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Radar detection techniques: Application of stochastical and fractal strategies
Title
Radar detection techniques: Application of stochastical and fractal strategies.
Creator
De Groff, Dolores F., Florida Atlantic University, Neelakanta, Perambur S.
Abstract/Description
This thesis is concerned with the evaluation of radar detection performance specific to the following target and background considerations: (1) Stochastical description and determination of the envelope statistics pertaining to radar clutter of the coastline regions. (2) Detection of low-altitude targets by sea-borne radars operating near the coastline; and (3) Fractal characterization of the ocean surface as viewed by a satellite-based radar altimeter. The first problem refers to the...
Show moreThis thesis is concerned with the evaluation of radar detection performance specific to the following target and background considerations: (1) Stochastical description and determination of the envelope statistics pertaining to radar clutter of the coastline regions. (2) Detection of low-altitude targets by sea-borne radars operating near the coastline; and (3) Fractal characterization of the ocean surface as viewed by a satellite-based radar altimeter. The first problem refers to the elucidation of the most appropriate statistics that would describe the relevant envelope distribution of the clutter caused by the dual region of sea and land of a typical coastline environment. In the second analysis, performance of the radar in terms of false-alarm and detection probabilities is predicted. The third effort addressed provides a fractal description of the ocean surface as viewed by a satellite based radar altimeter. By characterizing the ocean bed as a fractal surface, the extent to which the sea surface data contributes errors to the mispointing/autoboresight information is ascertained.
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Date Issued
1990
PURL
http://purl.flvc.org/fcla/dt/14651
Subject Headings
Radar--Interference, Radar
Format
Document (PDF)
Maximum entropy-based optimization of artificial neural networks: An application to ATM telecommunication parameter predictions
Title
Maximum entropy-based optimization of artificial neural networks: An application to ATM telecommunication parameter predictions.
Creator
Sundaram, Karthik., Florida Atlantic University, De Groff, Dolores F., Neelakanta, Perambur S., College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
Abstract/Description
This thesis addresses studies on cost-functions developed on the basis of maximum entropy principle, for applications in artificial neural network (ANN) optimization endeavors. The maximization of entropy refers to maximizing Shannon information pertinent to the difference in the output and the teacher value of an ANN. Apart from the Shannon format of the negative entropy formulation a set of Csiszar family functions are also considered. The error-measures obtained, via these maximum entropy...
Show moreThis thesis addresses studies on cost-functions developed on the basis of maximum entropy principle, for applications in artificial neural network (ANN) optimization endeavors. The maximization of entropy refers to maximizing Shannon information pertinent to the difference in the output and the teacher value of an ANN. Apart from the Shannon format of the negative entropy formulation a set of Csiszar family functions are also considered. The error-measures obtained, via these maximum entropy formulations are adopted as cost-functions in the training and prediction schedules of a test perceptron. A comparative study is done on the performance of these cost-functions in facilitating the test network towards optimization so as to predict a standard teacher function sin (.). The study is also extended to predict a parameter (such as cell delay variation) in a practical ATM telecommunication system. Concluding remarks and scope for an extended study are also indicated.
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Date Issued
1999
PURL
http://purl.flvc.org/fcla/dt/15660
Subject Headings
Neural network (Computer science), Asynchronous transfer mode
Format
Document (PDF)
Studies on carrier-free (or ultra-wideband) radar performance under clutter and stealth-target environments
Title
Studies on carrier-free (or ultra-wideband) radar performance under clutter and stealth-target environments.
Creator
Mendivil, Edwin David., Florida Atlantic University, De Groff, Dolores F., College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
Abstract/Description
This thesis is concerned with the use of ultra-wideband radar detection specific to the following target and background considerations. (1) Statistical attributes of the RCS models of stealth-targets illuminated by ultra-wideband radars. (2) Analysis of radar echo signatures of low flying stealth-targets with a background of sea-clutter and illuminated by an ultra-wideband radar. (3) Analysis of impulse echoes from simple (planar) surface(s) coated with a radar absorbing material (RAM). The...
Show moreThis thesis is concerned with the use of ultra-wideband radar detection specific to the following target and background considerations. (1) Statistical attributes of the RCS models of stealth-targets illuminated by ultra-wideband radars. (2) Analysis of radar echo signatures of low flying stealth-targets with a background of sea-clutter and illuminated by an ultra-wideband radar. (3) Analysis of impulse echoes from simple (planar) surface(s) coated with a radar absorbing material (RAM). The first problem refers to the elucidation of Swerling-Marcum type classifications of RCS fluctuation(s) to characterize the stochastical aspects of the echoes from stealth-targets illuminated by an impulse from an ultra-wideband radar. In the second analysis, performance of a radar receiver configuration, using the log-likelihood function of the signal received from a stealth target flying at low altitude over the sea-surface is predicted. The third effort addressed provides analytical representations in time-domain of echoes from planar surface(s) coated with RAM's for normal incidence of ultra-wideband short pulse illumination.
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Date Issued
1996
PURL
http://purl.flvc.org/fcla/dt/15278
Subject Headings
Radar, Signal processing, Radar cross sections, Stealth aircraft
Format
Document (PDF)
Stochastical aspects of neuronal activity, neural networks, and communication
Title
Stochastical aspects of neuronal activity, neural networks, and communication.
Creator
De Groff, Dolores F., Florida Atlantic University, Neelakanta, Perambur S., College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
Abstract/Description
By revisiting the popular framework of depicting neuronal (collective) activities as analogous to Ising's spin-glass theory of interacting magnetic spins, the contradictions that coexist with such an analogy are extracted and discussed. To alleviate such contradictions, an alternative strategy of equating the neuronal interactions to the partially anisotropic nematic phase of disorder pertaining to liquid crystals is proposed. Hence, the extent of anisotropy in the neuronal system, quantified...
Show moreBy revisiting the popular framework of depicting neuronal (collective) activities as analogous to Ising's spin-glass theory of interacting magnetic spins, the contradictions that coexist with such an analogy are extracted and discussed. To alleviate such contradictions, an alternative strategy of equating the neuronal interactions to the partially anisotropic nematic phase of disorder pertaining to liquid crystals is proposed. Hence, the extent of anisotropy in the neuronal system, quantified in terms of an order-function, is specified to elucidate the nonlinear squashing action of the input-output relations in a neuronal cell. The relevant approach thereof, is based on Langevin's theory considerations as applied to dipole molecules. Further, in view of the stochastical properties due to the inherent disorder associated with the neuronal assembly, the progression of state-transitions across the interconnected cells is modeled as a momentum flow relevant to particle dynamics. Hence, corresponding wave mechanics attributions of such a collective movement of state-transition activity are described in terms of a probabilistic wave function. Lastly, the stochastical aspects of noise-perturbed neuronal dynamics are studied via Fokker-Planck equation representing the Langevin-type relaxational (nonlinear) process associated with the neuronal states. On each of these topics portraying the stochastical characteristics of the neuronal assembly and its activities, newer and/or more exploratory inferences are made, logical conclusions are enumerated and relevant discussions are presented along with the scope for future research to be pursued.
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Date Issued
1993
PURL
http://purl.flvc.org/fcla/dt/12326
Subject Headings
Neurons--Mathematical models, Stochastic processes, Neural networks (Computer science)
Format
Document (PDF)