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High speed realisation of digital filters /Tsim, Man-tat, Jimmy. January 1989 (has links)
Thesis (M. Phil.)--University of Hong Kong, 1989.
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Environmental sounds: acquisition, analysis, and representationAltaf, Muhammad Umair Bin 21 September 2015 (has links)
The dissertation presents the design and development of a systematic
signal analysis and representation framework beyond short-time Fourier
power spectrum for sounds, in particular environmental sounds. This
framework is consistent with the underlying assumptions of the
analysis method and its elements are correlated with human
perception. The sound signal has to conform to certain conditions for
its power spectrum to have a physical and perceptual meaning. We
contend that very few environmental sounds readily meet these criteria
and argue that the quantities that are traditionally used to describe
sounds need to be repurposed and, if necessary, redefined to represent
sounds by non-Fourier means. We propose a perceptuo-analytic
organization of sounds so that any environmental sound can be analyzed
based on its signal characteristics and perception.
We present environmental sound acquisition in the context of
collection and annotation of a database for the footstep sounds, a
common environmental sound, and show that it can be represented by
these unconventional means and further analyzed to produce
descriptions which are obscured with the traditional analysis. We
present a novel application of extracting gait characteristics from
the footstep sounds which is enabled by the proposed framework.
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Underwater fading channel simulator for a parametric communication systemGalvin, Ross January 1997 (has links)
No description available.
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Digital filter applications to modeling wave propagation in springs, strings, membranes and acoustical space /Van Duyne, Scott A. January 2007 (has links)
Thesis (Ph. D.)--Department of Music, Stanford University, 2007. / Includes bibliographical references (leaves 226-236).
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Enhanced Weak Signal Detection Using SVM Based Correlation AlgorithmKramer, Samuel Leonard 05 June 2024 (has links)
Traditional signal detection algorithms are often robust and are typically sufficient for high SNR data. However, the assumptions behind these methods begin to fall apart when signal period becomes either very short, or small in amplitude compared to any corruptive noise. To address this a kernel transform based cross-correlation algorithm is proposed for the application of weak signal detection. The algorithm leverages kernel methods to inflate SNR of the data and enhance the noise rejection capabilities of the traditional cross-correlation. The goal of the algorithm is to achieve detection for signals past the limits of those of the matched filter and the cross-correlation in the presence of white and colored noise. To evaluate the effectiveness of the correlation algorithm, Monte Carlo simulations are performed to determine the performance in the context of different types of noise. The performance of the algorithm will be compared against the cross-correlation and the matched filter. / Master of Science / As society advances, the tools we rely on become increasingly more intricate. Pivotal to the development of these systems is the algorithms used to process the data they collect. Particularly crucial to the field of signal processing, weak signal detection is focused on the processing of barely comprehensible data in the context of powerful noise. In recent years, advancements in weak signal detection have focused on pushing the theoretical limits of signal discernibility, especially when heavily obscured by noise. Leveraging the power of machine learning, certain AI algorithms have showcased promise in the detection of weak signals. It has yet to be seen if a foundational principle of AI called a kernel transform can be applied to classic signal detection theory to increase detection performance. This thesis will propose a kernel based detection algorithm for weak signal detection and the performance of the algorithm will be compared against previously established theory. New breakthroughs in detection algorithms facilitate improvements in active and passive sonar, medical devices and even the finance sector.
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Sampling and reconstruction of one-dimensional analogue signalsScoular, Spencer Charles January 1992 (has links)
No description available.
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Power efficient linear transmitters and the LINC techniqueHetzel, Simon Andrew January 1993 (has links)
No description available.
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Time series classificationRajan, Jebu Jacob January 1994 (has links)
No description available.
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Intelligent adaptive digital distance relaying for high resistance earth faultsLi, Kai-Kwong January 1998 (has links)
No description available.
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Geometric techniques in multiple view point correspondencesAriyawansa, D. D. A. P. January 1999 (has links)
No description available.
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