Results 11  20
of
1,222,787
Linear Transformations for Randomness Extraction
"... Although informationefficient approaches for extracting randomness from natural sources have been intensively studied, certain difficulties exist in implementing them in real applications like highspeed random number generators (RNGs) due to their high complexities. In this paper, we focus on simp ..."
Abstract
 Add to MetaCart
on simple linear constructions, namely linear transformations, for randomness extraction. The main questions are, what sources can linear transformations be applied and how to construct the transformation matrices such that the extractions are informationefficient. We show that sparse random matrices
LINEARLY TRANSFORMABLE MINIMAL SURFACES
"... ABSTRACT. We give a complete description of a nonplanar minimal surface in R3 with the surprising property that the surface remains minimal after mapping by a linear transformation that dilates by three distinct factors in three orthogonal directions. The surface is defined in closed form using Jaco ..."
Abstract
 Add to MetaCart
ABSTRACT. We give a complete description of a nonplanar minimal surface in R3 with the surprising property that the surface remains minimal after mapping by a linear transformation that dilates by three distinct factors in three orthogonal directions. The surface is defined in closed form using
Multiple Linear Transforms
, 2001
"... In the past several years, Linear Discriminant Analysis (LDA) is being replaced by Heteroscedastic Discriminant Analysis (HDA), to improve the performance of a recognition system that uses a mixture of diagonal covariance prototypes to model the data. A specific version HDA, popularly known as Maxi ..."
Abstract

Cited by 7 (3 self)
 Add to MetaCart
as Maximum Likelihood Linear Transform (MLLT) is also used, on the features finally obtained. However the performance of such systems is not as good as could be obtained for a corresponding system that uses full covariance matrices. We propose the method of Multiple Linear Transforms (MLT), that bridges
BDD Minimization by Linear Transformations
 IN ADVANCED COMPUTER SYSTEMS
, 1998
"... Binary Decision Diagrams (BDDs) are a powerful tool and are frequently used in many applications in VLSI CAD, like synthesis and verification. Unfortunately, BDDs are very sensitive to the variable ordering and their size often becomes infeasible. Recently, a new approach for BDD minimization bas ..."
Abstract

Cited by 12 (2 self)
 Add to MetaCart
based on linear transformations, i.e. a special type of spectral techniques, has been proposed. In this paper we study this minimization method in more detail. While so far only experimental results are known, we prove for a family of Boolean functions that by linear transformations an exponential
A NEW POLYNOMIALTIME ALGORITHM FOR LINEAR PROGRAMMING
 COMBINATORICA
, 1984
"... We present a new polynomialtime algorithm for linear programming. In the worst case, the algorithm requires O(tf'SL) arithmetic operations on O(L) bit numbers, where n is the number of variables and L is the number of bits in the input. The running,time of this algorithm is better than the ell ..."
Abstract

Cited by 841 (3 self)
 Add to MetaCart
We present a new polynomialtime algorithm for linear programming. In the worst case, the algorithm requires O(tf'SL) arithmetic operations on O(L) bit numbers, where n is the number of variables and L is the number of bits in the input. The running,time of this algorithm is better than
On ZeroPreserving Linear Transformations
"... Abstract. For an arbitrary subset I of IR and for a function f defined on I, the number of zeros of f on I will be denoted by ZI(f). In this paper we attempt to characterize all linear transformations T taking a linear subspace W of C(I) into functions defined on J (I, J ⊆ IR) such that for all f ∈ ..."
Abstract

Cited by 2 (0 self)
 Add to MetaCart
Abstract. For an arbitrary subset I of IR and for a function f defined on I, the number of zeros of f on I will be denoted by ZI(f). In this paper we attempt to characterize all linear transformations T taking a linear subspace W of C(I) into functions defined on J (I, J ⊆ IR) such that for all f
Eigenvalues of a linear transformation
 Formalized Mathematics
, 2008
"... Summary. The article presents well known facts about eigenvalues of linear transformation of a vector space (see [14]). I formalize main dependencies between eigenvalues and the diagram of the matrix of a linear transformation over a finitedimensional vector space. Finally, I formalize the subspa ..."
Abstract

Cited by 1 (1 self)
 Add to MetaCart
Summary. The article presents well known facts about eigenvalues of linear transformation of a vector space (see [14]). I formalize main dependencies between eigenvalues and the diagram of the matrix of a linear transformation over a finitedimensional vector space. Finally, I formalize
Digraphs of Finite Linear Transformations
"... If T is a function from a finite set V to itself, we form the digraph D of T as follows. It has V for its vertex set, and there is an arc from x to T (x) for each x E V. Here we answer the following question. Given a finite field F, which digraphs arise as digraphs of a linear transformation from so ..."
Abstract
 Add to MetaCart
If T is a function from a finite set V to itself, we form the digraph D of T as follows. It has V for its vertex set, and there is an arc from x to T (x) for each x E V. Here we answer the following question. Given a finite field F, which digraphs arise as digraphs of a linear transformation from
Hessenberg Pairs of Linear Transformations
, 2008
"... Let K denote a field and V denote a nonzero finitedimensional vector space over K. We consider an ordered pair of linear transformations A: V → V and A ∗ : V → V that satisfy (i)–(iii) below. (i) Each of A,A ∗ is diagonalizable on V. (ii) There exists an ordering {Vi} d i=0 where V−1 = 0, Vd+1 = 0. ..."
Abstract

Cited by 2 (1 self)
 Add to MetaCart
Let K denote a field and V denote a nonzero finitedimensional vector space over K. We consider an ordered pair of linear transformations A: V → V and A ∗ : V → V that satisfy (i)–(iii) below. (i) Each of A,A ∗ is diagonalizable on V. (ii) There exists an ordering {Vi} d i=0 where V−1 = 0, Vd+1 = 0
Linear Transformations of Euclidean Topological Spaces
"... Summary. We introduce linear transformations of Euclidean topological spaces given by a transformation matrix. Next, we prove selected properties and basic arithmetic operations on these linear transformations. Finally, we show that a linear transformation given by an invertible matrix is a homeomor ..."
Abstract

Cited by 3 (3 self)
 Add to MetaCart
Summary. We introduce linear transformations of Euclidean topological spaces given by a transformation matrix. Next, we prove selected properties and basic arithmetic operations on these linear transformations. Finally, we show that a linear transformation given by an invertible matrix is a
Results 11  20
of
1,222,787