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- 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.
Show less - Date Issued
- 1990
- PURL
- http://purl.flvc.org/fcla/dt/14651
- Subject Headings
- Radar--Interference, Radar
- Format
- Document (PDF)
- Title
- Electric Power Distribution Systems: Optimal Forecasting of Supply-Demand Performance and Assessment of Technoeconomic Tariff Profile.
- Creator
- Melendez, Roxana, De Groff, Dolores, Neelakanta, Perambur, Florida Atlantic University, College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
- Abstract/Description
-
This study is concerned with the analyses of modern electric power-grids designed to support large supply-demand considerations in metro areas of large cities. Hence proposed are methods to determine optimal performance of the associated distribution networks vis-á-vis power availability from multiple resources (such as hydroelectric, thermal, wind-mill, solar-cell etc.) and varying load-demands posed by distinct set of consumers of domestic, industrial and commercial sectors. Hence,...
Show moreThis study is concerned with the analyses of modern electric power-grids designed to support large supply-demand considerations in metro areas of large cities. Hence proposed are methods to determine optimal performance of the associated distribution networks vis-á-vis power availability from multiple resources (such as hydroelectric, thermal, wind-mill, solar-cell etc.) and varying load-demands posed by distinct set of consumers of domestic, industrial and commercial sectors. Hence, developing the analytics on optimal power-distribution across pertinent power-grids are verified with the models proposed. Forecast algorithms and computational outcomes on supply-demand performance are indicated and illustratively explained using real-world data sets. This study on electric utility takes duly into considerations of both deterministic (technological factors) as well as stochastic variables associated with the available resource-capacity and demand-profile details. Thus, towards forecasting exercise as above, a representative load-curve (RLC) is defined; and, it is optimally determined using an Artificial Neural Network (ANN) method using the data availed on supply-demand characteristics of a practical power-grid. This RLC is subsequently considered as an input parametric profile on tariff policies associated with electric power product-cost. This research further focuses on developing an optimal/suboptimal electric-power distribution scheme across power-grids deployed between multiple resources and different sets of user demands. Again, the optimal/suboptimal decisions are enabled using ANN-based simulations performed on load sharing details. The underlying supply-demand forecasting on distribution service profile is essential to support predictive designs on the amount of power required (or to be generated from single and/or multiple resources) versus distributable shares to different consumers demanding distinct loads. Another topic addressed refers to a business model on a cost reflective tariff levied in an electric power service in terms of the associated hedonic heuristics of customers versus service products offered by the utility operators. This model is based on hedonic considerations and technoeconomic heuristics of incumbent systems In the ANN simulations as above, bootstrapping technique is adopted to generate pseudo-replicates of the available data set and they are used to train the ANN net towards convergence. A traditional, multilayer ANN architecture (implemented with feed-forward and backpropagation techniques) is designed and modified to support a fast convergence algorithm, used for forecasting and in load-sharing computations. Underlying simulations are carried out using case-study details on electric utility gathered from the literature. In all, ANN-based prediction of a representative load-curve to assess power-consumption and tariff details in electrical power systems supporting a smart-grid, analysis of load-sharing and distribution of electric power on smart grids using an ANN and evaluation of electric power system infrastructure in terms of tariff worthiness deduced via hedonic heuristics, constitute the major thematic efforts addressed in this research study.
Show less - Date Issued
- 2019
- PURL
- http://purl.flvc.org/fau/fd/FA00013242
- Subject Headings
- Electric power distribution, Supply and demand--Forecasting, Artificial neural networks, Tariff
- Format
- Document (PDF)
- 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.
Show less - Date Issued
- 1999
- PURL
- http://purl.flvc.org/fcla/dt/15660
- Subject Headings
- Neural network (Computer science), Asynchronous transfer mode
- Format
- Document (PDF)
- 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.
Show less - Date Issued
- 1996
- PURL
- http://purl.flvc.org/fcla/dt/15278
- Subject Headings
- Radar, Signal processing, Radar cross sections, Stealth aircraft
- Format
- Document (PDF)
- 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.
Show less - 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)
