurs ou qui sous-tendent l'efficacité thérapeutique de la SHF du NST chez l'homme ne sont pas encore élucidés. Notre travail a porté principalement sur l'animal éveillé libre de ses mouvements. <br />Dans une première partie, nous avons analysé les effets de la SHF du NST sur le comportement moteur de rats sains et 6-OHDA et nous avons établi une corrélation entre ces effets et les taux de glutamate et de GABA extracellulaire mesurés par microdialyse intracérébrale au sein de la SNr. Ces données comportementales et neurochimiques couplées à des injections pharmacologiques intranigrales suggèrent que les dyskinésies de la patte avant induites par la SHF du NST sont médiées par le glutamate et fournissent de nouveaux arguments quant aux mécanismes de la SHF du NST dans la MP.<br />Dans une seconde partie nous avons réalisé des microdialyses intracérébrales chez des singes normaux, puis exprimant pleinement les symptômes moteurs induits par le MPTP et enfin après récupération de ces symptômes moteurs dans le but de corréler les déficits et la récupération motrice à des changements de concentration de neurotransmetteurs présents dans deux territoires striataux : le sensori-moteur et le limbique. Notre étude s'est focalisée sur la dopamine et ses métabolites, le glutamate, le GABA et la sérotonine. Nos résultats montrent que les variations de dopamine pourraient jouer un rôle important dans les mécanismes de compensation permettant la récupération de fonctions motrices normales.

Capacity improvement of Wireless Communication Systems is a very important area of current research. The goal is to increase the number of users supported by the system per unit bandwidth allotted. One important way of achieving this improvement is to use multiple antennas backed by intelligent signal processing. In this thesis, we present methods for blind separation of co-channel BPSK signals arriving at an antenna array. These methods consist of two parts, Constellation Estimation and Assignment. We give two methods for constellation estimation, the Smallest Distance Clustering and the Maximum Likelihood Estimation. While the latter is theoretically sound,the former is Computationally simple and intuitively appealing. We show that the Maximum Likelihood Constellation Estimation is well approximated by the Smallest Distance Clustering Algorithm at high SNR. The Assignment Algorithm exploits the structure of the BPSK signals. We observe that both the methods for estimating the constellation vectors perform very well at high SNR and nearly attain Cramer-Rao bounds. Using this fact and noting that the Assignment Algorithm causes negligble error at high SNR, we derive an upper bound on the probability of bit error for the above methods at high SNR. This upper bound falls very rapidly with increasing SNR, showing that our constellation estimation-assignment approach is very efficient. Simulation results are given to demonstrate the usefulness of the bounds.