Delay estimation of DPOAEs: Is the f1 or f2 sweep more accurate?

Distortion product otoacoustic emission (DPOAE) delay estimation has important implications for models of emission generation and cochlear mechanics. However, the DPOAE signal environment makes the accurate estimation of DPOAE onset a difficult task. To date, two Fourier domain methods have been used exclusively in f1 and f2 sweep methods for DPOAE delay estimation. However, these sweep methods suffer from serious limitations. Additionally, the two different sweep methods result in large differences in the estimated DPOAE delay, which are incompatible with the physical reality. In this study, a novel technique is employed for DPOAE latency estimation based on zero-phase filtering and penalized contrast changepoint estimation. This method has the advantage that it can be applied to a DPOAE time series evoked with a single (f1, f2) primary tone pair. The results are compared in the same human subjects against the traditional Fourier methods. The changepoint method provides support for the notion that the difference between the f1 and f2 sweeps is artifactual and that the f2 sweep times may be closer to the true delay

Ground-based synthetic aperture radar (GBSAR) interferometry for deformation monitoring

Ph. D ThesisGround-based synthetic aperture radar (GBSAR), together with interferometry, represents a powerful tool for deformation monitoring. GBSAR has inherent flexibility, allowing data to be collected with adjustable temporal resolutions through either continuous or discontinuous mode. The goal of this research is to develop a framework to effectively utilise GBSAR for deformation monitoring in both modes, with the emphasis on accuracy, robustness, and real-time capability. To achieve this goal, advanced Interferometric SAR (InSAR) processing algorithms have been proposed to address existing issues in conventional interferometry for GBSAR deformation monitoring. The proposed interferometric algorithms include a new non-local method for the accurate estimation of coherence and interferometric phase, a new approach to selecting coherent pixels with the aim of maximising the density of selected pixels and optimizing the reliability of time series analysis, and a rigorous model for the correction of atmospheric and repositioning errors. On the basis of these algorithms, two complete interferometric processing chains have been developed: one for continuous and the other for discontinuous GBSAR deformation monitoring. The continuous chain is able to process infinite incoming images in real time and extract the evolution of surface movements through temporally coherent pixels. The discontinuous chain integrates additional automatic coregistration of images and correction of repositioning errors between different campaigns. Successful deformation monitoring applications have been completed, including three continuous (a dune, a bridge, and a coastal cliff) and one discontinuous (a hillside), which have demonstrated the feasibility and effectiveness of the presented algorithms and chains for high-accuracy GBSAR interferometric measurement. Significant deformation signals were detected from the three continuous applications and no deformation from the discontinuous. The achieved results are justified quantitatively via a defined precision indicator for the time series estimation and validated qualitatively via a priori knowledge of these observing sites.China Scholarship Council (CSC), Newcastle Universit

Individual Differences in Stimulus Frequency Otoacoustic Emission Phase

Otoacoustic emissions (OAEs) are sounds that originate in the cochlea and are measured in the ear canal. OAEs provide a noninvasive tool for investigating cochlear mechanics. Stimulus-frequency OAEs (SFOAEs) are evoked by presenting a single frequency tone, called a probe tone, which have an advantage over other OAEs because they are the least influenced by cochlear nonlinearities. However, because the SFOAE are generated in the cochlea with the same frequency as the stimulus, additional techniques, such as the use of suppressor tones are needed to enable separation of the probe tone from the SFOAE. The primary goal of this investigation was to explore individual differences in SFOAE phase gradient delays. These delays were hypothesized to improve estimates of cochlear health, inferred from hearing thresholds. Efficient measures of phase gradient delays can be obtained using frequency swept tones analyzed with time-frequency filtering, such as the least squares (LS) fit. The least squares fit is a time-frequency filter because the LS fit estimates coefficients for a subset of the total signal which are then used to separate and estimate signals of interest. However, the limitations of the frequency swept tone procedure and LS fit for estimating SFOAEs are not well understood. This investigation first focused on identifying limitations of such SFOAE and refining the LS fitting procedure. It was determined that including a suppressor was necessary for obtaining optimal SFOAE estimates, and the investigation shifted from further refining the LS fitting procedure to exploration of alternative time-frequency analyses which permit clearer characterization of the various latency contributions to suppressor based SFOAEs estimates. The use of a fast, continuous filtered wavelet transform provided a unique perspective on the distribution of SFOAE energy in the time-frequency domain and confirmed that SFOAEs are a sum of both long and short latency contributions. The distributions of long and short SFOAE energy explain some the discrepancies between discrete tone and swept tone SFOAEs procedures. Predicting behavioral thresholds from SFOAE phase, magnitude, or phase and magnitude combined may be misleading when the analysis is not focused around the SFOAE latency contributions from the region where SFOAEs are most affected by cochlear damage. It was revealed that more focus should be given to understanding the best ways to separate the long and the short latencies for different stimulus parameters and individuals, in order to improve sensitivity to cochlear health

Decoding Electrophysiological Correlates of Selective Attention by Means of Circular Data

Sustaining our attention to a relevant sensory input in a complex listening environment, is of great importance for a successful auditory communication. To avoid the overload of the auditory system, the importance of the stimuli is estimated in the higher levels of the auditory system. Based on these information, the attention is drifted away from the irrelevant and unimportant stimuli. Long-term habituation, a gradual process independent from sensory adaptation, plays a major role in drifting away our attention from irrelevant stimuli. A better understanding of attention-modulated neural activity is important for shedding light on the encoding process of auditory streams. For instance, these information can have a direct impact on developing smarter hearing aid devices in which more accurate objective measures can be used to re ect the hearing capabilities of patients with hearing pathologies. As an example, an objective measures of long-term habituation with respect to di erent level of sound stimuli can be used more accurately for adjustment of hearing aid devices in comparison to verbal reports. The main goal of this thesis is to analyze the neural decoding signatures of long-term habituation and neural modulations of selective attention by exploiting circular regularities in electrophysiological (EEG) data, in which we can objectively measure the level of attentional-binding to di erent stimuli. We study, in particular, the modulations of the instantaneous phase (IP) in event related potentials (ERPs) over trials for di erent experimental settings. This is in contrast to the common approach where the ERP component of interest is computed through averaging a su ciently large number of ERP trials. It is hypothesized that a high attentional binding to a stimulus is related to a high level of IP cluster. As the attention binding reduces, IP is spread more uniformly on a unit circle. This work is divided into three main parts. In the initial part, we investigate the dynamics of long-term habituation with di erent acoustical stimuli (soft vs. loud) over ERP trials. The underlying temporal dynamics in IP and the level of phase cluster of the ERPs are assessed by tting circular probability functions (pdf) over data segments. To increase the temporal resolution of detecting times at which a signi cant change in IP occurs, an abrupt change point model at di erent pure-tone stimulations is used. In a second study, we improve upon the results and methodology by relaxing some of the constrains in order to integrate the gradual process of long-term habituation into the model. For this means, a Bayesian state-space model is proposed. In all of the aforementioned studies, we successfully classi ed between di erent stimulation levels, using solely the IP of ERPs over trials. In the second part of the thesis, the experimental setting is expanded to contain longer and more complex auditory stimuli as in real-world scenarios. Thereby, we study the neural-correlates of attention in spontaneous modulations of EEG (ongoing activity) which uses the complete temporal resolution of the signal. We show a mapping between the ERP results and the ongoing EEG activity based on IP. A Markov-based model is developed for removing spurious variations that can occur in ongoing signals. We believe the proposed method can be incorporated as an important preprocessing step for a more reliable estimation of objective measures of the level of selective attention. The proposed model is used to pre-process and classify between attending and un-attending states in a seminal dichotic tone detection experiment. In the last part of this thesis, we investigate the possibility of measuring a mapping between the neural activities of the cortical laminae with the auditory evoked potentials (AEP) in vitro. We show a strong correlation between the IP of AEPs and the neural activities at the granular layer, using mutual information.Die Aufmerksamkeit auf ein relevantes auditorisches Signal in einer komplexen H orumgebung zu lenken ist von gro er Bedeutung f ur eine erfolgreiche akustische Kommunikation. Um eine Uberlastung des H orsystems zu vermeiden, wird die Bedeutung der Reize in den h oheren Ebenen des auditorischen Systems bewertet. Basierend auf diesen Informationen wird die Aufmerksamkeit von den irrelevanten und unwichtigen Reizen abgelenkt. Dabei spielt die sog. Langzeit- Habituation, die einen graduellen Prozess darstellt der unabh angig von der sensorischen Adaptierung ist, eine wichtige Rolle. Ein besseres Verst andnis der aufmerksamkeits-modulierten neuronalen Aktivit at ist wichtig, um den Kodierungsprozess von sog. auditory streams zu beleuchten. Zum Beispiel k onnen diese Informationen einen direkten Ein uss auf die Entwicklung intelligenter H orsysteme haben bei denen genauere, objektive Messungen verwendet werden k onnen, um die H orf ahigkeiten von Patienten mit H orpathologien widerzuspiegeln. So kann beispielsweise ein objektives Ma f ur die Langzeit- Habituation an unterschiedliche Schallreize genutzt werden um - im Vergleich zu subjektiven Selbsteinsch atzungen - eine genauere Anpassung der H orsysteme zu erreichen. Das Hauptziel dieser Dissertation ist die Analyse neuronaler Dekodierungssignaturen der Langzeit- Habituation und neuronaler Modulationen der selektiver Aufmerksamkeit durch Nutzung zirkul arer Regularit aten in elektroenzephalogra schen Daten, in denen wir objektiv den Grad der Aufmerksamkeitsbindung an verschiedene Reize messen k onnen. Wir untersuchen insbesondere die Modulation der Momentanphase (engl. Instantaneous phase, IP) in ereigniskorrelierten Potenzialen (EKPs) in verschiedenen experimentellen Settings. Dies steht im Gegensatz zu dem traditionellen Ansatz, bei dem die interessierenden EKP-Komponenten durch Mittelung einer ausreichend gro en Anzahl von Einzelantworten im Zeitbereich ermittelt werden. Es wird vermutet, dass eine hohe Aufmerksamkeitsbindung an einen Stimulus mit einem hohen Grad an IP-Clustern verbunden ist. Nimmt die Aufmerksamkeitsbindung hingegen ab, so ist die Momentanphase uniform auf dem Einheitskreis verteilt. Diese Arbeit gliedert sich in drei Teile. Im ersten Teil untersuchen wir die Dynamik der Langzeit-Habituation mit verschiedenen akustischen Reizen (leise vs. laut) in EKP-Studien. Die zugrundeliegende zeitliche Dynamik der Momentanphase und die Ebene des Phasenclusters der EKPs werden durch die Anpassung von zirkul aren Wahrscheinlichkeitsfunktionen (engl. probability density function, pdf) uber Datensegmente bewertet. Mithilfe eines sog. abrupt change-point Modells wurde die zeitliche Au osung der Daten erh oht, sodass signi kante Anderungen in der Momentanphase bei verschiedenen Reintonstimulationen detektierbar sind. In einer zweiten Studie verbessern wir die Ergebnisse und die Methodik, indem wir einige der Einschr ankungen lockern, um den gradualen Prozess der Langzeit-Habituation in das abrupt changepoint Modell zu integrieren. Dazu wird ein bayes`sches Zustands-Raum-Modell vorgeschlagen. In den zuvor genannten Studien konnte erfolgreich mithilfe der Momentanphase zwischen verschiedenen Stimulationspegeln unterschieden werden. Im zweiten Teil der Arbeit wird der experimentelle Rahmen erweitert, um komplexere auditorische Reize wie in realen H orsituationen untersuchen zu k onnen. Dabei analysieren wir die neuronalen Korrelate der Aufmerksamkeit anhand spontaner Modulationen der kontinuierlichen EEG-Aktivit at, die eine zeitliche Au osung erm oglicht. Wir zeigen eine Abbildung zwischen den EKP-Ergebnissen und der kontinuierlichen EEG-Aktivit at auf Basis der Momentanphase. Ein Markov-basiertes Modell wird entwickelt, um st orende Variationen zu entfernen, die in kontinuierlichen EEG-Signalen auftreten k onnen. Wir glauben, dass die vorgeschlagene Methode als wichtiger Vorverarbeitungsschritt zur soliden objektiven Absch atzung des Aufmerksamkeitsgrades mithilfe von EEG-Daten verwendet werden kann. In einem dichotischen Tonerkennungsexperiment wird das vorgeschlagene Modell zur Vorverarbeitung der EEG-Daten und zur Klassi zierung zwischen gerichteten und ungerichteten Aufmerksamkeitszust anden erfolgreich verwendet. Im letzten Teil dieser Arbeit untersuchen wir den Zusammenhang zwischen den neuronalen Aktivit aten der kortikalen Laminae und auditorisch evozierten Potentialen (AEP) in vitro im Tiermodell. Wir zeigen eine starke Korrelation zwischen der Momentanphase der AEPs und den neuronalen Aktivit aten in der Granularschicht unter Verwendung der Transinformation

A feasibility study of the Spatio-temporal analysis of cardiac precordial vibrations

Imperial Users onl

Vision Sensors and Edge Detection

Vision Sensors and Edge Detection book reflects a selection of recent developments within the area of vision sensors and edge detection. There are two sections in this book. The first section presents vision sensors with applications to panoramic vision sensors, wireless vision sensors, and automated vision sensor inspection, and the second one shows image processing techniques, such as, image measurements, image transformations, filtering, and parallel computing

Field Trial of a Flexible Real-time Software-defined GPU-based Optical Receiver

We introduce a flexible, software-defined real-time multi-modulation format receiver implemented on an off-the-shelf general-purpose graphics processing unit (GPU). The flexible receiver is able to process 2 GBaud 2-, 4-, 8-, and 16-ary pulse-amplitude modulation (PAM) signals as well as 1 GBaud 4-, 16- and 64-ary quadrature amplitude modulation (QAM) signals, with the latter detected using a Kramers-Kronig (KK) coherent receiver. Experimental performance evaluation is shown for back-to-back. In addition, by using the JGN high speed R&D network testbed, performance is evaluated after transmission over 91 km field-deployed optical fiber and reconfigurable optical add-drop multiplexers (ROADMs).Comment: Accepted for publication at Journal of Lightwave Technology, already available via JLT Early Access, see supplied DOI. This v2 version of the article is improved w.r.t. v1 after JLT peer-review. This article is a longer journal version of the conference paper: S.P. van der Heide, et al., Real-time, Software-Defined, GPU-Based Receiver Field Trial, ECOC 2020 paper We1E5, also via arXiv:2010.1433

Study of phase noise in optical coherent systems

Le bruit de phase est un problème important dans la conception de systèmes cohérents optiques. Bien que le bruit de phase soit étudié énormément dans les communications sans fil, certains aspects de bruit de phase sont nouveaux dans des systèmes cohérents optiques. Dans cette thèse, nous explorons les statistiques de bruit de phase dans les systèmes optiques cohérentes et proposons une nouvelle technique pour améliorer la robustesse du système envers le bruit de phase. Notre première contribution traite de l’étude des statistiques de bruit de phase en présence de compensation électronique de la dispersion chromatique (CD) dans des systèmes cohérents. Nous montrons que le modèle proposé précédemment pour l’interaction de CD avec bruit de phase doit être modifié à cause d’un modèle trop simple pour la récupération de phase. Nous dérivons une expression plus précise pour le bruit de phase estimé par la récupération de phase avec décision dirigée (DD), et utilisons cette expression pour modifier les statistiques de décision pour les symboles reçus. Nous calculons le taux d’erreur binaire (BER) pour le format de transmission DQPSK semi-analytiquement en utilisant nos statistiques de décision modifiées et montrons que pour la récupération de phase idéale, le BER semi-analytique est bien assorti avec le BER simulé avec la technique Monte-Carlo (MC). Notre deuxième contribution est l’adaptation d’une technique de codage MLCM pour les systèmes cohérents limités par le bruit de phase et le bruit blanc additif Gaussien (AWGN). Nous montrons que la combinaison d’une constellation optimisée pour le bruit de phase avec MLCM offre un système robuste à complexité modérée. Nous vérifions que la performance de MLCM dans des systèmes cohérents avec constellations 16-aires se détériorés par le bruit de phase non-linéaire et de Wiener. Pour le bruit de phase non-linéaire, notre conception de MLCM démontre une performance supérieure par rapport àune conception de MLCM déjà présente dans la littérature. Pour le bruit de phase de Wiener, nous comparons deux format de transmission, constellations carrées et optimisée pour bruit de phase, et deux techniques de codage, MLCM et codage à débit uniforme. Nos résultats expérimentaux pour BER après codage suivent les mêmes tendances que le BER simulé et confirment notre conception.Phase noise is an important issue in designing today’s optical coherent systems. Although phase noise is studied heavily in wireless communications, some aspects of phase noise are novel in optical coherent systems. In this thesis we explore phase noise statistics in optical coherent systems and propose a novel technique to increase system robustness toward phase noise. Our first contribution deals with the study of phase noise statistics in the presence of electronic chromatic dispersion (CD) compensation in coherent systems. We show that previously proposed model for phase noise and CD interaction must be modified due to an overly simple model of carrier phase recovery. We derive a more accurate expression for the estimated phase noise of decision directed (DD) carrier phase recovery, and use this expression to modify the decision statistics of received symbols. We calculate bit error rate (BER) of a differential quadrature phase shift keying (DQPSK) system semi-analytically using our modified decision statistics and show that for ideal DD carrier phase recovery the semi-analytical BER matches the BER simulated via Monte-Carlo (MC) technique. We show that the semi-analytical BER is a lower bound of simulated BER from Viterbi-Viterbi (VV) carrier phase recovery for a wide range of practical system parameters. Our second contribution is concerned with adapting a multi-level coded modulation (MLCM) technique for phase noise and additive white Gaussian noise (AWGN) limited coherent system. We show that the combination of a phase noise optimized constellation with MLCM offers a phase-noise robust system at moderate complexity. We propose a numerical method to design set-partitioning (mapping bits to symbols) and optimizing code rates for minimum block error rate (BLER).We verify MLCM performance in coherent systems of 16-ary constellations impaired by nonlinear and Wiener phase noise. For nonlinear phase noise, superior performance of our MLCM design over a previously designed MLCM system is demonstrated in terms of BLER. For Wiener phase noise, we compare optimized and square 16-QAM constellations assuming either MLCM or uniform rate coding. We compare post forward error correction (FEC) BER in addition to BLER by both simulation and experiment and show that superior BLER performance is translated into post FEC BER. Our experimental post FEC BER results follow the same trends as simulated BER, validating our design