Fixed-Point Computation of Equilibria in Biochemical Regulatory Networks

2019 ◽  
pp. 45-62
Author(s):  
Isabel Cristina Pérez-Verona ◽  
Mirco Tribastone ◽  
Max Tschaikowski
Keyword(s):  
Fixed Point ◽  
Regulatory Networks ◽  
Fixed Point Computation ◽  
Computation Of Equilibria

Using Digitised X-Ray Powder Diffraction Scans as Input for a New Pc-At Search/Match Program

1987 ◽  
Vol 31 ◽  
pp. 423-430 ◽  
Author(s):  
P. Caussin ◽  
J. Nusinovici ◽  
D.W. Beard
Keyword(s):  
Fixed Point ◽  
Data Base ◽  
Powder Diffraction ◽  
Phase Identification ◽  
Interactive Graphics ◽  
List Type ◽  
Fast Method ◽  
X Ray ◽  
Fixed Point Computation ◽  
Peak Location

AbstractA Search/Matcti program lias 'beea written for the IBM PC AT computer that is capable of -using "background - subtracted, digitized 2-ray powder diffraction scans as inputs in addition to the d/I data traditionally used. This novel procedure has proved especially effective when numerous unresolved lines are present in the pattern. The method is also less demanding of data quality thaii the peak location programs. The program may he extended to searching & data "base of digitized standard patterns.The program, has several parameters that can- "be adjusted, including chemistry. The results from the Johnson/Vand list type of output are directly accessible to the interactive graphics program. This gives the diffraction!st a fast method for verifying the phase identification. Because of the speed of fixed point computation techniques, the 52,791 pattern file can be scanned in about 90 seconds.This paper will illustrate the utility of the program.

scholarly journals Derivation tree analysis for accelerated fixed-point computation

2011 ◽  
Vol 412 (28) ◽  
pp. 3226-3241 ◽  
Author(s):  
Javier Esparza ◽  
Stefan Kiefer ◽  
Michael Luttenberger
Keyword(s):  
Fixed Point ◽  
Derivation Tree ◽  
Tree Analysis ◽  
Fixed Point Computation

scholarly journals Iterative Schemes for Fixed Point Computation of Nonexpansive Mappings

2012 ◽  
Vol 2012 ◽  
pp. 1-12
Author(s):  
Rudong Chen
Keyword(s):  
Fixed Point ◽  
Fixed Points ◽  
Nonexpansive Mappings ◽  
Infinite Family ◽  
Common Fixed Points ◽  
Minimum Norm ◽  
Practical Applications ◽  
Fixed Point Computation ◽  
The Common ◽  
Special Case

Fixed point (especially, the minimum norm fixed point) computation is an interesting topic due to its practical applications in natural science. The purpose of the paper is devoted to finding the common fixed points of an infinite family of nonexpansive mappings. We introduce an iterative algorithm and prove that suggested scheme converges strongly to the common fixed points of an infinite family of nonexpansive mappings under some mild conditions. As a special case, we can find the minimum norm common fixed point of an infinite family of nonexpansive mappings.

Fixed Points-Contractive Functions

2001 ◽  
Author(s):  
Krzysztof A. Sikorski
Keyword(s):  
Banach Space ◽  
Fixed Point ◽  
Fixed Point Theorem ◽  
Fixed Points ◽  
Research Area ◽  
Banach Fixed Point Theorem ◽  
Homotopy Methods ◽  
Simplicial Algorithm ◽  
Intensive Research ◽  
Fixed Point Computation

Fixed point computation has been an intensive research area since 1967 when Scarf introduced simplicial algorithm to approximate fixed points. Several algorithms have been invented since then, including restart and homotopy methods. Most of these were designed to approximate fixed points of general maps and used the residual error criterion. In this chapter we consider the absolute and/or relative error criteria for contractive univariate and multivariate functions. The departure of our analysis is the classical Banach fixed point theorem. Namely, we consider a function f : D →D, where D is a closed subset of a Banach space B. We assume that f is contractive with a factor q < 1, i.e., . . . ||f(x) – f(y)|| ≤ q ||x-y||, for all x,y ∈ D. Then, there exists a unique ∝ = ∝ (f) ∈ D such that ∝ is a fixed point of f, ∝ = f (∝)

Sign in / Sign up

Export Citation Format

Share Document