نتایج جستجو برای: distortion bounds

تعداد نتایج: 113343  

2015
Gangadharan Murugusundaramoorthy G. Murugusundaramoorthy

Abstract. We introduce a new subclass corresponding to the class of k−uniformly convex and starlike functions associated with HurwitzLerch zeta functions and determine many properties like the coefficient estimates, extreme points, closure theorem, distortion bounds, radii of starlikeness and convexity. Furthermore, we obtain an integral transform results, neighborhood results, integral means i...

2007
Maslina Darus

In this paper, we introduce a new class of analytic functions which are analytic related to Hadamard products. Characterization properties which include coefficient bounds, growth and distortion, and closure theorem are given. Further, results on integral transforms are also discussed. 2000 Mathematical Subject Classification: 30C45

2011
M. K. AOUF G. MURUGUSUNDARAMOORTHY K. THILAGAVATHI

Making use of convolution product, we introduce a unified class of spiral-like functions and obtain the coefficient bounds, extreme points and radius of starlikeness for functions belonging to the generalized class Pλ μ (α, β, γ). Furthermore, Distortion theorems for the fractional derivative and fractional integration are obtained. Also we get result about coefficient inequality.

2004
G. MURUGUSUNDARAMOORTHY N. MAGESH

Making use of Linear operator theory, we define a new subclass of uniformly convex functions and a corresponding subclass of starlike functions with negative coefficients. The main object of this paper is to obtain coefficient estimates distortion bounds, closure theorems and extreme points for functions belonging to this new class. The results are generalized to families with fixed finitely ma...

2010
POONAM SHARMA

In this paper, a class of analytic functions with fixed argument of its coefficients involving Wright’s generalized hypergeometric function is defined with the help of subordination. The coefficient inequalities have been derived. Growth, distortion bounds and extreme points for functions belonging to the defined class have been investigated with consequent results.

2008
H. E. Darwish

Abstract. Using of Salagean operator, we define a new subclass of uniformly convex functions with negative coefficients and with fixed second coefficient. The main objective of this paper is to obtain coefficient estimates, distortion bounds, closure theorems and extreme points for functions belonging of this new class. The results are generalized to families with fixed finitely many coefficients.

2009
G. MURUGUSUNDARAMOORTHY

The Wright’s generalized hypergeometric function is used here to introduce a new class of p-valent functions WT p(λ, α, β) defined in the open unit disc and investigate its various characteristics. Further we obtain distortion bounds, extreme points and radii of close-to-convexity, starlikeness and convexity of functions belonging to the class WT p(λ, α, β).

1995
Michael J. Ruf James W. Modestino

This paper describes a methodology for evaluating the rate-distortion behavior of combined source and channel coding schemes with particular application to images. In particular, we demonstrate use of the operational rate-distortion function to obtain the optimum tradeoff between source coding accuracy and channel error protection under the constraint of a fixed transmission band-width. Further...

Journal: :Logica Universalis 2013
Thomas Studer

The problem of data privacy is to verify that confidential information stored in an information system is not provided to unauthorized users and, therefore, personal and other sensitive data remain private. One way to guarantee this is to distort a knowledge base such that it does not reveal sensitive information. In the present paper we will give a universal definition of the problem of knowle...

Journal: :CoRR 2009
Yasutada Oohama

We consider a distributed source coding problem of L correlated Gaussian observations Yi, i = 1, 2, · · · , L. We assume that the random vector Y L = t(Y1, Y2, · · · , YL) is an observation of the Gaussian random vector X = t(X1, X2, · · · , XK), having the form Y L = AX +N , where A is a L×K matrix and N = t(N1, N2, · · · , NL) is a vector of L independent Gaussian random variables also indepe...

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