Chaotic Transitions in Deterministic and Stochastic Dynamical Systems : : Applications of Melnikov Processes in Engineering, Physics, and Neuroscience / / Emil Simiu.

The classical Melnikov method provides information on the behavior of deterministic planar systems that may exhibit transitions, i.e. escapes from and captures into preferred regions of phase space. This book develops a unified treatment of deterministic and stochastic systems that extends the appli...

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Place / Publishing House:Princeton, NJ : : Princeton University Press, , [2014]
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Year of Publication:2014
Language:English
Series:Princeton Series in Applied Mathematics ; 51
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Chaotic Transitions in Deterministic and Stochastic Dynamical Systems : Applications of Melnikov Processes in Engineering, Physics, and Neuroscience / Emil Simiu.
Princeton, NJ : Princeton University Press, [2014]
©2002
1 online resource (240 p.) : 94 line illus.
text txt rdacontent
computer c rdamedia
online resource cr rdacarrier
text file PDF rda
Princeton Series in Applied Mathematics ; 51
Frontmatter -- Contents -- Preface -- Chapter 1. Introduction -- PART 1. FUNDAMENTALS -- Chapter 2. Transitions in Deterministic Systems and the Melnikov Function -- Chapter 3. Chaos in Deterministic Systems and the Melnikov Function -- Chapter 4. Stochastic Processes -- Chapter 5. Chaotic Transitions in Stochastic Dynamical Systems and the Melnikov Process -- PART 2. APPLICATIONS -- Chapter 6. Vessel Capsizing -- Chapter 7. Open-Loop Control of Escapes in Stochastically Excited Systems -- Chapter 8. Stochastic Resonance -- Chapter 9. Cutoff Frequency of Experimentally Generated Noise for a First-Order Dynamical System -- Chapter 10. Snap-Through of Transversely Excited Buckled Column -- Chapter 11. Wind-Induced Along-Shore Currents over a Corrugated Ocean Floor -- Chapter 12. The Auditory Nerve Fiber as a Chaotic Dynamical System -- Appendix A1 Derivation of Expression for the Melnikov Function -- Appendix A2 Construction of Phase Space Slice through Stable and Unstable Manifolds -- Appendix A3 Topological Conjugacy -- Appendix A4 Properties of Space ∑2 -- Appendix A5 Elements of Probability Theory -- Appendix A6 Mean Upcrossing Rate τu-1 for Gaussian Processes -- Appendix A7 Mean Escape Rate τ∊-1 for Systems Excited by White Noise -- References -- Index
restricted access http://purl.org/coar/access_right/c_16ec online access with authorization star
The classical Melnikov method provides information on the behavior of deterministic planar systems that may exhibit transitions, i.e. escapes from and captures into preferred regions of phase space. This book develops a unified treatment of deterministic and stochastic systems that extends the applicability of the Melnikov method to physically realizable stochastic planar systems with additive, state-dependent, white, colored, or dichotomous noise. The extended Melnikov method yields the novel result that motions with transitions are chaotic regardless of whether the excitation is deterministic or stochastic. It explains the role in the occurrence of transitions of the characteristics of the system and its deterministic or stochastic excitation, and is a powerful modeling and identification tool. The book is designed primarily for readers interested in applications. The level of preparation required corresponds to the equivalent of a first-year graduate course in applied mathematics. No previous exposure to dynamical systems theory or the theory of stochastic processes is required. The theoretical prerequisites and developments are presented in the first part of the book. The second part of the book is devoted to applications, ranging from physics to mechanical engineering, naval architecture, oceanography, nonlinear control, stochastic resonance, and neurophysiology.
Issued also in print.
Mode of access: Internet via World Wide Web.
In English.
Description based on online resource; title from PDF title page (publisher's Web site, viewed 31. Jan 2022)
Chaotic behavior in systems.
Differentiable dynamical systems.
Stochastic systems.
MATHEMATICS / Applied. bisacsh
Affine transformation.
Amplitude.
Arbitrarily large.
Attractor.
Autocovariance.
Big O notation.
Central limit theorem.
Change of variables.
Chaos theory.
Coefficient of variation.
Compound Probability.
Computational problem.
Control theory.
Convolution.
Coriolis force.
Correlation coefficient.
Covariance function.
Cross-covariance.
Cumulative distribution function.
Cutoff frequency.
Deformation (mechanics).
Derivative.
Deterministic system.
Diagram (category theory).
Diffeomorphism.
Differential equation.
Dirac delta function.
Discriminant.
Dissipation.
Dissipative system.
Dynamical system.
Eigenvalues and eigenvectors.
Equations of motion.
Even and odd functions.
Excitation (magnetic).
Exponential decay.
Extreme value theory.
Flow velocity.
Fluid dynamics.
Forcing (recursion theory).
Fourier series.
Fourier transform.
Fractal dimension.
Frequency domain.
Gaussian noise.
Gaussian process.
Harmonic analysis.
Harmonic function.
Heteroclinic orbit.
Homeomorphism.
Homoclinic orbit.
Hyperbolic point.
Inference.
Initial condition.
Instability.
Integrable system.
Invariant manifold.
Iteration.
Joint probability distribution.
LTI system theory.
Limit cycle.
Linear differential equation.
Logistic map.
Marginal distribution.
Moduli (physics).
Multiplicative noise.
Noise (electronics).
Nonlinear control.
Nonlinear system.
Ornstein-Uhlenbeck process.
Oscillation.
Parameter space.
Parameter.
Partial differential equation.
Perturbation function.
Phase plane.
Phase space.
Poisson distribution.
Probability density function.
Probability distribution.
Probability theory.
Probability.
Production-possibility frontier.
Relative velocity.
Scale factor.
Shear stress.
Spectral density.
Spectral gap.
Standard deviation.
Stochastic process.
Stochastic resonance.
Stochastic.
Stream function.
Surface stress.
Symbolic dynamics.
The Signal and the Noise.
Topological conjugacy.
Transfer function.
Variance.
Vorticity.
Title is part of eBook package: De Gruyter Princeton Series in Applied Mathematics eBook-Package 9783110515831 ZDB-23-PAM
Title is part of eBook package: De Gruyter Princeton University Press eBook-Package Backlist 2000-2013 9783110442502
print 9780691144344
https://doi.org/10.1515/9781400832507
https://www.degruyter.com/isbn/9781400832507
Cover https://www.degruyter.com/document/cover/isbn/9781400832507/original
language English
format eBook
author Simiu, Emil,
Simiu, Emil,
spellingShingle Simiu, Emil,
Simiu, Emil,
Chaotic Transitions in Deterministic and Stochastic Dynamical Systems : Applications of Melnikov Processes in Engineering, Physics, and Neuroscience /
Princeton Series in Applied Mathematics ;
Frontmatter --
Contents --
Preface --
Chapter 1. Introduction --
PART 1. FUNDAMENTALS --
Chapter 2. Transitions in Deterministic Systems and the Melnikov Function --
Chapter 3. Chaos in Deterministic Systems and the Melnikov Function --
Chapter 4. Stochastic Processes --
Chapter 5. Chaotic Transitions in Stochastic Dynamical Systems and the Melnikov Process --
PART 2. APPLICATIONS --
Chapter 6. Vessel Capsizing --
Chapter 7. Open-Loop Control of Escapes in Stochastically Excited Systems --
Chapter 8. Stochastic Resonance --
Chapter 9. Cutoff Frequency of Experimentally Generated Noise for a First-Order Dynamical System --
Chapter 10. Snap-Through of Transversely Excited Buckled Column --
Chapter 11. Wind-Induced Along-Shore Currents over a Corrugated Ocean Floor --
Chapter 12. The Auditory Nerve Fiber as a Chaotic Dynamical System --
Appendix A1 Derivation of Expression for the Melnikov Function --
Appendix A2 Construction of Phase Space Slice through Stable and Unstable Manifolds --
Appendix A3 Topological Conjugacy --
Appendix A4 Properties of Space ∑2 --
Appendix A5 Elements of Probability Theory --
Appendix A6 Mean Upcrossing Rate τu-1 for Gaussian Processes --
Appendix A7 Mean Escape Rate τ∊-1 for Systems Excited by White Noise --
References --
Index
author_facet Simiu, Emil,
Simiu, Emil,
author_variant e s es
e s es
author_role VerfasserIn
VerfasserIn
author_sort Simiu, Emil,
title Chaotic Transitions in Deterministic and Stochastic Dynamical Systems : Applications of Melnikov Processes in Engineering, Physics, and Neuroscience /
title_sub Applications of Melnikov Processes in Engineering, Physics, and Neuroscience /
title_full Chaotic Transitions in Deterministic and Stochastic Dynamical Systems : Applications of Melnikov Processes in Engineering, Physics, and Neuroscience / Emil Simiu.
title_fullStr Chaotic Transitions in Deterministic and Stochastic Dynamical Systems : Applications of Melnikov Processes in Engineering, Physics, and Neuroscience / Emil Simiu.
title_full_unstemmed Chaotic Transitions in Deterministic and Stochastic Dynamical Systems : Applications of Melnikov Processes in Engineering, Physics, and Neuroscience / Emil Simiu.
title_auth Chaotic Transitions in Deterministic and Stochastic Dynamical Systems : Applications of Melnikov Processes in Engineering, Physics, and Neuroscience /
title_alt Frontmatter --
Contents --
Preface --
Chapter 1. Introduction --
PART 1. FUNDAMENTALS --
Chapter 2. Transitions in Deterministic Systems and the Melnikov Function --
Chapter 3. Chaos in Deterministic Systems and the Melnikov Function --
Chapter 4. Stochastic Processes --
Chapter 5. Chaotic Transitions in Stochastic Dynamical Systems and the Melnikov Process --
PART 2. APPLICATIONS --
Chapter 6. Vessel Capsizing --
Chapter 7. Open-Loop Control of Escapes in Stochastically Excited Systems --
Chapter 8. Stochastic Resonance --
Chapter 9. Cutoff Frequency of Experimentally Generated Noise for a First-Order Dynamical System --
Chapter 10. Snap-Through of Transversely Excited Buckled Column --
Chapter 11. Wind-Induced Along-Shore Currents over a Corrugated Ocean Floor --
Chapter 12. The Auditory Nerve Fiber as a Chaotic Dynamical System --
Appendix A1 Derivation of Expression for the Melnikov Function --
Appendix A2 Construction of Phase Space Slice through Stable and Unstable Manifolds --
Appendix A3 Topological Conjugacy --
Appendix A4 Properties of Space ∑2 --
Appendix A5 Elements of Probability Theory --
Appendix A6 Mean Upcrossing Rate τu-1 for Gaussian Processes --
Appendix A7 Mean Escape Rate τ∊-1 for Systems Excited by White Noise --
References --
Index
title_new Chaotic Transitions in Deterministic and Stochastic Dynamical Systems :
title_sort chaotic transitions in deterministic and stochastic dynamical systems : applications of melnikov processes in engineering, physics, and neuroscience /
series Princeton Series in Applied Mathematics ;
series2 Princeton Series in Applied Mathematics ;
publisher Princeton University Press,
publishDate 2014
physical 1 online resource (240 p.) : 94 line illus.
Issued also in print.
contents Frontmatter --
Contents --
Preface --
Chapter 1. Introduction --
PART 1. FUNDAMENTALS --
Chapter 2. Transitions in Deterministic Systems and the Melnikov Function --
Chapter 3. Chaos in Deterministic Systems and the Melnikov Function --
Chapter 4. Stochastic Processes --
Chapter 5. Chaotic Transitions in Stochastic Dynamical Systems and the Melnikov Process --
PART 2. APPLICATIONS --
Chapter 6. Vessel Capsizing --
Chapter 7. Open-Loop Control of Escapes in Stochastically Excited Systems --
Chapter 8. Stochastic Resonance --
Chapter 9. Cutoff Frequency of Experimentally Generated Noise for a First-Order Dynamical System --
Chapter 10. Snap-Through of Transversely Excited Buckled Column --
Chapter 11. Wind-Induced Along-Shore Currents over a Corrugated Ocean Floor --
Chapter 12. The Auditory Nerve Fiber as a Chaotic Dynamical System --
Appendix A1 Derivation of Expression for the Melnikov Function --
Appendix A2 Construction of Phase Space Slice through Stable and Unstable Manifolds --
Appendix A3 Topological Conjugacy --
Appendix A4 Properties of Space ∑2 --
Appendix A5 Elements of Probability Theory --
Appendix A6 Mean Upcrossing Rate τu-1 for Gaussian Processes --
Appendix A7 Mean Escape Rate τ∊-1 for Systems Excited by White Noise --
References --
Index
isbn 9781400832507
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callnumber-first Q - Science
callnumber-subject QA - Mathematics
callnumber-label QA614
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https://www.degruyter.com/isbn/9781400832507
https://www.degruyter.com/document/cover/isbn/9781400832507/original
illustrated Illustrated
dewey-hundreds 500 - Science
dewey-tens 510 - Mathematics
dewey-ones 515 - Analysis
dewey-full 515.352
dewey-sort 3515.352
dewey-raw 515.352
dewey-search 515.352
doi_str_mv 10.1515/9781400832507
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hierarchy_parent_title Title is part of eBook package: De Gruyter Princeton Series in Applied Mathematics eBook-Package
Title is part of eBook package: De Gruyter Princeton University Press eBook-Package Backlist 2000-2013
is_hierarchy_title Chaotic Transitions in Deterministic and Stochastic Dynamical Systems : Applications of Melnikov Processes in Engineering, Physics, and Neuroscience /
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code="a">Instability.</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">Integrable system.</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">Invariant manifold.</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">Iteration.</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">Joint probability distribution.</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">LTI system theory.</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">Limit cycle.</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">Linear differential equation.</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">Logistic map.</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">Marginal distribution.</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">Moduli (physics).</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">Multiplicative noise.</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">Noise (electronics).</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">Nonlinear control.</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">Nonlinear system.</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">Ornstein-Uhlenbeck process.</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">Oscillation.</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">Parameter space.</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">Parameter.</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">Partial differential equation.</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">Perturbation function.</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">Phase plane.</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">Phase space.</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">Poisson distribution.</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">Probability density function.</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">Probability distribution.</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">Probability theory.</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">Probability.</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">Production-possibility frontier.</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">Relative velocity.</subfield></datafield><datafield tag="653" ind1=" " ind2=" 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