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Physical Sciences and Mathematics Commons™
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- Artificial Neural Network (2)
- Jamming FM Signals (2)
- Pattern Recognition (2)
- Signal Classification (2)
- Blind Deconvolution (1)
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- Blur recontruction (1)
- Breast Cancer (1)
- Composite (1)
- Compressive Sampling (1)
- Compressive Sensing (1)
- Deconvolution (1)
- Diagnosis (1)
- EGFR (1)
- Fiber Bragg Grating (1)
- Image recontruction (1)
- Neural Network Architecture (1)
- Noninvasive (1)
- Optic (1)
- Polarization Maintaining (1)
- Raman (1)
- Spectroscopy (1)
- Strain (1)
- Structural Health Monitoring (1)
- Wideband Frequency Modulation (1)
Articles 1 - 5 of 5
Full-Text Articles in Physical Sciences and Mathematics
Bragg Gratings In Polarization Maintaining Optical Fiber As Three Dimensional Strain Sensor, Joel Quintana
Bragg Gratings In Polarization Maintaining Optical Fiber As Three Dimensional Strain Sensor, Joel Quintana
Open Access Theses & Dissertations
Fiber-Bragg Gratings (FBG) for Structural Health Monitoring (SHM) have been studied extensively as they offer electrically passive operation, electromagnetic interference (EMI) immunity, high sensitivity and multiplexing as compared to conventional electric strain sensors. FBG sensors written within polarization maintaining (PM) optical fiber offer ad- ditional dimensions of strain measurement, greatly reducing the number of sensors needed to properly monitor a structure. This reduction however, adds complexity to the dis- crimination of the sensorâ??s optical response to its corresponding applied strains. This Dissertation defines the set of algorithms needed to measure planar strain using PM-FBGs exclusively. It defines the minimum number …
Compressive Vector Reconstruction: Hypothesis For Blind Image Deconvolution, Alonso Orea Amador
Compressive Vector Reconstruction: Hypothesis For Blind Image Deconvolution, Alonso Orea Amador
Open Access Theses & Dissertations
Alternative imaging devices propose to acquire and compress images simultaneously. These devices are based on the compressive sensing (CS) theory. A reduction in the measurement required for reconstruction without a post-compression sub-system allows imaging devices to become simpler, smaller, and cheaper. In this research, we propose a new algorithm to compress and reconstruct blurred images for CS imaging devices. Blur effect in images is common due to relative motion, lens, limited aperture dimensions, lack of focus, and/or atmospheric turbulence. Our intention is to compress a blurred image with CS techniques and then reconstruct a blur-free version using the proposed algorithm. …
Optimization Of Neural Network Architecture For Classification Of Radar Jamming Fm Signals, Alberto Soto
Optimization Of Neural Network Architecture For Classification Of Radar Jamming Fm Signals, Alberto Soto
Open Access Theses & Dissertations
Radar jamming signal classification is valuable when situational awareness of radar systems is sought out for timely deployment of electronic support measures. Our Thesis shows that artificial neural networks can be utilized for effective and efficient signal classification. The goal is to optimize an artificial Neural Network (NN) approach capable of distinguishing between two common radar waveforms, namely bandlimited white Gaussian jamming noise (BWGN) and the ubiquitous linearly frequency modulated (LFM) signal. This is made possible by creating a theoretical framework for NN architecture testing that leads to a high probability of detection (PD) and a low probability of false …
Classification Of Radar Jammer Fm Signals Using A Neural Network Approach, Ariadna Estefania Mendoza
Classification Of Radar Jammer Fm Signals Using A Neural Network Approach, Ariadna Estefania Mendoza
Open Access Theses & Dissertations
A Neural Network (NN) used to classify radar signals is proposed for the purpose of military survivability and lethality analysis. The goal of the NN is to correctly differentiate Frequency-Modulated (FM) signals from Additive White Gaussian Noise (AWGN) using limited signal pre-processing. The FM signals used to test the NN approach are the linear or chirp FM and the power-law FM. Preliminary simulations using the moments of the signals in the time and frequency domain yielded better results in the frequency domain, suggesting that time domain training would not be as effective frequency domain training. To test this hypoThesis, we …
Label-Free Raman Imaging To Monitor Breast Tumor Signatures, John Ciubuc
Label-Free Raman Imaging To Monitor Breast Tumor Signatures, John Ciubuc
Open Access Theses & Dissertations
Methods built on Raman spectroscopy have shown major potential in describing and discriminating between malignant and benign specimens. Accurate, real-time medical diagnosis benefits in substantial improvements through this vibrational optical method. Not only is acquisition of data possible in milliseconds and analysis in minutes, Raman allows concurrent detection and monitoring of all biological components. Besides validating a significant Raman signature distinction between non-tumorigenic (MCF-10A) and tumorigenic (MCF-7) breast epithelial cells, this study reveals a label-free method to assess overexpression of epidermal growth factor receptors (EGFR) in tumor cells. EGFR overexpression sires Raman features associated with phosphorylated threonine and serine, and …