Results 61 to 70 of about 897 (167)
Artificial neural networks (ANNs) are widely used machine learning techniques with applications in various fields. Heuristic search optimization methods are typically used to minimize the loss function in ANNs. However, these methods can lead the network to become stuck in local optima, limiting performance.
Taninnuch Lamjiak +5 more
wiley +1 more source
The Intrinsic Geometry on Bounded Pseudoconvex Domains [PDF]
The Diederich--Fornæss index has been introduced since 1977 to classify bounded pseudoconvex domains. In this article, we derive several intrinsic, geometric conditions on boundary of domains for arbitrary indexes. Many results, in the past, by various mathematicians estimated the index by assuming some properties of domains.
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In this paper, we are thus motivated to define and introduce the extended fuzzy‐valued convex functions that can take the singleton fuzzy values −∞˜ and +∞˜ at some points. Such functions can be characterized using the notions of effective domain and epigraph.
T. Allahviranloo +7 more
wiley +1 more source
Embedding Strictly Pseudoconvex Domains Into Balls [PDF]
Every relatively compact strictly pseudoconvex domain D D with
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Some aspects of the Kobayashi and Caratheodory metrics on pseudoconvex domains
The purpose of this article is to consider two themes, both of which emanate from and involve the Kobayashi and the Caratheodory metric. First, we study the biholomorphic invariant introduced by B.
Mahajan, Prachi, Verma, Kaushal
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On some new sharp embedding theorems in minimal and pseudoconvex domains [PDF]
summary:We present new sharp embedding theorems for mixed-norm analytic spaces in pseudoconvex domains with smooth boundary. New related sharp results in minimal bounded homogeneous domains in higher dimension are also provided.
Mihić, Olivera R. +2 more
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Variations of pseudoconvex domains
A connected Hausdorff space E together with a locally homeomorphic map \(\pi\) of E to \({\mathbb{R}}^ m\) is called an unramified covering domain over the space \({\mathbb{R}}^ m\). Suppose D is such a domain and \(D_ p\) is a sequence of relatively compact subdomains of D such that \(x^ 0\in D_ 1\), \(D_ p\subset D_{p+1}\), \(\cup^{\infty}_{p=1}D_ p ...
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On functional analytic approach for corona and Gleason’s problems for holomorphic Lipschitz algebras
We study Lipschitz algebras of holomorphic functions of the order k, 0 ≤ k ≤ ∞, and the exponent α, α ∈ (0, 1]. The Gel’fand theory and maximal ideal spaces of these algebras are discussed.
S.R. Patel
doaj +1 more source
On Pseudoconvex Domains in $\mathbf{P}^n$
Let \(\Omega\) be a domain in \(\mathbb{C}\mathbb{P}^n\) and let \(K_\Omega\) be its Bergman kernel with respect to the Fubiny-Study metric. The authors prove first a localization principle for \(K_\Omega\). This can be stated as follows: assume that \(\Omega\) is pseudoconvex and that its complement has non-void interior. Then, given a point \(x\) in \
DIEDERICH, Klas, OHSAWA, Takeo
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Solutions to $ar{partial}$-equations on strongly pseudo-convex domains with $L^p$-estimates
We construct a solution to the $ar{partial}$-equation on a strongly pseudo-convex domain of a complex manifold. This is done for forms of type $(0,s)$, $sgeq 1 $, with values in a holomorphic vector bundle which is Nakano positive and for complex valued ...
Osama Abdelkader, Shaban Khidr
doaj

