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(1 - 6 of 6)
- Title
- STOCHASTIC SPIN ENTROPY.
- Creator
- NESTOR, JOSEPH CARL, Florida Atlantic University
- Abstract/Description
-
The thesis first discusses the history and general properties of entropy, concentrating on the mathematical properties. It then introduces the formalism of stochastic quantum mechanics and the stochastic Boltzmann-Gibbs-Shannon entropy, emphasizing the advantages of the stochastic formalism. The relative entropy for the spin 1/2 system is constructed in the formalisms of usual quantum mechanics and stochastic quantum mechanics. The maximum spin entropy states are then found for the quantum...
Show moreThe thesis first discusses the history and general properties of entropy, concentrating on the mathematical properties. It then introduces the formalism of stochastic quantum mechanics and the stochastic Boltzmann-Gibbs-Shannon entropy, emphasizing the advantages of the stochastic formalism. The relative entropy for the spin 1/2 system is constructed in the formalisms of usual quantum mechanics and stochastic quantum mechanics. The maximum spin entropy states are then found for the quantum mechanical relative spin entropy and the stochastic classical relative spin entropy. The latter is shown to be an acceptable candidate for a new relative spin entropy for the spin 1/2 system.
Show less - Date Issued
- 1983
- PURL
- http://purl.flvc.org/fcla/dt/14182
- Subject Headings
- Entropy, Quantum theory
- Format
- Document (PDF)
- Title
- Quantitative methodology and applications in measuring supply chain complexity.
- Creator
- Morgan, Courtney Luke, Sr., Florida Atlantic University, Han, Chingping (Jim), College of Engineering and Computer Science, Department of Ocean and Mechanical Engineering
- Abstract/Description
-
The study of this paper on entropy-based methodology for measuring and analyzing the material and information complexity across organizational interfaces within a logistical framework material and Information flows within the supply chain are often complex. The complexity analysis described in this paper can be used to highlight several issues that are critical to effective supply chain management, and for internal control. My methodology is based on the understanding that the level of...
Show moreThe study of this paper on entropy-based methodology for measuring and analyzing the material and information complexity across organizational interfaces within a logistical framework material and Information flows within the supply chain are often complex. The complexity analysis described in this paper can be used to highlight several issues that are critical to effective supply chain management, and for internal control. My methodology is based on the understanding that the level of control and predictability, as well as the dynamic characteristics and static of the flows contribute to the overall level of complexity within the supply chain. This study demonstrated that supply chain complexity is realistically understood, carefully and accurately assessed it can be used to monitor and effectively control the performance of the entire supply chain and delivery system. At the supply chain interface, the methodology can provide quantitative insights into the transfer of complexity along the supply chain.
Show less - Date Issued
- 2002
- PURL
- http://purl.flvc.org/fcla/dt/12938
- Subject Headings
- Business logistics, Entropy (Information theory)
- Format
- Document (PDF)
- Title
- Dynamics of self-system coherence: Relations of entropy and global properties.
- Creator
- McMillan, Katharine K., Florida Atlantic University, Nowak, Andrzej
- Abstract/Description
-
Dynamical systems research has found evidence that global properties of self-system, i.e., self-esteem (SE), self-stability (SS), and self-certainty (SC), emerge from coherence of self-relevant information. Self-certainty may play a role in self-esteem and self-stability. Traits were deconstructed into levels from extremely to not at all. Ss indicated frequencies of trait levels, completed Rosenberg SE, SS; and self-evaluations of traits, roles, certainty, and importance. Entropy H identifies...
Show moreDynamical systems research has found evidence that global properties of self-system, i.e., self-esteem (SE), self-stability (SS), and self-certainty (SC), emerge from coherence of self-relevant information. Self-certainty may play a role in self-esteem and self-stability. Traits were deconstructed into levels from extremely to not at all. Ss indicated frequencies of trait levels, completed Rosenberg SE, SS; and self-evaluations of traits, roles, certainty, and importance. Entropy H identifies meaningful distributions of deconstructed traits. H may be useful alternative to variance from the mean in identifying individuals for whom a trait is meaningful despite the high variability of endorsements. Low H indicated order. H correlated negatively with SC, SE, SS, ratings of traits, roles, and importance as predicted. SC accounted for some of the variance of the relations; SS, however, was found to play a greater role in the relations of entropy and global properties.
Show less - Date Issued
- 2003
- PURL
- http://purl.flvc.org/fcla/dt/12983
- Subject Headings
- Entropy, Self-esteem, Self-perception, Self-evaluation
- Format
- Document (PDF)
- Title
- A maximum entropy bandwidth extrapolation technique using wavelet subspaces.
- Creator
- Vann, Laura Dominick., Florida Atlantic University, Helmken, Henry, College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
- Abstract/Description
-
This dissertation is concerned with the development of a bandwidth extrapolation technique that performs maximum entropy estimations over wavelet subspaces. Bandwidth extrapolation techniques have been used in radar applications to improve range and cross range resolution of radar cross section (RCS) images. Comparisons are made of the performance of conventional maximum entropy estimation to maximum entropy estimation over wavelet subspaces. A least squares prediction error measure is used...
Show moreThis dissertation is concerned with the development of a bandwidth extrapolation technique that performs maximum entropy estimations over wavelet subspaces. Bandwidth extrapolation techniques have been used in radar applications to improve range and cross range resolution of radar cross section (RCS) images. Comparisons are made of the performance of conventional maximum entropy estimation to maximum entropy estimation over wavelet subspaces. A least squares prediction error measure is used to compare original measured RCS data to extrapolated data. Then a relative error is defined as the ratio of prediction error using conventional maximum entropy to prediction error using maximum entropy over wavelet subspaces. Application of the bandwidth extrapolation technique is to measured RCS data of two objects. The first object consists of two 3/8" diameter conducting spheres placed 4" apart. Measurements used are for vertical polarization and 0 degree aspect angle covering a frequency range of 8.0 to 12.3827 GHz. The second object is a 1.6 meter aluminum cone. Measurements used are for vertical polarization and 0 degree aspect angle (nose on) covering a frequency range of 4.64 to 18.00 GHz. Results are shown for extrapolate measured data plus the original data with Gaussian white noise added to noise ratios of 25 dB, 20 dB, 15 dB, and 10 dB.
Show less - Date Issued
- 1997
- PURL
- http://purl.flvc.org/fcla/dt/12531
- Subject Headings
- Maximum entropy method, Wavelets (Mathematics), Radar cross sections
- Format
- Document (PDF)
- Title
- Studies on nonlinear activity and cross-entropy considerations in neural networks.
- Creator
- Abusalah, Salahalddin Tawfiq., Florida Atlantic University, Neelakanta, Perambur S., College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
- Abstract/Description
-
The objectives of this research as deliberated in this dissertation are two-folded: (i) To study the nonlinear activity in the neural complex (real and artificial) and (ii) to analyze the learning processe(s) pertinent to an artificial neural network in the information-theoretic plane using cross-entropy error-metrics. The research efforts envisaged enclave the following specific tasks: (i) Obtaining a general solution for the Bernoulli-Riccati equation to represent a single parameter family...
Show moreThe objectives of this research as deliberated in this dissertation are two-folded: (i) To study the nonlinear activity in the neural complex (real and artificial) and (ii) to analyze the learning processe(s) pertinent to an artificial neural network in the information-theoretic plane using cross-entropy error-metrics. The research efforts envisaged enclave the following specific tasks: (i) Obtaining a general solution for the Bernoulli-Riccati equation to represent a single parameter family of S-shaped (sigmoidal) curves depicting the nonlinear activity in the neural network. (ii) Analysis of the logistic growth of output versus input values in the neural complex (real and artificial) under the consideration that the boundaries of the sets constituting the input and output entities are crisp and/or fuzzy. (iii) Construction of a set of cross-entropy error-metrics (known as Csiszar's measures) deduced in terms of the parameters pertinent to a perceptron topology and elucidation of their relative effectiveness in training the network optimally towards convergence. (iv) Presenting the methods of symmetrizing and balancing the aforesaid error-entropy measures (in the information-theoretic plane) so as to make them usable as error-metrics in the test domain. (v) Description and analysis of the dynamics of neural learning process in the information-theoretic plane for both crisp and fuzzy attributes of input values. Relevant to these topics portraying the studies on nonlinear activity and cross-entropy considerations vis-a-vis neural networks, newer and/or exploratory inferences are made, logical conclusions are enumerated and relative discussions are presented along with the scope for future research to be pursued.
Show less - Date Issued
- 1996
- PURL
- http://purl.flvc.org/fcla/dt/12447
- Subject Headings
- Neural networks (Computer science), Entropy (Information theory), Nonlinear control theory
- Format
- Document (PDF)
- Title
- Ubiquitous entropy and heat death in Philip K. Dick and Pamela Zoline.
- Creator
- Kasdorf, Krista., Florida Atlantic University, Scroggins, Mark
- Abstract/Description
-
My scientifically informed readings of Philip K. Dick's Ubik (1969) and Pamela Zoline's "The Heat Death of the Universe" (1967) consider entropy's multifarious meanings from both thermodynamics and information theory. Additionally, rather than relying upon overarching assumptions about the texts' cultural moment, I explore each fiction's presentation of entropy as negative or positive. For Dick, the loss of female mothering accelerates the heat death of late-capitalistic society, with entropy...
Show moreMy scientifically informed readings of Philip K. Dick's Ubik (1969) and Pamela Zoline's "The Heat Death of the Universe" (1967) consider entropy's multifarious meanings from both thermodynamics and information theory. Additionally, rather than relying upon overarching assumptions about the texts' cultural moment, I explore each fiction's presentation of entropy as negative or positive. For Dick, the loss of female mothering accelerates the heat death of late-capitalistic society, with entropy a negative, destructive force. Zoline, however, recognizes the injurious ramifications of entrapping women within the gender role of self-sacrificing wife/mother; her protagonist purposefully accelerates entropy production to destroy such a closed system.
Show less - Date Issued
- 2006
- PURL
- http://purl.flvc.org/fcla/dt/13359
- Subject Headings
- Entropy (Information theory), Literature and science, Science fiction, American--History and criticism, Dick, Philip K--Criticism and interpretation, Zoline, Pamela,--1941---Criticism and interpretation
- Format
- Document (PDF)
