Self-Referentiality, Fractels, and Applications

Similar documents
Analytic Continuation of Analytic (Fractal) Functions

NOTES ON BARNSLEY FERN

Construction of Smooth Fractal Surfaces Using Hermite Fractal Interpolation Functions. P. Bouboulis, L. Dalla and M. Kostaki-Kosta

THE CONLEY ATTRACTORS OF AN ITERATED FUNCTION SYSTEM

ITERATED FUNCTION SYSTEMS WITH CONTINUOUS PLACE DEPENDENT PROBABILITIES

arxiv: v1 [math.ds] 17 Mar 2010

Approximation of the attractor of a countable iterated function system 1

HIDDEN VARIABLE BIVARIATE FRACTAL INTERPOLATION SURFACES

Wavelet Sets, Fractal Surfaces and Coxeter Groups

ITERATED FUNCTION SYSTEMS WITH A GIVEN CONTINUOUS STATIONARY DISTRIBUTION

HABILITATION THESIS. New results in the theory of Countable Iterated Function Systems

Expectations over Fractal Sets

Fractals. R. J. Renka 11/14/2016. Department of Computer Science & Engineering University of North Texas. R. J. Renka Fractals

Local time of self-affine sets of Brownian motion type and the jigsaw puzzle problem

NATIONAL BOARD FOR HIGHER MATHEMATICS. Research Scholarships Screening Test. Saturday, February 2, Time Allowed: Two Hours Maximum Marks: 40

Fractals and iteration function systems II Complex systems simulation

Fractals, fractal-based methods and applications. Dr. D. La Torre, Ph.D.

A class of domains with fractal boundaries: Functions spaces and numerical methods

INVERSE FUNCTION THEOREM and SURFACES IN R n

TOPOLOGY PROCEEDINGS Volume 36 (2010) Pages E-Published on April 2, 2010

Notes for Functional Analysis

Iterated function systems on functions of bounded variation

USING THE RANDOM ITERATION ALGORITHM TO CREATE FRACTALS

Topological dynamics: basic notions and examples

THE SHIFT SPACE FOR AN INFINITE ITERATED FUNCTION SYSTEM

Generation of Fractals via Self-Similar Group of Kannan Iterated Function System

Spectral Properties of an Operator-Fractal

Mathematical Analysis Outline. William G. Faris

arxiv: v1 [math.ds] 31 Jul 2018

Estimating the Spatial Extent of Attractors of Iterated Function Systems

Properties of Linear Transformations from R n to R m

7. Let X be a (general, abstract) metric space which is sequentially compact. Prove X must be complete.

MET Workshop: Exercises

Construction of recurrent fractal interpolation surfaces(rfiss) on rectangular grids

5 FUNCTIONS. 5.1 Definition and Basic Properties. c Dr Oksana Shatalov, Fall

Course 212: Academic Year Section 1: Metric Spaces

Examensarbete. Fractals and Computer Graphics. Meritxell Joanpere Salvadó

V -variable fractals and superfractals

9 FUNCTIONS. 9.1 The Definition of Function. c Dr Oksana Shatalov, Fall

3 FUNCTIONS. 3.1 Definition and Basic Properties. c Dr Oksana Shatalov, Fall

MATH 104: INTRODUCTORY ANALYSIS SPRING 2008/09 PROBLEM SET 8 SOLUTIONS

Definition: For nonempty sets X and Y, a function, f, from X to Y is a relation that associates with each element of X exactly one element of Y.

Changes to the third printing May 18, 2013 Measure, Topology, and Fractal Geometry

The projectivity of C -algebras and the topology of their spectra

Plasticity of the unit ball and related problems

ON THE DIAMETER OF THE ATTRACTOR OF AN IFS Serge Dubuc Raouf Hamzaoui Abstract We investigate methods for the evaluation of the diameter of the attrac

ON LEFT-INVARIANT BOREL MEASURES ON THE

Topological properties

Economics 204 Summer/Fall 2011 Lecture 5 Friday July 29, 2011

SPRING 2006 PRELIMINARY EXAMINATION SOLUTIONS

Fractals and Dimension

Math 421, Homework #9 Solutions

Random measures, intersections, and applications

THE HUTCHINSON BARNSLEY THEORY FOR INFINITE ITERATED FUNCTION SYSTEMS

1. Bounded linear maps. A linear map T : E F of real Banach

Minkowski Sums and Aumann s Integrals in Set Invariance Theory for Autonomous Linear Time Invariant Systems

NATIONAL BOARD FOR HIGHER MATHEMATICS. M. A. and M.Sc. Scholarship Test. September 22, Time Allowed: 150 Minutes Maximum Marks: 30

B. Appendix B. Topological vector spaces

d(x n, x) d(x n, x nk ) + d(x nk, x) where we chose any fixed k > N

Random fixed point equations and inverse problems by collage theorem

1. Simplify the following. Solution: = {0} Hint: glossary: there is for all : such that & and

3 FUNCTIONS. 3.1 Definition and Basic Properties. c Dr Oksana Shatalov, Spring

Cuntz algebras, generalized Walsh bases and applications

FINAL PROJECT TOPICS MATH 399, SPRING αx 0 x < α(1 x)

Simultaneous zero inclusion property for spatial numerical ranges

Copulas with fractal supports

Language-Restricted Iterated Function Systems, Koch Constructions, and L-systems

Take a line segment of length one unit and divide it into N equal old length. Take a square (dimension 2) of area one square unit and divide

MAS3706 Topology. Revision Lectures, May I do not answer enquiries as to what material will be in the exam.

ON RIGIDITY OF ALGEBRAIC DYNAMICAL SYSTEMS

MATH 23b, SPRING 2005 THEORETICAL LINEAR ALGEBRA AND MULTIVARIABLE CALCULUS Midterm (part 1) Solutions March 21, 2005

3 FUNCTIONS. 3.1 Definition and Basic Properties. c Dr Oksana Shatalov, Fall

Solve EACH of the exercises 1-3

2) Let X be a compact space. Prove that the space C(X) of continuous real-valued functions is a complete metric space.

Notas de Aula Grupos Profinitos. Martino Garonzi. Universidade de Brasília. Primeiro semestre 2018

Vector Space and Linear Transform

Commutative Banach algebras 79

BOUNDARY VALUE PROBLEMS ON A HALF SIERPINSKI GASKET

A NOTE ON MATRIX REFINEMENT EQUATIONS. Abstract. Renement equations involving matrix masks are receiving a lot of attention these days.

Fast Basins and Branched Fractal Manifolds of Attractors of Iterated Function Systems

VALUATION THEORY, GENERALIZED IFS ATTRACTORS AND FRACTALS

Lecture Notes 6: Dynamic Equations Part C: Linear Difference Equation Systems

A nonlinear equation is any equation of the form. f(x) = 0. A nonlinear equation can have any number of solutions (finite, countable, uncountable)

On a Topological Problem of Strange Attractors. Ibrahim Kirat and Ayhan Yurdaer

PDEs in Image Processing, Tutorials

Lecture 5: The Bellman Equation

A PROOF OF A CONVEX-VALUED SELECTION THEOREM WITH THE CODOMAIN OF A FRÉCHET SPACE. Myung-Hyun Cho and Jun-Hui Kim. 1. Introduction

Math113: Linear Algebra. Beifang Chen

Undecidable properties of self-affine sets and multi-tape automata

RECURRENT ITERATED FUNCTION SYSTEMS

Austin Mohr Math 730 Homework. f(x) = y for some x λ Λ

The Order in Chaos. Jeremy Batterson. May 13, 2013

Real Analysis Chapter 4 Solutions Jonathan Conder

CONTRACTION MAPPING & THE COLLAGE THEOREM Porter 1. Abstract

THE DAUGAVETIAN INDEX OF A BANACH SPACE 1. INTRODUCTION

Selçuk Demir WS 2017 Functional Analysis Homework Sheet

Geometry and topology of continuous best and near best approximations

P.S. Gevorgyan and S.D. Iliadis. 1. Introduction

Walker Ray Econ 204 Problem Set 2 Suggested Solutions July 22, 2017

Nondeterministic Kinetics Based Feature Clustering for Fractal Pattern Coding

Transcription:

Self-Referentiality, Fractels, and Applications Peter Massopust Center of Mathematics Research Unit M15 Technical University of Munich Germany 2nd IM-Workshop on Applied Approximation, Signals, and Images, Bernried, Feb 27 - Mar 3, 2017 1 / 43

Joint work with Michael Barnsley (Australian National University) Markus Hegland (Australian National University and Institute of Advanced Study, Technical University of Munich, Germany) 2 / 43

Outline Iterated Function Systems (IFSs) Fractal Functions Fractels Local IFSs 3 / 43

Iterated Function Systems Standing assumptions: (X, d X ) is a complete metric space with metric d X. 1 < n N and N n := {1,..., n}. A family F of continuous mappings f i : X X, i N n, is called a iterated function system (IFS). If all mappings in F are contractive on X then the IFS is called contractive. Assumption: From now on all f i are contractive. 4 / 43

Hyperspace of Nonempty Compact Subsets of X Let (H(X), d H ) be the hyperspace of nonempty compact subsets of X endowed with the Hausdorff metric d H : d H (A, B) := max{max a A min b B d X(a, b), max b B min a A d X(a, b)}. Define F : H(X) H(X) by n F(B) := f i (B). i=1 (J. Hutchinson [1981], M. Barnsley & S. Demko [1985]) 5 / 43

Some Results (X, d X ) complete implies (H(X), d H ) complete. If all f i : X X are contractive on X with contractivity constants s i ( 1, 1) then F : H(X) H(X) is contractive on H(X) with contractivity constant s = max{s i }. The Banach Fixed Point Theorem implies that F has a unique fixed point in H(X). This fixed point A is called the fractal generated by the IFS F. A = F(A) = n f i (A). i=1 Self-referential equation 6 / 43

Construction of Fractals Via IFSs Consequences of the Banach Fixed Point Theorem: Let E 0 H(X) be arbitrary. Set E k := F(E k 1 ) = n i=1 f i (E k 1 ). Then A = lim k E k = lim k F k (E 0 ). 7 / 43

Sierpiński Triangle T Define f i : [0, 1] 2 [0, 1] 2 by f 0 (x, y) = ( x 2, y 2), f 1 (x, y) = ( x f 2 (x, y) = 2 + 1 2, y 2), ( x 2 + 1 4, y 2 + 3 4 ). T = f 0 (T) f 1 (T) f 2 (T) (W. Sierpiński [1915]) 8 / 43

Semi-Group Property F 2 (A) = (F F)(A) = (f 1 f 1 )(A) (f 1 f 2 )(A) (f n f n )(A) n = (f i1 f i2 )(A). i 1,i 2 =1 In general: n F k (A) = (f i1 f ik )(A). i 1,...,i k =1 Hence A = lim k F k (A). A is invariant under the semi-group S[F] generated by f F. 9 / 43

Collage Theorem (Barnsley 1985) Let M H(X) and ε > 0 be given. Suppose that F is a (contractive) IFS such that ) n d H (M, f i (M) ε. then i=1 d H (M, A) ε 1 s, where A is the fractal generated by the IFS F and s := max{s i }. 10 / 43

The Barnsley Fern 11 / 43

The Barnsley fern is a fractal model of a fern belonging to the black spleenwort variety. It is generated by the IFS {f i : [0, 1] 2 [0, 1] 2 }, where ( ) cos x f 1 := y 4 60 π 5 sin 60 π sin 60 π cos 60 π ( ( ) x 0 + y) 3, 2 ( ) cos 5π x f 2 := y 3 1 18 sin 5π 18 ( ) 1 x 3 cos 2π 3 f 3 := y 1 3 sin 2π 3 sin 5π 18 cos 5π 18 9 sin 5π 25 18 25 9 cos 5π 18 ( ( ) x 0 + y) 3, 2 ( ( ) x 0 + y) 2, 5 ( ) 0 0 x f 4 := y 0 11 50 ( x y). 12 / 43

Fractal Functions - Geometric Construction 1 1 0.8 0.75 0.6 0.5 0.4 0.25 0.2-0.25 0.2 0.4 0.6 0.8 1 0.2 0.4 0.6 0.8 1 1 0.8 0.6 0.4 0.8 0.6 0.4 0.2 0.2-0.2 0.2 0.4 0.6 0.8 1 0.2 0.4 0.6 0.8 1-0.2 13 / 43

Fractal Functions - Analytic Construction Let Ω := [0, n) R. Let u k : Ω Ω, u k (x) := x n + k, k = 0, 1,..., n 1. Let λ k : R R be bounded functions, and s k R. For g L (Ω) define a Read-Bajractarević (RB) operator by n 1 T (g) := (λ k u 1 k=0 n 1 k )χ u k (Ω) + k=0 s k (g u 1 k )χ u k (Ω). If max s k < 1, then T is contractive on L (Ω) and its unique fixed point f : Ω R satisfies n 1 f = (λ k u 1 k=0 n 1 k )χ u k (Ω) + k=0 s k (f u 1 k )χ u k (Ω) f is called a fractal function. 14 / 43

Equivalent characterization of a fractal function: f(u k (x)) = λ k (x) + s k f(x), x [0, n), k. The fixed point f can be evaluated via where f 0 L. f = lim k T k f 0, The rate of convergence is given by Moreover, f T k f 0 sk 1 s T f 0 f 0. T 1 + s 1 s. 15 / 43

Inhomogeneous Refinability Extend f to R by setting it equal to zero off Ω. Let n 1 (λ k u 1 k ) χ u k (Ω), on Ω k=0 Λ := 0, on R \ Ω. The fixed point equation for f can then be written as n 1 f(x) = Λ(x) + s k f (Nx k). k=0 16 / 43

Examples (T t f)(x) = { x + 1 2 f(2x), x [0, 1); (2 x) + 1 2 f(2x 1), x [1, 2). (T p f)(x) = { x + 1 4 f(2x), x [0, 1); (2 x) + 1 4 f(2x 1), x [1, 2). 17 / 43

1.0 1.0 0.8 0.8 0.6 0.6 0.4 0.4 0.2 0.2 18 / 43

1.0 1.0 0.8 0.8 0.6 0.6 0.4 0.4 0.2 0.2 18 / 43

1.2 1.0 1.0 0.8 0.8 0.6 0.4 0.2 0.6 0.4 0.2 18 / 43

1.2 1.0 1.0 0.8 0.8 0.6 0.4 0.2 0.6 0.4 0.2 18 / 43

1.0 1.2 1.0 0.8 0.8 0.6 0.6 0.4 0.2 0.4 0.2 0.5 1.0 1.5 2.0 0.5 1.0 1.5 2.0 Takagi function f(x) = x(2 x) 18 / 43

Relation Between F and T (X, d X ) compact metric space and (Y, d Y ) complete metric space Let f L (X, Y) be a fractal function generated by the RB operator T. The following diagram commutes: X Y G L (X, Y) where G is the mapping F X Y G T L (X, Y) L (X, Y) g G(g) = {(x, g(x)) x X} X Y. 19 / 43

Differentiable Fractal Functions 2.5 2 1.5 1 0.5 0.2 0.4 0.6 0.8 1 7.5 5 2.5-2.5-5 -7.5 0.2 0.4 0.6 0.8 1 300 200 100-100 -200-300 0.2 0.4 0.6 0.8 1 20 / 43

Applications of Fractal Functions Fractal functions can be pieced together to generate multiresolution analyses and continuous compactly supported refinable functions and wavelets. In the literature these became known as the GHM scaling vector and the DGHM multiwavelet. 1 0.8 0.6 0.4 0.2 0.2 0.4 0.6 0.8 1 1 0.8 0.6 0.4 0.2-1 -0.5 0.5 1-0.2 75 100 50 25 50-1 -0.5 0.5 1-1 -0.5 0.5 1-25 -50-50 -75-100 21 / 43

A Fundamental Result D. Hardin proved in 2012 that every compactly supported refinable function is a piecewise fractal function. In particular, the unique compactly supported continuous function determined by the mask of a convergent subdivision scheme is a piecewise fractal function. 22 / 43

Every Continuous Function is a Fractal Function Let f C[a, b] and h C[a, b] any function with h(a) = f(a) and h(b) = f(b). Then f generates an entire family of fractal functions via the fixed point of T g := f + n k=1 s k (g h) u 1 k χ u k (Ω). This family is parametrized by the scaling factors s k and its construction is reminiscent of splines. If s k = 0 for all k then T f = f, i.e., every continuous function is a fractal function. 23 / 43

Approximation with Fractal Functions By the Collage Theorem one can approximate the graph of any function arbitrarily close by the graph of a fractal function. But one can do better... 24 / 43

Fractels Let (X, d X ) and (Y, d Y ) be complete metric spaces. Let u : X X be an injective mapping. Let f : dom f X Y. An invertible mapping w C(X Y) of the form w(x, y) = (u(x), v(x, y)), for some v : X Y Y, and which satisfies w(graph f) graph f, is called a fractel for f. 25 / 43

Characterization of Fractels Fractel is an abbreviation for fractal element. The class of fractels is not empty; the identity function id X Y on X Y is a fractel for any function f. This fractel is called the trivial fractel. If w = (u, v) is a fractal for f, then u(dom f) dom f. The function w : X Y X Y is a fractel for f if and only if for all x dom f X. v(x, f(x)) = f(u(x)), 26 / 43

Example of a Fractel Let f : R + R be given by f(x) := ax p, where a, p R. Then, a nontrivial fractel for f is w(x, y) = ( x 2, y 2 p ), where v(x, y) = y 2 p : v(x, ax p ) = axp 2 p = f( x 2 ). The fractel ( x 2, y 2 p ) is independent of a and linear in (x, y). Note that different functions may share the same fractel. 27 / 43

Semi-Group of Fractels Suppose that w 1 = (u 1, v 1 ) and w 2 = (u 2, v 2 ) are fractels for f : X Y. Then w 1 w 2 := (u 1 u 2, v 1 (u 2, v 2 )) is also a fractel for f. The collection of all nontrivial fractels of a given function f forms a semi-group under composition. The collection of all fractels of a function f forms a monoid under where the identity element is the trivial fractel. 28 / 43

Self-Referential Functions A function f : X Y is called self-referential if it has a nontrivial semigroup of fractels. Example f : [0, 1] R, x 4x(1 x). f( x 2 ) = x + 1 4f(x) and f(x+1 2 ) = 1 x + 1 4 f(x). Two fractels: w 1 (x, y) = ( 1 2 x, x + 1 4 y), w 2 (x, y) = ( 1 2 (x + 1), 1 x + 1 4 y). Recall: graph f is invariant under the semi-group generated by {w 1, w 2 }. 29 / 43

Let X := R m and Y := R n. Linear Fractels Let GL(n, R) be the general linear group on R n and Aff(m, R) = R m GL(m, R) the affine group over R m. Let f : R m R n be a function. A fractel w = (u, v) of f is called linear if (i) u Aff(m, R) and (ii) v(x, ) GL(n, R), x R m. A linear fractel w has the explicit form w(x, y) = (Ax + b, My), where A and M are invertible matrices and b R m. 30 / 43

A Property of Linear Fractels Let w be a linear fractel. Then all the eigenvalues of the matrix A GL(d, R) have modulus 1 and at least one eigenvalue has modulus strictly less than 1. If d = 1, then A < 1. This proposition together with A(dom(f)) dom(f) implies that the collection of all fractels, including the trivial fractel, cannot form a group under function composition. 31 / 43

Algebra of Fractels If f : X Y is bijective, then a fractel for f is given by w(x, y) := (u(x), f u f 1 (y)). If w = (u, v), u GL(d, R), is a fractel for f : R d Y, then (A 1 u A(x) + A 1 (u I)b, v(ax + b, y)) is a fractel for f(ax + b), where I is the unit of GL(d, R). 32 / 43

Fractels for the Ring of Functions f : X C Let f 1, f 2 : X C. Let w i : X Y X Y, where w i = (u, v i ) is a fractel for f i, i = 1, 2. (i) A fractel for f 1 + f 2 is (u(x), F 1 (x, y f 2 (x)) + v 2 (x, y f 1 (x))). (ii) A fractel for af 1, a R\{0}, is (u(x), av 1 (x, y/a). (iii) If dom(f 1 ) dom(f 2 ) and if f 1 f 2 0 on dom(f 1 ) dom(f 2 ), then a fractel for f 1 f 2 is ( ) )) (u(x), v 1 x, v 2 (x,. y f 2 (x) y f 1 (x) 33 / 43

From Fractels to Fractals Let f : [0, 1] R, x x m + g 1 (x), where m R\{0} and g 1 : [0, 1] R. Let s 1, s 2 > 0 with s 1 + s 2 1. Let w 1 : R 2 R 2, (x, y) (s 1 x, s m 1 y + g 1 (s 1 x) s m 1 g 1 (x)), and w 2 : R 2 R 2, (x, y) (s 2 x s 2 +1, s 2 m y+g 2 (s 2 x) s 2 m g 2 (x)), where g 2 (x) = x m (x 1) m + g 1 (x). The IFS {[0, 1] R; w 1 (x, y), w 2 (x, y)} is contractive and its attractor is graph f. 34 / 43

Local IFSs Let {X i : i N n } be a family of nonempty subsets of X. Let for each X i exist a contractive mapping f i : X i X. Then F loc := {(X i, f i ) : i N n } is called a local IFS. Note that if X i = X for all i then one obtains an IFS. Define a set-valued operator F loc : 2 X 2 X by n F loc (S) := f i (S X i ). i=1 A 2 X is called a local fractal if n A = F loc (A) = f i (A X i ). i=1 35 / 43

Assumptions: X is compact. Construction of Local Fractals All X i are closed, i.e., compact in X. Local IFS {(X i, f i ) : i N n } is contractive. Let K 0 := X and K k := F loc (K k 1 ) = i N n f i (K k 1 X i ) Assume that K k. (E.g.: f i (X i ) X i, i N n.) Then K := K k and K = lim K k. n N 0 k K = lim K k = lim f i (K k 1 X i ) = f i (K X i ) = F loc (K). k k i N n i N n 36 / 43

Approximation of Functions with Fractels Consider fractels which have a domain dom w = dom u R where the domain of u is an interval [a, b]. u(x) := x+τ 2 for some τ [a, b]. v(x, y) := σy + (1 σ)g(x) for some 0 σ < 1 and G C[a, b]. Approximations are obtained by approximating G(x), for instance, constant approximations G(x) γ. The functions w(x, y) = ( 1 2 (x + τ), σy + (1 σ)γ) are fractels for functions h of the form where 2 θ = σ. h(x) = α(x τ) θ + γ, α R, 37 / 43

Approximation Procedure Generate an approximation of a function f by first constructing its fractels of the form w(x, y) = ( 1 2 (x + τ), σy + (1 σ)g(x)) and then obtain an approximation of w by approximating G by a constant γ: Let f : Ω R have fractel w(x, y) = ( 1 2 (x + τ), σy + λ(x)), where λ is given by (1 σ)g. Further suppose that λ = (1 σ)γ is an approximation for λ. Denote by f the function with fractel w(x, y) = ( 1 2 (x + τ), σy + λ(x)) = ( 1 2 (x + τ), σy + (1 σ)γ)). Then f f G γ. 38 / 43

A Proposition A function f defined by f(x) = α(x τ) θ + g(x), for x [a, b] with θ > 0 and τ [a, b], admits a fractel w with where σ = 2 θ and w(x, y) = ( 1 2 (x + τ), σy + (1 σ)g(x)), G(x) = g ( 1 2 (x + τ)) σg(x). 1 σ 39 / 43

An Example Consider the function f(x) = x, x [0, 1]. A fractel is w 1 (x, y) = ( 1 2 x, 1 2 y) with domain [0, 1] R. w 1 recovers the function f for x [0, 1 2 ]. We now need to recover f for x ( 1 2, 1]. For this we introduce two fractels defined over the domain [ 1 2, 1] R. First. choose the components u i as u i (x) = 1 2 (x + τ i) where τ i = 1 2 (i 1), i = 2, 3. Set g i (x) = x α i (x τ i ) θ i, where θ i > 0 is a free parameter. 40 / 43

This yields G i (x) = 1 2 (x + τ i) σ i x 1 σ i. and therefore the fractels w 2 and w 3 (and a local IFS): w 1 (x, y) = ( 1 2 x, y 2 ), x [0, 1], w 2 (x, y) = ( 1 4 (2x + 1), σ 2y + 2 1 2x + 1 σ2 x), x [ 1 2, 1], w 3 (x, y) = ( 1 2 (x + 1), σ 3y + 1 2 x + 1 σ3 x), x [ 1 2, 1]. Using approximation by the midpoint rule and setting σ i = 1 2 : w 1 (x, y) = ( 1 2 x, y 2 ), x [0, 1], w 2 (x, y) = ( 1 4 (2x + 1), (y + 5 2 1 2 w 3 (x, y) = ( 1 2 (x + 1), (y + 5 1 2 3 2 ), x [ 1 2, 1], 3 2 ), x [ 1 2, 1]. 41 / 43

0.015 0.010 0.005 e_r(x) 0.000 0.005 0.010 10-5 10-4 10-3 10-2 10-1 10 0 x The relative error of the fractal approximation of f(x) = x based on the midpoint formula. 42 / 43

References M. F. Barnsley, M. Hegland, P. Massopust: Numerics and Fractals, Bull. Inst. Math., Academica Sinica (N.S.), Vol. 9 (3)(2014), (389-430) M. F. Barnsley, M. Hegland, P. Massopust: Self-Referential Functions, arxiv:1610.01369. P. Massopust: Interpolation and Approximation with Splines and Fractals, Oxford University Press, January 2010. P. Massopust: Fractal Functions, Fractal Surfaces, and Wavelets, Academic Press, 2nd ed., 2016. THANK YOU! 43 / 43