Unconstrained Optimization and Quantum Calculus
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Beschreibung
This book provides a better clue to apply quantum derivative instead of classical derivative in the modified optimization methods, compared with the competing books which employ a number of standard derivative optimization techniques to address large-scale, unconstrained optimization issues. Essential proofs and applications of the various techniques are given in simple manner without sacrificing accuracy. New concepts are illustrated with the help of examples. This book presents the theory and application of given optimization techniques in generalized and comprehensive manner. Methods such as steepest descent, conjugate gradient and BFGS are generalized and comparative analyses will show the efficiency of the techniques.
This book provides a better clue to apply quantum derivative instead of classical derivative in the modified optimization methods, compared with the competing books which employ a number of standard derivative optimization techniques to address large-scale, unconstrained optimization issues. Essential proofs and applications of the various techniques are given in simple manner without sacrificing accuracy. New concepts are illustrated with the help of examples. This book presents the theory and application of given optimization techniques in generalized and comprehensive manner. Methods such as steepest descent, conjugate gradient and BFGS are generalized and comparative analyses will show the efficiency of the techniques.
Gives an exhaustive review of the literature Presents introduction of quantum calculus in the optimization methods Covers all classical optimization methods which are generalized for improving the results
Autor*in
Bhagwat Ram
Themen in »Unconstrained Optimization and Quantum Calculus«
Numerical Optimization Unconstrained Optimization Quantum Calculus Global Convergence Optimization Algorithm q-derivative Conjugate Gradient Method Gradient Descent method Optimal Solution Optimization Algorithm