scholarly journals A new algorithm that generates the image of the attractor of a generalized iterated function system

2019 ◽  
Vol 83 (4) ◽  
pp. 1399-1413 ◽  
Author(s):  
Radu Miculescu ◽  
Alexandru Mihail ◽  
Silviu-Aurelian Urziceanu
Keyword(s):  
Iterated Function System ◽  
Function System ◽  
Iterated Function

ARCLENGTH AS THE INVARIANT MEASURE FOR AN IFS WITH PROBABILITIES

Fractals ◽  
2015 ◽  
Vol 23 (04) ◽  
pp. 1550046
Author(s):  
D. LA TORRE ◽  
F. MENDIVIL
Keyword(s):  
Invariant Measure ◽  
Iterated Function System ◽  
Function System ◽  
Iterated Function

Given a continuous rectifiable function [Formula: see text], we present a simple Iterated Function System (IFS) with probabilities whose invariant measure is the normalized arclength measure on the graph of [Formula: see text].

Stochastic Fractal Modeling and Process Planning for Machining Using Two-Dimensional Iterated Function System

2008 ◽  
Vol 392-394 ◽  
pp. 575-579
Author(s):  
Yu Hao Li ◽  
Jing Chun Feng ◽  
Y. Li ◽  
Yu Han Wang
Keyword(s):  
Path Planning ◽  
Tool Path ◽  
Iterated Function System ◽  
Numerical Control ◽  
Function System ◽  
Tool Path Planning ◽  
Ongoing Research ◽  
Iterated Function ◽  
Planning Algorithm ◽  
Path Planning Algorithm

Self-affine and stochastic affine transforms of R2 Iterated Function System (IFS) are investigated in this paper for manufacturing non-continuous objects in nature that exhibit fractal nature. A method for modeling and fabricating fractal bio-shapes using machining is presented. Tool path planning algorithm for numerical control machining is presented for the geometries generated by our fractal generation function. The tool path planning algorithm is implemented on a CNC machine, through executing limited number of iteration. This paper describes part of our ongoing research that attempts to break through the limitation of current CAD/CAM and CNC systems that are oriented to Euclidean geometry objects.

A graphical representation of protein based on a novel iterated function system

2014 ◽  
Vol 403 ◽  
pp. 21-28 ◽  
Author(s):  
Tingting Ma ◽  
Yuxin Liu ◽  
Qi Dai ◽  
Yuhua Yao ◽  
Ping-an He
Keyword(s):  
Graphical Representation ◽  
Iterated Function System ◽  
Function System ◽  
Iterated Function

Fractal dimension and iterated function system (IFS) for speech recognition

1992 ◽  
Vol 28 (15) ◽  
pp. 1382 ◽  
Author(s):  
E.L.J. Bohez ◽  
T.R. Senevirathne ◽  
J.A. van Winden
Keyword(s):  
Fractal Dimension ◽  
Speech Recognition ◽  
Iterated Function System ◽  
Function System ◽  
Iterated Function

Fractal Top for Contractive and Non-Contractive Transformations

2012 ◽  
Vol 3 (4) ◽  
pp. 49-65
Author(s):  
Sarika Jain ◽  
S. L. Singh ◽  
S. N. Mishra
Keyword(s):  
Fixed Point ◽  
Iterated Function System ◽  
Function System ◽  
Feedback Process ◽  
Iterated Function ◽  
Spatial Part ◽  
One Step ◽  
The One ◽  
Definition Of

Barnsley (2006) introduced the notion of a fractal top, which is an addressing function for the set attractor of an Iterated Function System (IFS). A fractal top is analogous to a set attractor as it is the fixed point of a contractive transformation. However, the definition of IFS is extended so that it works on the colour component as well as the spatial part of a picture. They can be used to colour-render pictures produced by fractal top and stealing colours from a natural picture. Barnsley has used the one-step feed- back process to compute the fractal top. In this paper, the authors introduce a two-step feedback process to compute fractal top for contractive and non-contractive transformations.

scholarly journals Prediction of magnetic storm events using the <i>D<sub>st</sub></i> index

2005 ◽  
Vol 12 (6) ◽  
pp. 799-806 ◽  
Author(s):  
V. V. Anh ◽  
Z. G. Yu ◽  
J. A. Wanliss ◽  
S. M. Watson
Keyword(s):  
Time Series ◽  
Magnetic Storm ◽  
Iterated Function System ◽  
Numerical Results ◽  
Function System ◽  
Storm Events ◽  
Dst Index ◽  
Measure Representation ◽  
Iterated Function

Abstract. This paper provides a method to predict magnetic storm events based on the time series of the Dst index over the period 1981-2002. This method is based on the multiple scaling of the measure representation of the Dst time series. This measure is modeled as a recurrent iterated function system, which leads to a method to predict storm patterns included in its attractor. Numerical results are provided to evaluate the performance of the method in outside-sample forecasts.

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