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3 edition of Convolutional representations of commutants and multipliers found in the catalog.

Convolutional representations of commutants and multipliers

Nikolai Bozhinov

Convolutional representations of commutants and multipliers

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  • 1 Currently reading

Published by Pub. House of the Bulgarian Academy of Sciences in Sofia .
Written in English

  • Linear operators.,
  • Convolutions (Mathematics),
  • Operator product expansions.

  • Edition Notes

    StatementNikolai Bozhinov.
    LC ClassificationsQA329.2 .B69 1988
    The Physical Object
    Pagination307 p. ;
    Number of Pages307
    ID Numbers
    Open LibraryOL2253798M
    LC Control Number89131360

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Convolutional representations of commutants and multipliers by Nikolai Bozhinov Download PDF EPUB FB2

Convolutional representations of commutants and multipliers. Sofia: Pub. House of the Bulgarian Academy of Sciences, (OCoLC) Document Type: Book: All Authors / Contributors: Nikolai Bozhinov. Convolutional representation of the multipliers of the formal Leontiev expansion.- Leontiev’s expansions in the case of multiple zeros of the indicatrix.- A Convolution for the General Right Inverse of the Backward Shift Operator in Spaces of Locally Holomorphic Functions.- and the Duhamel convolution.

This connection is expressed saying that l is the convolutional operator {1}*, i. lf={1}* relation allows to obtain explicit representations of the commutants of Volterra’s integration operator in various function : Ivan H.

Dimovski. In this article, we are interested in giving an explicit convolutional representation of multipliers of the convolution of the right inverse operators of differentiation, found by the first author.

Nonclassical convolutions and their uses. Convolutional representations of commutants and multipliers. Integral Representations of Multipliers.- Isometric Multipliers.- This paper presents a new video representation, called trajectory-pooled deep-convolutional descriptor (TDD), which shares the merits of both hand-crafted features and.


BOZHINOV Institute of Mathematics with Computer Centre, Bulgarian Academy of Sciences, P.O. BoxSofia, Bulgaria 1. : N.S. Bozhinov. Commutants of the Euler operator and corresponding mean-periodic functions Article in Integral Transforms and Special Functions 18(2) February with 11.

as the base of his \convolutional approach". By means of this approach, he has built new operational calculi for local and nonlocal boundary value problems, extending the area of applicability of the multipliers theory and relating it to the theory of commuting linear operators.

Based on this convolutional approach, a new variant ofFile Size: KB. A direct algebraic construction of a family of operational calculi for the Euler differential operator δ = t d dt is proposed. It extends the Mikusiski's approach to the Heaviside operational.

A survey of three types of convolutions, depending on arbitrary linear functionals is made. They are convolutions for right inverse operators of the differentiation operator, the Euler operator and the square of the differentiation operator. Three lines of applications of these convolutions are outlined: characterizing their multipliers, the commutants and direct Cited by: 2.

In this paper, we are interested in giving a convolutional representation of multipliers of the Dimovski convolution in the space C(Δ) of continuous functions on Δ. The main result (Theorem 12) is a characterization of the topological automorphisms on C (Δ) among multipliers of the Dimovski : Swietłana Minczewa-Kamińska.

commuting with the Euler operator δ in C1(R+). Now a connection between the mean-periodic functions for δ with respect to Φ and the convolutional algebra (C(R+),∗) will be given: Theorem 8.

The mean-periodic functions for the Euler operator δ with respect to any non-zero functional Φ: C(R+) → C form an ideal in the convolutional algebra. Hierarchical Modular Optimization of Convolutional Networks Achieves Representations Similar to Macaque IT and Human Ventral Stream Daniel Yamins McGovern Institute of Brain Research Massachusetts Institute of Technology Cambridge, MA [email protected] Ha Hong McGovern Institute of Brain Research Massachusetts Institute of Technology.


The following type of Carleman estimate is known to be true on a certain range of p,q: kevxuk Lq(Rd) ≤ Cke vxP(D)uk Lp(Rd) with C independent of v ∈ Rd. The. BOOK OF ABSTRACTS Department of Mathematics, University of Coimbra, Portugal September 7–11, problem via representation technique Marisa Toste Column The generalized quadraticity of linear combination of two commuting quadratic matrices Simo Puntanen On the relative linear.

For another applications of the classical Duhamel products and discrete Duhamel products can be found, for instance, in [1–3, 5, 9–15, 17, 18]. References [1] Bozhinov N.

Convolutional Representations of Commutants and Multipliers. Sofia Publ House Bulg Acad Sci, [2] Dimovski I. Convolutional : M.

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Convolutional representations of the commutants of linear integration operators.- The commutant of the differentiation operator in an invariant hyperplane.- An Application of the Convolutional Approach to Dirichlet Expansions of Locally Holomorphic Functions.- Eq.1) The notation (f ∗ N g) for cyclic convolution denotes convolution over the cyclic group of integers modulo N.

Circular convolution arises most often in the context of fast convolution with a fast Fourier transform (FFT) algorithm. Fast convolution algorithms In many situations, discrete convolutions can be converted to circular convolutions so that fast transforms with a.

Abstract. As a successful deep model applied in image super-resolution (SR), the Super-Resolution Convolutional Neural Network (SRCNN) [1, 2] has demonstrated superior performance to the previous hand-crafted models either in speed and restoration r, the high computational cost still hinders it from practical usage that demands real-time Cited by: mathematical books from foreign languages (English, German, Russian and French) for the audience of Bulgarian mathematicians.

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It has long been recognized that the invariance and equivariance properties of a representation are critically important for success in many vision tasks.

developed a convolutional coprocessor [10] and an accelerator design is reported in [11]. However, systolic implementations are very inflexible. Therefore, these proposals had to resort to complex arbitration and routing logic to share inputs and connect outputs of the convolvers to other resources.

Further-Cited by: Integral Transforms and Special Functions Vol. 18, No. 2, February– Commutants of the Euler operator and corresponding mean-periodic functions IVAN H. DIMOVSKI and VALENTIN Z. HRISTOV* Bulgarian Academy of Sciences, Institute of Mathematics and Informatics, Section Complex Analysis, Acad.

Bonchev Str., Block 8, Sofia. A Toeplitz matrix may be defined as a matrix A where Ai,j = ci−j, for constants c1−n cn−1. The set of n × n Toeplitz matrices is a subspace of the vector space of n × n matrices under matrix addition and scalar multiplication.

Two Toeplitz matrices may be added in O (n) time and multiplied in O (n2) time. You can write a book review and share your experiences.

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The Multiplier Quotients Ring of an Annihilators-free Convolutional Algebra -- 2. Convolutions of General Integration Operators. Applications -- Convolutions of the Linear Right Inverses of the Differentiation Operator -- An Application of the Convolutional Approach to Dirichlet Expansions of Locally Holomorphic Functions -- A Monte Carlo Search-based Triplet Sampling Method for Learning Disentangled Representation of Impulsive Noise on Steering Gear: A MULTICHANNEL KALMAN-BASED WIENER FILTER APPROACH FOR SPEAKER INTERFERENCE REDUCTION IN MEETINGS: A MULTI-DILATION AND MULTI-RESOLUTION FULLY CONVOLUTIONAL NETWORK FOR.

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The Clebsch representation in optimal control, integrable systems and discrete dynamics Novel aspects of approximating Hilbert Schmidt operators via Gabor Multipliers and Spline-type Spaces Darian Onchis, University of Vienna, Austria FoCMbased on a .Predicting the affective valence of unknown multi-word expressions is key for concept-level sentiment analysis.

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