Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 16 of 16 for “"signal representation"”.
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Amplitude sampling for signal representation
… for conventional acquisition of bandlimited signals typically relies on uniform time sampling and assumes infinite-precision amplitude values. This thesis explores signal representation and recovery based on uniform amplitude sampling with either assuming infinite-precision timing information …
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Multidimensional Geometrical Signal Representation: Constructions and Applications
We propose a computational procedure to find all alias-free quantized sampling lattices with minimum sampling density for a given frequency support. Central to this algorithm is a novel condition linking alias-free sampling with the Fourier transform of the indicator function defined on the …
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Sparse signal representation based algorithms with application to ultrasonic array imaging
… problem of mode conversion. We propose a sparse signal representation based method for imaging solid materials in the presence of mode conversion phenomenon. In the case of two-layer imaging we model the signal propagation effect using Huygens principle and Rayleigh-Sommerfeld diffraction …
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Signal compression and reconstruction using multiple bases representation
The problem of efficient signal communication at low data rates involves, in general, the encoding of the source for maximum data compression at the transmitter end, and the reconstruction using the received information and all the available a priori or side information at the receiver end. In this …
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Sparse Representation and its Application to Multivariate Time Series Classification
In signal processing field, there are various measures that can be employed to analyse and represent the signal in order to obtain meaningful outcome. Sparse representation (SR) has continued to receive great attention as one of the well-known tools in statistical theory which among others, is used …
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Sparse Representation and its Application to Multivariate Time Series Classification
In signal processing field, there are various measures that can be employed to analyse and represent the signal in order to obtain meaningful outcome. Sparse representation (SR) has continued to receive great attention as one of the well-known tools in statistical theory which among others, is used …
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Powering Next-Generation Artificial Intelligence by Designing Three-dimensional High-Performance Neuromorphic Computing System with Memristors
… (1) neural network structure; (2) spike-based signal representation; (3) synaptic plasticity and associative memory learning [1, 2]. In this dissertation, the next-generation platform of artificial intelligence is explored by utilizing memristors to design a three-dimensional high-performance …
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Wavelets and filter banks: New results and applications
… for time-scale analysis of non-stationary signals. Wavelet analysis uses orthonormal bases in which computations can be done efficiently with multirate systems known as filter banks. This thesis develops a comprehensive set of tools for (multidimensional) multirate signal analysis and uses …
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Dictionary learning for scalable sparse image representation
Modern era of signal processing has developed many technical tools for recording and processing large and growing amount of data together with algorithms specialised for data analysis. This gives rise to new challenges in terms of data processing and modelling data representation. Fields ranging …
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Blind Estimation of Perceptual Quality for Modern Speech Communications
… and on innovative techniques to detect multiple signal distortions. The estimators do not depend on a clean reference signal hence are termed ``blind." Quality meters are then distributed along the network chain to allow for both quality degradations and quality enhancements to be handled. In …
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Distributed Space-Time Message Relaying for Uncoded/Coded Wireless Cooperative Communications
… help to provide extra observations of the source signals to the destination. Modern research in wireless communications pays more attention to these extra observations which were formerly neglected within networks. Cooperative communication processes this abundant information existing at the …
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Information Processing in the Auditory Thalamus of the Echolocating Bat, Myotis Lucifugus: Implications for Fluttering Target Detection
… which the auditory system processes time-varying signals. Echolocating bats provide a useful model to study the neural bases for the perception of time-varying signals because of their dependence on such sounds. Previous work has shown that the time-domain representation of sound undergoes a …
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Heart Rate Variability analysis in patients undergoing local anesthesia
… that affect the HRV and the large number of signal processing techniques that have been used for HRV analysis are the contributing factors of these conflicting results. The aim of this study was to investigate for the first time the effect of HRV during Brachial plexus block (local …
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Characteristics of muscle activation patterns at the ankle in stroke patients during walking.
… that features identified from the sEMG signal can be used to classify underlying impairments. A clinically viable gait analysis system has been developed, integrating an in-house wireless sEMG system synchronised with bilateral video and inertial orientation sensors. Signal processing …
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Message passing algorithms - methods and applications
… The Sum-Product algorithm on factor graph representations of the universal investment algorithms provides computationally tractable approximations to the investment strategies. Finally, we present results of simulations of our algorithms and compare them to other portfolios. We then turn …
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Signal representations: from images to irregular-domain signals
Efficient representations of high-dimensional data such as images, that can essentially describe the data with a few parameters, play a vital role in many problems in signal processing and related fields, ranging from signal compression and denoising to inverse problems. This thesis studies the …