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[PDF] Top 20 Regularization of nonlinear Ill-posed equations with accretive operators

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Regularization of nonlinear Ill-posed equations with accretive operators

Regularization of nonlinear Ill-posed equations with accretive operators

... An accretive operator A is said to be maximal accretive if it is accretive and the inclusion G(A) ⊆ G(B), with B accretive, where G(A) and G(B) denote graphs of A and B, respectively, implies ... See full document

23

Convergence rates in regularization for a system of nonlinear ill posed equations with m accretive operators

Convergence rates in regularization for a system of nonlinear ill posed equations with m accretive operators

... the regularization parameter choice without the property for j, for the case of demicontinuous or weakly continuous accretive operators A i satisfying ... See full document

9

A regularization algorithm for zero points of accretive operators

A regularization algorithm for zero points of accretive operators

... In this paper, we study a viscosity algorithm with a computational error. A strong con- vergence theorem for zero points of accretive operators is established in a reflexive Banach space. The organization of ... See full document

9

Regularization of Ill-Posed Point Neuron Models

Regularization of Ill-Posed Point Neuron Models

... strongly nonlinear equations of the kind (1), even when β < ...straightforward regularization technique obtained by replacing the Heaviside firing rate function by a Lipschitz continuous ... See full document

23

Application of cubic B-splines collocation method for solving nonlinear inverse diffusion problem

Application of cubic B-splines collocation method for solving nonlinear inverse diffusion problem

... of ill-posed problems. The matrix A is singular and ill-posed, thus the estimate of C 0 by ...Tikhonov regularization method must be used to control this ...Tikhonov ... See full document

20

An Application of Newton Type Iterative Method for Lavrentiev Regularization for Ill-Posed Equations: Finite Dimensional Realization

An Application of Newton Type Iterative Method for Lavrentiev Regularization for Ill-Posed Equations: Finite Dimensional Realization

... for nonlinear ill-posed operator equation F (x) = f when the operator F : D(F ) ⊆ X → X defined on a real Hilbert space X is monotone, and the available data is f δ with kf − f δ k ≤ ... See full document

7

Regularization of ill posed mixed variational inequalities with non monotone perturbations

Regularization of ill posed mixed variational inequalities with non monotone perturbations

... Variational inequality problems in finite-dimensional and infinite-dimensional spaces appear in many fields of applied mathematics such as convex programming, nonlinear equations, equilibrium models in ... See full document

11

Expanding the applicability of Lavrentiev regularization methods for ill-posed problems

Expanding the applicability of Lavrentiev regularization methods for ill-posed problems

... 18. Argyros, IK: A semilocal convergence for directional Newton methods. Math. Comput. 80, 327-343 (2011) 19. Argyros, IK, Hilout, S: Weaker conditions for the convergence of Newton’s method. J. Complex. 28, 364-387 ... See full document

15

An optimal order yielding discrepancy principle for simplified regularization of ill posed problems in Hilbert scales

An optimal order yielding discrepancy principle for simplified regularization of ill posed problems in Hilbert scales

... simplified regularization in the framework of Hilbert scales was stud- ied for the first time and obtained error estimates under a priori and a poste- riori parameter choice ... See full document

13

Learning from Examples as an Inverse Problem

Learning from Examples as an Inverse Problem

... to regularization techniques for inverse problems, em- phasizing the strong algorithmic and conceptual analogy of certain learning algorithms with regu- larization ...that regularization schemes such as ... See full document

22

Atmospheric inverse modeling via sparse reconstruction

Atmospheric inverse modeling via sparse reconstruction

... Inversions with non-Gaussian priors, like the Laplacian in Eqs. (6) and (7), rarely have an analytical solution simpli- fying the calculation of the posterior distribution. The pos- terior distribution can also be ... See full document

19

Computation of Smooth Optical Flow in a Feedback Connected Analog Network

Computation of Smooth Optical Flow in a Feedback Connected Analog Network

... The circuitry consists of three functional layers (Figure 2). The input layer includes an array of adaptive photoreceptors [10] and provides the derivatives of the image brightness to the second layer. The spatial ... See full document

7

Ill-Posed Problems

Ill-Posed Problems

... to ill-posed problems in the field of mathematical physics and partial differential and integral equations, there are many simpler yet not less important ill-posed problems among ... See full document

9

Strong Convergence of Iterative Schemes for Zeros of Accretive Operators in Reflexive Banach Spaces

Strong Convergence of Iterative Schemes for Zeros of Accretive Operators in Reflexive Banach Spaces

... In 2007, Qin and Su 19 also considered the following iterative scheme in either a uniformly smooth Banach space or a reflexive Banach space having a weakly sequentially continuous duality mapping, which is a simpler ... See full document

19

Controllability for nonlinear evolution equations with monotone operators

Controllability for nonlinear evolution equations with monotone operators

... the set of all continuous functions from [, T] into X with the supremum norm. If X and Y are two Banach spaces, L(X, Y ) is the collection of all bounded linear operators from X into Y , and L(X, X) is simply ... See full document

17

Hybrid methods for accretive variational inequalities involving pseudocontractions in Banach spaces

Hybrid methods for accretive variational inequalities involving pseudocontractions in Banach spaces

... Throughout this paper, we always assume that E is a real Banach space, 〈· , ·〉 is the dual pair between E and E*, and 2 E denotes the family of all the nonempty subsets of E. Let C be a nonempty closed convex subset of E ... See full document

9

Ill-Posed Point Neuron Models

Ill-Posed Point Neuron Models

... be ill posed or “almost ill posed”? If so, then models employing a Heaviside firing rate function cannot be robustly solved with finite precision arithmetic and regularized approximations are ... See full document

21

A Generalized Nonlinear Random Equations with Random Fuzzy Mappings in Uniformly Smooth Banach Spaces

A Generalized Nonlinear Random Equations with Random Fuzzy Mappings in Uniformly Smooth Banach Spaces

... 22 Y. J. Cho, S. H. Shim, N.-J. Huang, and S. M. Kang, “Generalized strongly nonlinear implicit quasi- variational inequalities for fuzzy mappings,” in Set Valued Mappings with Applications in Nonlinear ... See full document

15

A Novel Iterative Algorithm for Solving Nonlinear Inverse Scattering Problems

A Novel Iterative Algorithm for Solving Nonlinear Inverse Scattering Problems

... We now replicate the reconstructions from the previous section but after adding 2% Gaussian noise to the data. The results obtained are shown in Figure 6.10. Once the noise is added, it seems like DCTMC is the preferred ... See full document

176

Local expansions and accretive mappings

Local expansions and accretive mappings

... Mapping Theorems for Local Expansions in Metric and Banach Spaces, J.. Mapping Theorems for Gateaux Differentiable and Accretive Operators, Nonlinear Analysis- TMA 6_ 1982, 423-433..[r] ... See full document

11

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