945 resultados para Acoustic Arrays, Array Signal Processing, Calibration, Speech Enhancement


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Die A4-Kollaboration am Mainzer Mikrotron MAMI erforscht die Struktur des Protons mit Hilfe der elastischen Streuung polarisierter Elektronen an unpolarisiertem Wasserstoff. Bei longitudinaler Polarisation wird die paritätsverletzende Asymmetrie im Wirkungsquerschnitt gemessen, die Aufschluss über den Strangeness-Beitrag zu den Vektor-Formfaktoren des Protons gibt. Insbesondere wurde eine Messung für Rückwärtsstreuwinkel bei einer Elektronenstrahlenergie von 319 MeV durchgeführt, die zusammen mit einem unter Vorwärtsstreuung bei gleichem Impulsübertrag bestimmten Wert die Separation der magnetischen und elektrischen Strangeness-Formfaktoren erlaubt. Im Rahmen der vorliegenden Arbeit wurde ein Elektroniksystem zur Energiemessung und Histogrammierung der auftretenden Einzelereignisse aufgebaut, das eine vernetzte Struktur aus 1022 Einzelkanälen besitzt und zur Verarbeitung einer Gesamtereignisrate von 100 MHz ausgelegt wurde. Für den experimentellen Betrieb wurden für alle Kanäle erforderliche Qualitäts-prüfungen und Eichmessungen vorgenommen. Die volle Funktionsfähigkeit des Systems zur Durchführung eines Zählratenexperiments für die paritätsverletzende Asymmetrie im Bereich von 10^{-6} wurde demonstriert. Um den bei rückwärtigen Streuwinkeln dominierenden inelastischen Untergrund an Photonen in den Spektren zu reduzieren, wurde das System außerdem um ein Taggersystem für Elektronen erweitert. Das Ergebnis einer vorläufigen Analyse für die paritätsverletzende Asymmetrie im Streuquerschnitt von longitudinal polarisierten Elektronen an unpolarisierten Protonen unter Rückwärtsstreuung bei einem Viererimpulsübertrag Q^2 = 0.23 GeV^2/c^2 beträgt A{PV}=(-16.37 +- 0.93 {stat} +- 0.69 {syst}) ppm. Für die Differenz der gemessenen Asymmetrie A{PV} und der theoretischen Vorhersage ohne Strangeness A{0}=(-16.27 +- 1.22) ppm ergibt sich A{S}= A{PV} - A{0} = (-0.10+-1.68) ppm. Mit dem bereits vorliegenden Wert der Vorwärtsstreuung von A{PV} = (-5.59+- 0.57 {stat} +- 0.29 {syst}) ppm kann ein Wert für den magnetischen bzw. elektrischen Formfaktor von G{M}^s = -0.01+- 0.15 bzw. G{E}^s = 0.034 +- 0.050 ermittelt werden.

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Beamforming entails joint processing of multiple signals received or transmitted by an array of antennas. This thesis addresses the implementation of beamforming in two distinct systems, namely a distributed network of independent sensors, and a broad-band multi-beam satellite network. With the rising popularity of wireless sensors, scientists are taking advantage of the flexibility of these devices, which come with very low implementation costs. Simplicity, however, is intertwined with scarce power resources, which must be carefully rationed to ensure successful measurement campaigns throughout the whole duration of the application. In this scenario, distributed beamforming is a cooperative communication technique, which allows nodes in the network to emulate a virtual antenna array seeking power gains in the order of the size of the network itself, when required to deliver a common message signal to the receiver. To achieve a desired beamforming configuration, however, all nodes in the network must agree upon the same phase reference, which is challenging in a distributed set-up where all devices are independent. The first part of this thesis presents new algorithms for phase alignment, which prove to be more energy efficient than existing solutions. With the ever-growing demand for broad-band connectivity, satellite systems have the great potential to guarantee service where terrestrial systems can not penetrate. In order to satisfy the constantly increasing demand for throughput, satellites are equipped with multi-fed reflector antennas to resolve spatially separated signals. However, incrementing the number of feeds on the payload corresponds to burdening the link between the satellite and the gateway with an extensive amount of signaling, and to possibly calling for much more expensive multiple-gateway infrastructures. This thesis focuses on an on-board non-adaptive signal processing scheme denoted as Coarse Beamforming, whose objective is to reduce the communication load on the link between the ground station and space segment.

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Assessment of the integrity of structural components is of great importance for aerospace systems, land and marine transportation, civil infrastructures and other biological and mechanical applications. Guided waves (GWs) based inspections are an attractive mean for structural health monitoring. In this thesis, the study and development of techniques for GW ultrasound signal analysis and compression in the context of non-destructive testing of structures will be presented. In guided wave inspections, it is necessary to address the problem of the dispersion compensation. A signal processing approach based on frequency warping was adopted. Such operator maps the frequencies axis through a function derived by the group velocity of the test material and it is used to remove the dependence on the travelled distance from the acquired signals. Such processing strategy was fruitfully applied for impact location and damage localization tasks in composite and aluminum panels. It has been shown that, basing on this processing tool, low power embedded system for GW structural monitoring can be implemented. Finally, a new procedure based on Compressive Sensing has been developed and applied for data reduction. Such procedure has also a beneficial effect in enhancing the accuracy of structural defects localization. This algorithm uses the convolutive model of the propagation of ultrasonic guided waves which takes advantage of a sparse signal representation in the warped frequency domain. The recovery from the compressed samples is based on an alternating minimization procedure which achieves both an accurate reconstruction of the ultrasonic signal and a precise estimation of waves time of flight. Such information is used to feed hyperbolic or elliptic localization procedures, for accurate impact or damage localization.

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The upgrade of the Mainz Mikrotron (MAMI) electron accelerator facility in 2007 which raised the beam energy up to 1.5,GeV, gives the opportunity to study strangeness production channels through electromagnetic process. The Kaon Spectrometer (KAOS) managed by the A1 Collaboration, enables the efficient detection of the kaons associated with strangeness electroproduction. Used as a single arm spectrometer, it can be combined with the existing high-resolution spectrometers for exclusive measurements in the kinematic domain accessible to them.rnrnFor studying hypernuclear production in the ^A Z(e,e'K^+) _Lambda ^A(Z-1) reaction, the detection of electrons at very forward angles is needed. Therefore, the use of KAOS as a double-arm spectrometer for detection of kaons and the electrons at the same time is mandatory. Thus, the electron arm should be provided with a new detector package, with high counting rate capability and high granularity for a good spatial resolution. To this end, a new state-of-the-art scintillating fiber hodoscope has been developed as an electron detector.rnrnThe hodoscope is made of two planes with a total of 18432 scintillating double-clad fibers of 0.83 mm diameter. Each plane is formed by 72 modules. Each module is formed from a 60deg slanted multi-layer bundle, where 4 fibers of a tilted column are connected to a common read out. The read-out is made with 32 channels of linear array multianode photomultipliers. Signal processing makes use of newly developed double-threshold discriminators. The discriminated signal is sent in parallel to dead-time free time-to-digital modules and to logic modules for triggering purposes.rnrnTwo fiber modules were tested with a carbon beam at GSI, showing a time resolution of 220 ps (FWHM) and a position residual of 270 microm m (FWHM) with a detection efficiency epsilon>99%.rnrnThe characterization of the spectrometer arm has been achieved through simulations calculating the transfer matrix of track parameters from the fiber detector focal plane to the primary vertex. This transfer matrix has been calculated to first order using beam transport optics and has been checked by quasielastic scattering off a carbon target, where the full kinematics is determined by measuring the recoil proton momentum. The reconstruction accuracy for the emission parameters at the quasielastic vertex was found to be on the order of 0.3 % in first test realized.rnrnThe design, construction process, commissioning, testing and characterization of the fiber hodoscope are presented in this work which has been developed at the Institut für Kernphysik of the Johannes Gutenberg - Universität Mainz.

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Users of cochlear implants (auditory aids, which stimulate the auditory nerve electrically at the inner ear) often suffer from poor speech understanding in noise. We evaluate a small (intermicrophone distance 7 mm) and computationally inexpensive adaptive noise reduction system suitable for behind-the-ear cochlear implant speech processors. The system is evaluated in simulated and real, anechoic and reverberant environments. Results from simulations show improvements of 3.4 to 9.3 dB in signal to noise ratio for rooms with realistic reverberation and more than 18 dB under anechoic conditions. Speech understanding in noise is measured in 6 adult cochlear implant users in a reverberant room, showing average improvements of 7.9–9.6 dB, when compared to a single omnidirectional microphone or 1.3–5.6 dB, when compared to a simple directional two-microphone device. Subjective evaluation in a cafeteria at lunchtime shows a preference of the cochlear implant users for the evaluated device in terms of speech understanding and sound quality.

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Medical instrumentation used in diagnosis and treatment relies on the accurate detection and processing of various physiological events and signals. While signal detection technology has improved greatly in recent years, there remain inherent delays in signal detection/ processing. These delays may have significant negative clinical consequences during various pathophysiological events. Reducing or eliminating such delays would increase the ability to provide successful early intervention in certain disorders thereby increasing the efficacy of treatment. In recent years, a physical phenomenon referred to as Negative Group Delay (NGD), demonstrated in simple electronic circuits, has been shown to temporally advance the detection of analog waveforms. Specifically, the output is temporally advanced relative to the input, as the time delay through the circuit is negative. The circuit output precedes the complete detection of the input signal. This process is referred to as signal advance (SA) detection. An SA circuit model incorporating NGD was designed, developed and tested. It imparts a constant temporal signal advance over a pre-specified spectral range in which the output is almost identical to the input signal (i.e., it has minimal distortion). Certain human patho-electrophysiological events are good candidates for the application of temporally-advanced waveform detection. SA technology has potential in early arrhythmia and epileptic seizure detection and intervention. Demonstrating reliable and consistent temporally advanced detection of electrophysiological waveforms may enable intervention with a pathological event (much) earlier than previously possible. SA detection could also be used to improve the performance of neural computer interfaces, neurotherapy applications, radiation therapy and imaging. In this study, the performance of a single-stage SA circuit model on a variety of constructed input signals, and human ECGs is investigated. The data obtained is used to quantify and characterize the temporal advances and circuit gain, as well as distortions in the output waveforms relative to their inputs. This project combines elements of physics, engineering, signal processing, statistics and electrophysiology. Its success has important consequences for the development of novel interventional methodologies in cardiology and neurophysiology as well as significant potential in a broader range of both biomedical and non-biomedical areas of application.

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Time-based localization techniques such as multilateration are favoured for positioning to wide-band signals. Applying the same techniques with narrow-band signals such as GSM is not so trivial. The process is challenged by the needs of synchronization accuracy and timestamp resolution both in the nanoseconds range. We propose approaches to deal with both challenges. On the one hand, we introduce a method to eliminate the negative effect of synchronization offset on time measurements. On the other hand, we propose timestamps with nanoseconds accuracy by using timing information from the signal processing chain. For a set of experiments, ranging from sub-urban to indoor environments, we show that our proposed approaches are able to improve the localization accuracy of TDOA approaches by several factors. We are even able to demonstrate errors as small as 10 meters for outdoor settings with narrow-band signals.

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In free viewpoint applications, the images are captured by an array of cameras that acquire a scene of interest from different perspectives. Any intermediate viewpoint not included in the camera array can be virtually synthesized by the decoder, at a quality that depends on the distance between the virtual view and the camera views available at decoder. Hence, it is beneficial for any user to receive camera views that are close to each other for synthesis. This is however not always feasible in bandwidth-limited overlay networks, where every node may ask for different camera views. In this work, we propose an optimized delivery strategy for free viewpoint streaming over overlay networks. We introduce the concept of layered quality-of-experience (QoE), which describes the level of interactivity offered to clients. Based on these levels of QoE, camera views are organized into layered subsets. These subsets are then delivered to clients through a prioritized network coding streaming scheme, which accommodates for the network and clients heterogeneity and effectively exploit the resources of the overlay network. Simulation results show that, in a scenario with limited bandwidth or channel reliability, the proposed method outperforms baseline network coding approaches, where the different levels of QoE are not taken into account in the delivery strategy optimization.

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SNP genotyping arrays have been developed to characterize single-nucleotide polymorphisms (SNPs) and DNA copy number variations (CNVs). The quality of the inferences about copy number can be affected by many factors including batch effects, DNA sample preparation, signal processing, and analytical approach. Nonparametric and model-based statistical algorithms have been developed to detect CNVs from SNP genotyping data. However, these algorithms lack specificity to detect small CNVs due to the high false positive rate when calling CNVs based on the intensity values. Association tests based on detected CNVs therefore lack power even if the CNVs affecting disease risk are common. In this research, by combining an existing Hidden Markov Model (HMM) and the logistic regression model, a new genome-wide logistic regression algorithm was developed to detect CNV associations with diseases. We showed that the new algorithm is more sensitive and can be more powerful in detecting CNV associations with diseases than an existing popular algorithm, especially when the CNV association signal is weak and a limited number of SNPs are located in the CNV.^

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Recordings from the PerenniAL Acoustic Observatory in the Antarctic ocean (PALAOA) show seasonal acoustic presence of 4 Antarctic ice-breeding seal species (Ross seal, Ommatophoca rossii, Weddell seal, Leptonychotes weddellii, crabeater, Lobodon carcinophaga, and leopard seal, Hydrurga leptonyx). Apart from Weddell seals, inhabiting the fast-ice in Atka Bay, the other three (pack-ice) species however have to date never (Ross and leopard seal) or only very rarely (crabeater seals) been sighted in the Atka Bay region. The aim of the PASATA project is twofold: the large passive acoustic hydrophone array (hereafter referred to as large array) aims to localize calling pack-ice pinniped species to obtain information on their location and hence the ice habitat they occupy. This large array consists of four autonomous passive acoustic recorders with a hydrophone sensor deployed through a drilled hole in the sea ice. The PASATA recordings are time-stamped and can therefore be coupled to the PALAOA recordings so that the hydrophone array spans the bay almost entirely from east to west. The second, smaller hydrophone array (hereafter referred to as small array), also consists of four autonomous passive acoustic recorders with hydrophone sensors deployed through drilled holes in the sea ice. The smaller array was deployed within a Weddell seal breeding colony, located further south in the bay, just off the ice shelf. Male Weddell seals are thought to defend underwater territories around or near tide cracks and breathing holes used by females. Vocal activity increases strongly during the breeding season and vocalizations are thought to be used underwater by males for the purpose of territorial defense and advertisement. With the smaller hydrophone array we aim to investigate underwater behaviour of vocalizing male and female Weddell seals to provide further information on underwater movement patterns in relation to the location of tide cracks and breathing holes. As a pilot project, one on-ice and three underwater camera systems have been deployed near breathing holes to obtain additional visual information on Weddell seal behavioural activity. Upon each visit in the breeding colony, a census of colony composition on the ice (number of animals, sex, presence of dependent pups, presence and severity of injuries-indicative of competition intensity) as well as GPS readings of breathing holes and positions of hauled out Weddell seals are taken.

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In the last two decades, there has been an important increase in research on speech technology in Spain, mainly due to a higher level of funding from European, Spanish and local institutions and also due to a growing interest in these technologies for developing new services and applications. This paper provides a review of the main areas of speech technology addressed by research groups in Spain, their main contributions in the recent years and the main focus of interest these days. This description is classified in five main areas: audio processing including speech, speaker characterization, speech and language processing, text to speech conversion and spoken language applications. This paper also introduces the Spanish Network of Speech Technologies (RTTH. Red Temática en Tecnologías del Habla) as the research network that includes almost all the researchers working in this area, presenting some figures, its objectives and its main activities developed in the last years.

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This paper presents an automatic modulation classifier for electronic warfare applications. It is a pattern recognition modulation classifier based on statistical features of the phase and instantaneous frequency. This classifier runs in a real time operation mode with sampling rates in excess of 1 Gsample/s. The hardware platform for this application is a Field Programmable Gate Array (FPGA). This AMC is subsidiary of a digital channelised receiver also implemented in the same platform.

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Nonparametric belief propagation (NBP) is a well-known particle-based method for distributed inference in wireless networks. NBP has a large number of applications, including cooperative localization. However, in loopy networks NBP suffers from similar problems as standard BP, such as over-confident beliefs and possible nonconvergence. Tree-reweighted NBP (TRW-NBP) can mitigate these problems, but does not easily lead to a distributed implementation due to the non-local nature of the required so-called edge appearance probabilities. In this paper, we propose a variation of TRWNBP, suitable for cooperative localization in wireless networks. Our algorithm uses a fixed edge appearance probability for every edge, and can outperform standard NBP in dense wireless networks.