نتایج جستجو برای: (m1,m2)-Convex function

تعداد نتایج: 1250472  

پایان نامه :وزارت علوم، تحقیقات و فناوری - دانشگاه بوعلی سینا - دانشکده علوم پایه 1391

abstract: in this thesis, we focus to class of convex optimization problem whose objective function is given as a linear function and a convex function of a linear transformation of the decision variables and whose feasible region is a polytope. we show that there exists an optimal solution to this class of problems on a face of the constraint polytope of feasible region. based on this, we dev...

2006
M. J. Fischer

Suppose we are given a particular fixed-length hash function h : 256-bits→ 128-bits. How can we use h to compute a 128-bit strong collision-free hash of a 512-bit input block? We consider several possible ways to extend h to a hash function H : 512-bits→ 128-bits. In the following, we suppose that m is 512-bits long, and we write m = m1m2, where m1 and m2 are 256 bits each. Method 1 Define H(m)...

Journal: :iranian journal of science and technology (sciences) 2009
a. ebadian

the aim of this paper is to prove some inequalities for p-valent meromorphic functions in thepunctured unit disk δ* and find important corollaries.

Journal: :iranian journal of optimization 2010
malik zawwar hussain fareeha saadia maria hussain

the rational cubic function with three parameters has been extended to rational bi-cubic function to visualize the shape of regular convex surface data. the rational bi-cubic function involves six parameters in each rectangular patch. data dependent constraints are derived on four of these parameters to visualize the shape of convex surface data while other two are free to refine the shape of s...

Journal: :international journal of nonlinear analysis and applications 2015
madjid eshaghi hamidreza reisi dezaki alireza moazzen

‎let $x$ be a real normed  space, then  $c(subseteq x)$  is  functionally  convex  (briefly, $f$-convex), if  $t(c)subseteq bbb r $ is  convex for all bounded linear transformations $tin b(x,r)$; and $k(subseteq x)$  is  functionally   closed (briefly, $f$-closed), if  $t(k)subseteq bbb r $ is  closed  for all bounded linear transformations $tin b(x,r)$. we improve the    krein-milman theorem  ...

Journal: :The Journal of biological chemistry 2006
Guangping Chen Otto Fröhlich Yuan Yang Janet D Klein Jeff M Sands

The vasopressin-regulated urea transporter (UT)-A1 is a transmembrane protein with two glycosylated forms of 97 and 117 kDa; both are derived from a single 88-kDa core protein. However, the precise molecular sites and the function for UT-A1 N-glycosylation are not known. In this study, we compared Madin-Darby canine kidney cells stably expressing wild-type (WT) UT-A1 to Madin-Darby canine kidne...

‎Let $X$ be a real normed  space, then  $C(subseteq X)$  is  functionally  convex  (briefly, $F$-convex), if  $T(C)subseteq Bbb R $ is  convex for all bounded linear transformations $Tin B(X,R)$; and $K(subseteq X)$  is  functionally   closed (briefly, $F$-closed), if  $T(K)subseteq Bbb R $ is  closed  for all bounded linear transformations $Tin B(X,R)$. We improve the    Krein-Milman theorem  ...

Fareeha Saadia Malik Zawwar Hussain, Maria Hussain

The rational cubic function with three parameters has been extended to rational bi-cubic function to visualize the shape of regular convex surface data. The rational bi-cubic function involves six parameters in each rectangular patch. Data dependent constraints are derived on four of these parameters to visualize the shape of convex surface data while other two are free to refine the shape of s...

Journal: :bulletin of the iranian mathematical society 2013
j.-l. liu

making use of an extended fractional differintegral operator ( introduced recently by patel and mishra), we introduce a new subclass of multivalent analytic functions and investigate certain interesting properties of this subclass.

2013
Frank Kelly

1. Suppose that the matrix Mk is of dimension nk × nk+1, k ∈ {1, . . . , h}. We wish to compute the product M1M2 · · ·Mh. Notice that the order of multiplication makes a difference. For example, if (n1, n2, n3, n4) = (1, 10, 1, 10), the calculation (M1M2)M3 requires 20 scalar multiplications, but the calculation M1(M2M3) requires 200 scalar multiplications. Indeed, multiplying a m × n matrix by...

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