About Peihao Li Peihao Li Ph.D., Electrical and Computer Engineering Signal processing semi-classical signal analysis image processing machine learning optimization scalability Decoding stream processing APIs Events Presented Events Sep 18 - Sep 24, 2022 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.
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.
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