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Extensions of Dynamic Programming, Machine Learning, Discrete Optimization
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biomedical signal analysis
Pulse Shaped Waveform Characterization using the Schrödinger Operator's Spectrum
Peihao Li , Ph.D., Electrical and Computer Engineering
Sep 18, 14:00
-
16:00
B1 R4214
biomedical signal analysis
MIMIC II database
Pulse-shaped signal characterization is a fundamental problem in signal processing. One recently developed tool available to analyze non-stationary pulse-shaped waveforms with a suitable peak reconstruction is semiclassical signal analysis (SCSA). SCSA is a signal representation method that decomposes a real positive signal y(t) into a set of squared eigenfunctions through the discrete spectrum of the Schrödinger operator which is of particular interest. Beginning with an introduction to the young method, this dissertation discusses the relevant properties of SCSA and how they are utilized in signal denoising and biomedical application. Based on this, different frameworks and methodologies are proposed to leverage the advantages of the SCSA, especially in the pulse-shaped signal analysis field.
