The Resource Nonlinear optimization in electrical engineering with applications in MATLAB, Mohamed Bakr, (electronic resource)

Nonlinear optimization in electrical engineering with applications in MATLAB, Mohamed Bakr, (electronic resource)

Label
Nonlinear optimization in electrical engineering with applications in MATLAB
Title
Nonlinear optimization in electrical engineering with applications in MATLAB
Statement of responsibility
Mohamed Bakr
Creator
Contributor
Provider
Subject
Language
eng
Cataloging source
NhCcYBP
http://library.link/vocab/creatorName
Bakr, Mohamed
Dewey number
003/.75
Index
index present
LC call number
QA427
LC item number
.B357 2013
Literary form
non fiction
Nature of contents
dictionaries
http://library.link/vocab/relatedWorkOrContributorName
ebrary
http://library.link/vocab/subjectName
  • Nonlinear theories
  • Mathematical optimization
Label
Nonlinear optimization in electrical engineering with applications in MATLAB, Mohamed Bakr, (electronic resource)
Instantiates
Publication
Note
Includes index
Carrier category
online resource
Carrier category code
  • cr
Carrier MARC source
rdacarrier
Content category
text
Content type code
  • txt
Content type MARC source
rdacontent
Contents
Machine generated contents note: 1.Mathematical background -- 1.1.Introduction -- 1.2.Vectors -- 1.3.Matrices -- 1.4.The solution of linear systems of equations -- 1.5.Derivatives -- 1.5.1.Derivative approximation -- 1.5.2.The gradient -- 1.5.3.The Jacobian -- 1.5.4.Second-order derivatives -- 1.5.5.Derivatives of vectors and matrices -- 1.6.Subspaces -- 1.7.Convergence rates -- 1.8.Functions and sets -- 1.9.Solutions of systems of nonlinear equations -- 1.10.Optimization problem definition -- References -- Problems -- 2.An introduction to linear programming -- 2.1.Introduction -- 2.2.Examples of linear programs -- 2.2.1.A farming example -- 2.2.2.A production example -- 2.2.3.Power generation example -- 2.2.4.Wireless communication example -- 2.2.5.A battery charging example -- 2.3.Standard form of an LP -- 2.4.Optimality conditions -- 2.5.The matrix form -- 2.6.Canonical augmented form -- 2.7.Moving from one basic feasible solution to another -- 2.8.Cost reduction -- 2.9.The classical Simplex method -- 2.10.Starting the Simplex method -- 2.10.1.Endless pivoting -- 2.10.2.The big M approach -- 2.10.3.The two-phase Simplex -- 2.11.Advanced topics -- A2.1.Minimax optimization -- A2.1.1.Minimax problem definition -- A2.1.2.Minimax solution using linear programming -- A2.1.3.A microwave filter example -- A2.1.4.The design of coupled microcavities optical filter -- References -- Problems -- 3.Classical optimization -- 3.1.Introduction -- 3.2.Single-variable Taylor expansion -- 3.3.Multidimensional Taylor expansion -- 3.4.Meaning of the gradient -- 3.5.Optimality conditions -- 3.6.Unconstrained optimization -- 3.7.Optimization with equality constraints -- 3.7.1.Method of direct substitution -- 3.7.2.Method of constrained variation -- 3.8.Lagrange multipliers -- 3.9.Optimization with inequality constraints -- 3.10.Optimization with mixed constraints -- A3.1.Quadratic programming -- A3.2.Sequential quadratic programming -- References -- Problems -- 4.One-dimensional optimization-Line search -- 4.1.Introduction -- 4.2.Bracketing approaches -- 4.2.1.Fixed line search -- 4.2.2.Accelerated line search -- 4.3.Derivative-free line search -- 4.3.1.Dichotomous line search -- 4.3.2.The interval-halving method -- 4.3.3.The Fibonacci search -- 4.3.4.The Golden Section method -- 4.4.Interpolation approaches -- 4.4.1.Quadratic models -- 4.4.2.Cubic interpolation -- 4.5.Derivative-based approaches -- 4.5.1.The classical Newton method -- 4.5.2.A quasi-Newton method -- 4.5.3.The Secant method -- 4.6.Inexact line search -- A4.1.Tuning of electric circuits -- A4.1.1.Tuning of a current source -- A4.1.2.Coupling of nanowires -- A4.1.3.Matching of microwave antennas -- References -- Problems -- 5.Derivative-free unconstrained techniques -- 5.1.Why unconstrained optimization? -- 5.2.Classification of unconstrained optimization techniques -- 5.3.The random jump technique -- 5.4.The random walk method -- 5.5.Grid search method -- 5.6.The univariate method -- 5.7.The pattern search method -- 5.8.The Simplex method -- 5.9.Response surface approximation -- A5.1.Electrical application: impedance transformers -- A5.2.Electrical application: the design of photonic devices -- References -- Problems -- 6.First-order unconstrained optimization techniques -- 6.1.Introduction -- 6.2.The steepest descent method -- 6.3.The conjugate directions method -- 6.3.1.Definition of conjugacy -- 6.3.2.Powell's method of conjugate directions -- 6.4.Conjugate gradient methods -- A6.1.Solution of large systems of linear equations -- A6.2.The design of digital FIR filters -- References -- Problems -- 7.Second-order unconstrained optimization techniques -- 7.1.Introduction -- 7.2.Newton's method -- 7.3.The Levenberg---Marquardt method -- 7.4.Quasi-Newton methods -- 7.4.1.Broyden's rank-1 update -- 7.4.2.The Davidon---Fletcher---Powell (DFP) formula -- 7.4.3.The Broyden---Fletcher---Goldfarb---Shanno method -- 7.4.4.The Gauss---Newton method -- A7.1.Wireless channel characterization -- A7.2.The parameter extraction problem -- A7.3.Artificial neural networks training -- References -- Problems -- 8.Constrained optimization techniques -- 8.1.Introduction -- 8.2.Problem definition -- 8.3.Possible optimization scenarios -- 8.4.A random search method -- 8.5.Finding a feasible starting point -- 8.6.The Complex method -- 8.7.Sequential linear programming -- 8.8.Method of feasible directions -- 8.9.Rosen's projection method -- 8.10.Barrier and penalty methods -- A8.1.Electrical engineering application: analog filter design -- A8.2.Spectroscopy -- References -- Problems -- 9.Introduction to global optimization techniques -- 9.1.Introduction -- 9.2.Statistical optimization -- 9.3.Nature-inspired global techniques -- 9.3.1.Simulated annealing -- 9.3.2.Genetic algorithms -- 9.3.3.Particle swarm optimization -- A9.1.Least pth optimization of filters -- A9.2.Pattern recognition -- References -- Problems -- 10.Adjoint sensitivity analysis -- 10.1.Introduction -- 10.2.Tellegen's theorem -- 10.3.Adjoint network method -- 10.4.Adjoint sensitivity analysis of a linear system of equations -- 10.5.Time-domain adjoint sensitivity analysis -- A 10.1 Sensitivity analysis of high-frequency structures -- References -- Problems
Dimensions
unknown
Extent
1 online resource (xiii, 308 p.) :
Form of item
online
Isbn
9781849195447
Isbn Type
(electronic bk.)
Media category
computer
Media MARC source
rdamedia
Media type code
  • c
Reproduction note
Electronic reproduction.
Specific material designation
remote
Stock number
99959079238
System control number
(NhCcYBP)11334247
Label
Nonlinear optimization in electrical engineering with applications in MATLAB, Mohamed Bakr, (electronic resource)
Publication
Note
Includes index
Carrier category
online resource
Carrier category code
  • cr
Carrier MARC source
rdacarrier
Content category
text
Content type code
  • txt
Content type MARC source
rdacontent
Contents
Machine generated contents note: 1.Mathematical background -- 1.1.Introduction -- 1.2.Vectors -- 1.3.Matrices -- 1.4.The solution of linear systems of equations -- 1.5.Derivatives -- 1.5.1.Derivative approximation -- 1.5.2.The gradient -- 1.5.3.The Jacobian -- 1.5.4.Second-order derivatives -- 1.5.5.Derivatives of vectors and matrices -- 1.6.Subspaces -- 1.7.Convergence rates -- 1.8.Functions and sets -- 1.9.Solutions of systems of nonlinear equations -- 1.10.Optimization problem definition -- References -- Problems -- 2.An introduction to linear programming -- 2.1.Introduction -- 2.2.Examples of linear programs -- 2.2.1.A farming example -- 2.2.2.A production example -- 2.2.3.Power generation example -- 2.2.4.Wireless communication example -- 2.2.5.A battery charging example -- 2.3.Standard form of an LP -- 2.4.Optimality conditions -- 2.5.The matrix form -- 2.6.Canonical augmented form -- 2.7.Moving from one basic feasible solution to another -- 2.8.Cost reduction -- 2.9.The classical Simplex method -- 2.10.Starting the Simplex method -- 2.10.1.Endless pivoting -- 2.10.2.The big M approach -- 2.10.3.The two-phase Simplex -- 2.11.Advanced topics -- A2.1.Minimax optimization -- A2.1.1.Minimax problem definition -- A2.1.2.Minimax solution using linear programming -- A2.1.3.A microwave filter example -- A2.1.4.The design of coupled microcavities optical filter -- References -- Problems -- 3.Classical optimization -- 3.1.Introduction -- 3.2.Single-variable Taylor expansion -- 3.3.Multidimensional Taylor expansion -- 3.4.Meaning of the gradient -- 3.5.Optimality conditions -- 3.6.Unconstrained optimization -- 3.7.Optimization with equality constraints -- 3.7.1.Method of direct substitution -- 3.7.2.Method of constrained variation -- 3.8.Lagrange multipliers -- 3.9.Optimization with inequality constraints -- 3.10.Optimization with mixed constraints -- A3.1.Quadratic programming -- A3.2.Sequential quadratic programming -- References -- Problems -- 4.One-dimensional optimization-Line search -- 4.1.Introduction -- 4.2.Bracketing approaches -- 4.2.1.Fixed line search -- 4.2.2.Accelerated line search -- 4.3.Derivative-free line search -- 4.3.1.Dichotomous line search -- 4.3.2.The interval-halving method -- 4.3.3.The Fibonacci search -- 4.3.4.The Golden Section method -- 4.4.Interpolation approaches -- 4.4.1.Quadratic models -- 4.4.2.Cubic interpolation -- 4.5.Derivative-based approaches -- 4.5.1.The classical Newton method -- 4.5.2.A quasi-Newton method -- 4.5.3.The Secant method -- 4.6.Inexact line search -- A4.1.Tuning of electric circuits -- A4.1.1.Tuning of a current source -- A4.1.2.Coupling of nanowires -- A4.1.3.Matching of microwave antennas -- References -- Problems -- 5.Derivative-free unconstrained techniques -- 5.1.Why unconstrained optimization? -- 5.2.Classification of unconstrained optimization techniques -- 5.3.The random jump technique -- 5.4.The random walk method -- 5.5.Grid search method -- 5.6.The univariate method -- 5.7.The pattern search method -- 5.8.The Simplex method -- 5.9.Response surface approximation -- A5.1.Electrical application: impedance transformers -- A5.2.Electrical application: the design of photonic devices -- References -- Problems -- 6.First-order unconstrained optimization techniques -- 6.1.Introduction -- 6.2.The steepest descent method -- 6.3.The conjugate directions method -- 6.3.1.Definition of conjugacy -- 6.3.2.Powell's method of conjugate directions -- 6.4.Conjugate gradient methods -- A6.1.Solution of large systems of linear equations -- A6.2.The design of digital FIR filters -- References -- Problems -- 7.Second-order unconstrained optimization techniques -- 7.1.Introduction -- 7.2.Newton's method -- 7.3.The Levenberg---Marquardt method -- 7.4.Quasi-Newton methods -- 7.4.1.Broyden's rank-1 update -- 7.4.2.The Davidon---Fletcher---Powell (DFP) formula -- 7.4.3.The Broyden---Fletcher---Goldfarb---Shanno method -- 7.4.4.The Gauss---Newton method -- A7.1.Wireless channel characterization -- A7.2.The parameter extraction problem -- A7.3.Artificial neural networks training -- References -- Problems -- 8.Constrained optimization techniques -- 8.1.Introduction -- 8.2.Problem definition -- 8.3.Possible optimization scenarios -- 8.4.A random search method -- 8.5.Finding a feasible starting point -- 8.6.The Complex method -- 8.7.Sequential linear programming -- 8.8.Method of feasible directions -- 8.9.Rosen's projection method -- 8.10.Barrier and penalty methods -- A8.1.Electrical engineering application: analog filter design -- A8.2.Spectroscopy -- References -- Problems -- 9.Introduction to global optimization techniques -- 9.1.Introduction -- 9.2.Statistical optimization -- 9.3.Nature-inspired global techniques -- 9.3.1.Simulated annealing -- 9.3.2.Genetic algorithms -- 9.3.3.Particle swarm optimization -- A9.1.Least pth optimization of filters -- A9.2.Pattern recognition -- References -- Problems -- 10.Adjoint sensitivity analysis -- 10.1.Introduction -- 10.2.Tellegen's theorem -- 10.3.Adjoint network method -- 10.4.Adjoint sensitivity analysis of a linear system of equations -- 10.5.Time-domain adjoint sensitivity analysis -- A 10.1 Sensitivity analysis of high-frequency structures -- References -- Problems
Dimensions
unknown
Extent
1 online resource (xiii, 308 p.) :
Form of item
online
Isbn
9781849195447
Isbn Type
(electronic bk.)
Media category
computer
Media MARC source
rdamedia
Media type code
  • c
Reproduction note
Electronic reproduction.
Specific material designation
remote
Stock number
99959079238
System control number
(NhCcYBP)11334247

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