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Full-Text Articles in Signal Processing
New Methods In Wavelet Analysis For Applications Of The Wavelet Transform, Jeffrey D. Williams
New Methods In Wavelet Analysis For Applications Of The Wavelet Transform, Jeffrey D. Williams
Theses and Dissertations
A commonality in the many applications and domains where signal processing (SP)is applied is the detection of events. Detection in SP requires the identification of the occurrence of an event, within a signal, and distinguishing the occurrence from no event. In a classical application of SP, seismologists seek to detect abnormalities in an electromagnetic (EM) signal to detect or not detect the occurrence of an earthquake, represented as an anomalous EM pulse. Since many signals are noisy, such as those produced by a seismograph, it can be challenging to distinguish a significant EM pulse from incident noise. In SP, smoothing …
Heuristic Approaches For Near-Optimal Placement Of Gps-Based Multi-Static Radar Receivers In American Coastal Waters, Brandon J. Hufstetler
Heuristic Approaches For Near-Optimal Placement Of Gps-Based Multi-Static Radar Receivers In American Coastal Waters, Brandon J. Hufstetler
Theses and Dissertations
Narcotics smuggling across the Caribbean Sea is a growing concern for the United States Coast Guard. One vector for this illicit trafficking is via small aircraft. This thesis proposes a multi-static radar architecture using the Global Positioning System (GPS) constellation as a transmission source to detect these aircraft as they transit a detection fence. The system developed in this thesis relies on the forward-scatter phenomenon in which a radar shadow is cast by a target as it crosses in front of a transmitter, creating a measurable difference in the signal amplitude at the receiver. This thesis first develops a mathematical …
An Investigation Of Preliminary Feature Screening Using Signal-To-Noise Ratios, David B. Sumrell
An Investigation Of Preliminary Feature Screening Using Signal-To-Noise Ratios, David B. Sumrell
Theses and Dissertations
A new saliency metric and a new saliency screening method are developed. This new metric, the SN saliency metric, is based upon signal-to-noise ratios, where the signal is provided by a sum of squared weights associated with a given feature, and the noise is based upon a sum of squared weights associated with a reference noise feature which is injected into the data. The resultant metric allows for a direct comparison of the feature of interest with a reference noise feature which is known to be nonsalient. The SN saliency screening method, which uses the SN saliency metric, offers the …