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steepest descent algorithm

A Generalized Hybrid Steepest-Descent Method for Variational Inequalities in Banach Spaces

A Generalized Hybrid Steepest-Descent Method for Variational Inequalities in Banach Spaces

... hybrid steepest-descent method introduced by Yamada 2001 is an algorithmic solution to the variational inequality problem over the fixed point set of nonlinear mapping and applicable to a broad range of ...

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An Improved Gauss Newtons Method based Back propagation Algorithm for Fast Convergence

An Improved Gauss Newtons Method based Back propagation Algorithm for Fast Convergence

... The steepest descent back-propagation (SDBP) is used in several applications despite its asymptotic slow convergence rate ...The algorithm is also known as a gradient ...of steepest ...

7

Adaptive Filtering using Steepest Descent and LMS Algorithm

Adaptive Filtering using Steepest Descent and LMS Algorithm

... an algorithm which is capable of separating this noise from the desired response called as the adaptive filtering ...recursive algorithm continuously to adjust its tap weights for operation in an unknown ...

5

Finite Step Relaxed Hybrid Steepest Descent Methods for Variational Inequalities

Finite Step Relaxed Hybrid Steepest Descent Methods for Variational Inequalities

... hybrid steepest-descent methods for solving VIF, C has been introduced and studied recently by many authors see, ...hybrid steepest-descent for variational ...hybrid ...

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Active noise reduction in double panel structures : decentralized adaptive feedforward control

Active noise reduction in double panel structures : decentralized adaptive feedforward control

... 3.4.1 Effect of plant uncertainties As was shown in equation 32 , a steepest descent algorithm with effort weighting can be used to control the system to a minimum error solution when t[r] ...

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An efficient algorithm for steepest descent method for unconstrained optimization

An efficient algorithm for steepest descent method for unconstrained optimization

... each steepest descent direction converge very ...new steepest descent method, which is for convex quadratic problems only is proposed by ...new steepest descent method uses the ...

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Efficient implementation of a modified and relaxed hybrid steepest descent method for a type of variational inequality

Efficient implementation of a modified and relaxed hybrid steepest descent method for a type of variational inequality

... hybrid steepest-descent method for solving VI(F, K) [7,8], but choosing an efficient and implementable nonexpansive mapping is still a difficult ...hybrid steepest-descent method for ...

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An Application of Hybrid Steepest Descent Methods for Equilibrium Problems and Strict Pseudocontractions in Hilbert Spaces

An Application of Hybrid Steepest Descent Methods for Equilibrium Problems and Strict Pseudocontractions in Hilbert Spaces

... hybrid steepest descent methods for finding a common element of the set of solutions of an equilibrium problem and the set of fixed points of a strict pseudocontraction mapping in the setting of real ...

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Steepest descent for a linear operator equation of the second kind with application to Tikhonov regularisation

Steepest descent for a linear operator equation of the second kind with application to Tikhonov regularisation

... The publisher or other rights-holder may allow further reproduction and re-use of this version - refer to the White Rose Research Online record for this item.. Where records identify the[r] ...

15

The hybrid steepest descent method for solving variational inequality over triple hierarchical problems

The hybrid steepest descent method for solving variational inequality over triple hierarchical problems

... Theorem . Let H be a real Hilbert space, C be a closed convex subset of H. Let A : C → H be a strongly positive linear bounded operator, f : C → H be a ρ-contraction, γ be a positive real number such that γ ¯ ρ – < ...

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Hybrid Steepest Descent Method with Variable Parameters for General Variational Inequalities

Hybrid Steepest Descent Method with Variable Parameters for General Variational Inequalities

... hybrid steepest-descent method for variational inequality problems over the intersection of the fixed point sets of nonexpansive mappings,” in Inherently Parallel Algorithms in Feasibility and Optimization ...

14

Optimal Control of Microgrid Networks Using Gradient Descent and Differential Evolution Methods

Optimal Control of Microgrid Networks Using Gradient Descent and Differential Evolution Methods

... are Steepest Descent method, Newton method and Differential Evolution ...gradient descent methods where as the differential evolution is an Evolutionary ...gradient descent methods and ...

7

Strong convergence of relaxed hybrid steepest-descent methods for triple hierarchical constrained optimization

Strong convergence of relaxed hybrid steepest-descent methods for triple hierarchical constrained optimization

... Up to now, a large number of practical problems such as signal processing and network resource allocation have been formulated as the monotone variational inequality over the fixed point set of a nonexpansive mapping, ...

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A Hybrid Method for Monotone Variational Inequalities Involving Pseudocontractions

A Hybrid Method for Monotone Variational Inequalities Involving Pseudocontractions

... In this section, we introduce an implicit algorithm and prove this algorithm converges strongly to x ∗ which solves the VI 1.2. Let C be a nonempty closed convex subset of a real Hilbert space H. Let f : C ...

8

A New Conjugancy Coefficient of Conjugate Gradient Method

A New Conjugancy Coefficient of Conjugate Gradient Method

... The nonlinear conjugate gradient method is a very useful technique for solving large scale minimization problems and has wide applications in many fields. The Conjugate Gradient method is one of the suitable methods for ...

6

On the convergence speed of artificial neural networks in‎ ‎the solving of linear ‎systems

On the convergence speed of artificial neural networks in‎ ‎the solving of linear ‎systems

... η = 100 1 and α = 100 1 . Similarly, Tables 3 and 4 show the approximated solutions over a number of iterations for the steepest descent and quasi- Newton methods, respectively. Fig. 7 shows the difference ...

9

Designing a short term line planning model

Designing a short term line planning model

... Genetic Algorithm. This Genetic Algorithm selects line routes from the set of candidate line routes to form a line ...Genetic Algorithm iteratively proposes new line ...Genetic Algorithm ...

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An Implicit Hierarchical Fixed-Point Approach to General Variational Inequalities in Hilbert Spaces

An Implicit Hierarchical Fixed-Point Approach to General Variational Inequalities in Hilbert Spaces

... On the other hand, let F : H → H be a κ-Lipschitzian and η-strongly monotone operator with constants κ, η > 0, and let T : H → H be nonexpansive such that FixT / ∅. In 2001, Yamada 6 introduced the so-called hybrid ...

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Hybrid Steepest-Descent Methods for Solving Variational Inequalities Governed by Boundedly Lipschitzian and Strongly Monotone Operators

Hybrid Steepest-Descent Methods for Solving Variational Inequalities Governed by Boundedly Lipschitzian and Strongly Monotone Operators

... hybrid steepest descent method for the variational inequality problem over the intersection of fixed point sets of nonexpansive mappings,” in Inherently Parallel Algorithms in Feasibility and Optimization ...

16

On the probability of positive definiteness in the gGUE via semi classical Laguerre polynomials

On the probability of positive definiteness in the gGUE via semi classical Laguerre polynomials

... In this paper, we compute the probability that an N × N matrix from the generalised Gaussian Unitary Ensemble (gGUE) is positive definite, extending a previous result of Dean and Majumdar [15]. For this purpose, we work ...

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