In this work we propose a new splitting technique, namely Asymmetric Forward-Backward-Adjoint Splitting (AFBA), for solving monotone inclusions involving three terms, a maximally monotone, a cocoercive and a bounded linear operator. Classical operator splitting methods, like DouglasRachford (DRS) and Forward-Backward splitting (FBS) are special cases of our new algorithm. Among other things, AF...

in this paper we study properties of symbols such that these belong to class of symbols sitting insidesm ρ,φ that we shall introduce as the following. so for because hypoelliptic pseudodifferential operatorsplays a key role in quantum mechanics we will investigate some properties of m−hypoelliptic pseudodifferential operators for which define base on this class of symbols. also we consider maxi...

Although the general characteristics of DNAPL flow and transport in the subsurface are reasonably well understood, it is often difficult and expensive to pinpoint sources of DNAPL contamination. Inversion techniques to improve site characterization rely on a forward model of multiphase flow. Ideally the forward model would be very fast, so that many realizations can be carried out in order to q...

In this paper, an approach to the problem of automatic facial feature extraction from a still frontal posed image and classification and recognition of facial expression and hence emotion and mood of a person is presented. Feed forward back propagation neural network is used as a classifier for classifying the expressions of supplied face into seven basic categories like surprise, neutral, sad,...

We present a general dilation scheme for quantum instruments with continuous outcome space in finite dimensions, in terms of an indirect POVM measurement performed on a finite dimensional ancilla. The general result is then applied to a large class of instruments generated by operator frames, which contains group-covariant instruments as a particular case, and allows one to construct dilation s...

The subject of this investigation is the class of difference functionals—linear combinations of finitely many function and/or derivative evaluations—which annihilate the nullspace of a certain constant coefficient differential operator. Any such functional can be viewed as an integral-differential operator whose Peano kernel is a compactly supported exponential spline. Besides extending some ea...

Both electroencephalography (EEG) and magnetoencephalography (MEG) are currently used to localize brain activity. The accuracy of source localization depends on numerous factors, including the specific inverse approach and source model, fundamental differences in EEG and MEG data, and the accuracy of the volume conductor model of the head (i.e., the forward model). Using Monte Carlo simulations...

We analyze Tikhonov regularization where the forward operator is defined on a direct sum U of several Banach spaces U i ; i ¼ 1;. .. ; m. The regularization term on U is a sum of different regularizations on each U i. The theoretical framework, known for the case m ¼ 1, can be easily reformulated to the case m > 1. Under certain assumptions on weak topologies and on the forward operator it is p...

We study the problem of reconstructing solutions inverse problems when only noisy measurements are available. assume that can be modeled with an infinite-dimensional forward operator is not continuously invertible. Then, we restrict this to finite-dimensional spaces so Lipschitz continuous. For operator, demonstrate there exists a neural network which robust-to-noise approximation operator. In ...

Preconcepts are basic units of knowledge that form the basis formal concepts in concept analysis (FCA). This paper investigates relations among different kinds preconcepts, such as protoconcepts, meet and join-semiconcepts concepts. The first contribution this paper, is to present a fuzzy powerset lattice gradation, coincides with preconcept at its 1-cut. second more significant contribution, i...