On Reciprocal Sequences of Matricial Carathéodory Sequences and Associated Matrix Functions

2012 ◽  
pp. 57-115 ◽  
Author(s):  
Bernd Fritzsche ◽  
Bernd Kirstein ◽  
Andreas Lasarow ◽  
Armin Rahn
Keyword(s):  
Matrix Functions ◽  
Associated Matrix

Extended Bessel Matrix Functions

2018 ◽  
Vol 6 (1) ◽  
pp. 1-11
Author(s):  
Ayman SHEHATA
Keyword(s):  
Matrix Functions

scholarly journals Approximated least-squares solutions of a generalized Sylvester-transpose matrix equation via gradient-descent iterative algorithm

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
Adisorn Kittisopaporn ◽  
Pattrawut Chansangiam
Keyword(s):  
Least Squares ◽  
Iterative Algorithm ◽  
Gradient Descent ◽  
Main Idea ◽  
Full Column Rank ◽  
Minimum Error ◽  
Matrix Coefficients ◽  
Special Cases ◽  
Efficiency And Effectiveness ◽  
Associated Matrix

AbstractThis paper proposes an effective gradient-descent iterative algorithm for solving a generalized Sylvester-transpose equation with rectangular matrix coefficients. The algorithm is applicable for the equation and its interesting special cases when the associated matrix has full column-rank. The main idea of the algorithm is to have a minimum error at each iteration. The algorithm produces a sequence of approximated solutions converging to either the unique solution, or the unique least-squares solution when the problem has no solution. The convergence analysis points out that the algorithm converges fast for a small condition number of the associated matrix. Numerical examples demonstrate the efficiency and effectiveness of the algorithm compared to renowned and recent iterative methods.

Gamma-generating matrices, j-inner matrix functions, and related extrapolation problems. 3

1992 ◽  
Vol 58 (6) ◽  
pp. 532-537 ◽  
Author(s):  
D. Z. Arov
Keyword(s):  
Matrix Functions

Human cervical tumor cell (SiHa) surface αvβ3 integrin receptor has associated matrix metalloproteinase (MMP-2) activity

2001 ◽  
Vol 127 (11) ◽  
pp. 653-658 ◽  
Author(s):  
Nibedita Chattopadhyay ◽  
Aparna Mitra ◽  
Eva Frei ◽  
Amitava Chatterjee
Keyword(s):  
Matrix Metalloproteinase ◽  
Tumor Cell ◽  
Αvβ3 Integrin ◽  
Cervical Tumor ◽  
Integrin Receptor ◽  
Associated Matrix ◽  
Αvβ3 Integrin Receptor

scholarly journals REDUCTION OF TODA LATTICE HIERARCHY TO GENERALIZED KdV HIERARCHIES AND THE TWO-MATRIX MODEL

1995 ◽  
Vol 10 (17) ◽  
pp. 2537-2577 ◽  
Author(s):  
H. ARATYN ◽  
E. NISSIMOV ◽  
S. PACHEVA ◽  
A.H. ZIMERMAN
Keyword(s):  
Poisson Bracket ◽  
Hamiltonian Structure ◽  
Toda Lattice ◽  
Free Field ◽  
String Model ◽  
Matrix Formulation ◽  
Hamiltonian Action ◽  
Kdv Hierarchy ◽  
Associated Matrix ◽  
Toda Lattice Hierarchy

Toda lattice hierarchy and the associated matrix formulation of the 2M-boson KP hierarchies provide a framework for the Drinfeld-Sokolov reduction scheme realized through Hamiltonian action within the second KP Poisson bracket. By working with free currents, which Abelianize the second KP Hamiltonian structure, we are able to obtain a unified formalism for the reduced SL (M+1, M−k) KdV hierarchies interpolating between the ordinary KP and KdV hierarchies. The corresponding Lax operators are given as superdeterminants of graded SL (M+1, M−k) matrices in the diagonal gauge and we describe their bracket structure and field content. In particular, we provide explicit free field representations of the associated W(M, M−k) Poisson bracket algebras generalizing the familiar nonlinear WM+1 algebra. Discrete Bäcklund transformations for SL (M+1, M−k) KdV are generated naturally from lattice translations in the underlying Toda-like hierarchy. As an application we demonstrate the equivalence of the two-matrix string model to the SL (M+1, 1) KdV hierarchy.

Expressions of angiogenesis associated matrix metalloproteinases and extracellular matrix proteins in cerebral vascular malformations

2010 ◽  
Vol 17 (2) ◽  
pp. 232-236 ◽  
Author(s):  
Atilla Bicer ◽  
Bulent Guclu ◽  
Abdulkadir Ozkan ◽  
Ozlem Kurtkaya ◽  
Demet Yalcinkaya Koc ◽  
...  
Keyword(s):  
Extracellular Matrix ◽  
Matrix Metalloproteinases ◽  
Vascular Malformations ◽  
Extracellular Matrix Proteins ◽  
Matrix Proteins ◽  
Associated Matrix ◽  
Cerebral Vascular Malformations ◽  
Cerebral Vascular

scholarly journals Very badly approximable matrix functions

2005 ◽  
Vol 11 (1) ◽  
pp. 127-154 ◽  
Author(s):  
V. V. Peller ◽  
S. R. Treil
Keyword(s):  
Matrix Functions ◽  
Badly Approximable

A New Random Data Description and Its Use in Transferring Road Roughness to Vehicle Response

1974 ◽  
Vol 96 (2) ◽  
pp. 676-679 ◽  
Author(s):  
J. C. Wambold ◽  
W. H. Park ◽  
R. G. Vashlishan
Keyword(s):  
Spectral Density ◽  
Frequency Distribution ◽  
Descriptive Analysis ◽  
Joint Probability ◽  
Amplitude Distribution ◽  
Matrix Functions ◽  
Initial Portion ◽  
Power Spectral ◽  
Road Roughness ◽  
Cross Spectral Density

The initial portion of the paper discusses the more conventional method of obtaining a vehicle transfer function where phase and magnitude are determined by dividing the cross spectral density of the input/output by the power spectral density (PSD) of the input. The authors needed a more descriptive analysis (over PSD) and developed a new signal description called Amplitude Frequency Distribution (AFD); a discrete joint probability of amplitude and frequency with the advantage of retaining amplitude distribution as well as frequency distribution. A better understanding was obtained, and transfer matrix functions were developed using AFD.

Derivatives of Eigenvalues and Eigenvectors of Matrix Functions

1993 ◽  
Vol 14 (4) ◽  
pp. 903-926 ◽  
Author(s):  
Alan L. Andrew ◽  
K.-W. Eric Chu ◽  
Peter Lancaster
Keyword(s):  
Matrix Functions ◽  
Eigenvalues And Eigenvectors ◽  
Derivatives Of
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