Transcript Slide 1

By Thomas Bowditch
A fractal is generally,
"a rough or fragmented geometric shape that can be subdivided in parts,
each of which is (at least approximately) a reduced-size copy of the whole,“
This is a property called self-similarity. The term was coined by Benoît
Mandlebrot in 1975 and was derived from the Latin fractus meaning "broken"
or "fractured".
A fractal often has the following features:
•It has a fine structure at arbitrarily small scales.
•It is too irregular to be easily described in traditional Euclidean geometric language.
•It is self-similar (at least approximately).
•It has a Hausdorff dimension which is greater than its topological dimension (although this requirement is not
met by space-filling curves such as the Hilbert curve).
•It has a simple and recursive definition.
Because they appear similar at all levels of magnification, fractals are often considered to be infinitely complex (in
informal terms). Natural objects that approximate fractals to a degree include clouds, mountain ranges, lightning bolts,
coastlines, and snow flakes. However, not all self-similar objects are fractals. For example, a straight Euclidean line is
formally self-similar but fails to have other fractal characteristics.
The Koch snowflake is a Mathematical curve and one of the earliest fractal curves to have been
described. It appeared in a 1904 paper entitled "On a continuous curve without tangents, constructible
from elementary geometry by the Swedish mathematician Helge von Koch. The lesser known Koch curve
is the same as the snowflake, except it starts with a line segment instead of an equilateral triangle.
One can imagine that it was created by starting with a line segment, then recursively altering each line
segment as follows:
Divide the line segment into three segments of equal length.
Draw an equilateral triangle that has the middle segment from step 1 as its base and points
outward.
Remove the line segment that is the base of the triangle from step 2.
The area of the Koch snowflake is ,
where s is the measure of one side of the original triangle,
and so an infinite perimeter encloses a finite area.
Let
the
be the number of sides,
be the length of a single side,
th iteration. Further, denote the area of the initial
The capacity dimension is then
be the length of the perimeter, and
triangle, and the length of an initial
the snowflake's area after
side 1. Then
The Koch curve has an infinite length because each time
the steps above are performed on each line segment of
the figure there are four times as many line segments, the
length of each being one-third the length of the segments
in the previous stage. Hence the total length increases by
one third and thus the length at step n will be (4/3)n: the
fractal dimension is log 4/log 3 ≈ 1.26, greater than the
dimension of a normal line
Here is how the curve is recursively constructed:
We start with a line segment (step 0, top segment.) Then on each
step we do the following:
1.Divide the line segment in three parts.
2.Draw an equilateral triangle with the middle segment as base.
3.Remove the middle segment .
Three common techniques for generating fractals are:
Escape-time fractals — These are defined by a
recurrence relation at each point in a space (such
as the complex plane). Examples of this type are
the Mandelbrot set, Julia set, the Burning Ship
fractal and the Lyapunov fractal.
Iterated function systems — These have a fixed
geometric replacement rule. Cantor set, Sierpinski
carpet, Sierpinski gasket, Peano curve, Koch
snowflake, Harter-Heighway dragon curve, TSquare, Menger sponge, are some examples of
such fractals.
Random fractals — Generated by stochastic
rather than deterministic processes, for example,
trajectories of the Brownian motion, Lévy flight,
fractal landscapes and the Brownian tree. The
latter yields so-called mass- or dendritic fractals,
for example, diffusion-limited aggregation or
clusters.
Mandelbrot set
Fractals can also be classified according to their self-similarity. There are three types of
self-similarity found in fractals:
Exact self-similarity — This is the strongest type of self-similarity;
the fractal appears identical at different scales. Fractals defined by
iterated function systems often display exact self-similarity.
Quasi-self-similarity — This is a loose form of self-similarity; the
fractal appears approximately (but not exactly) identical at different
scales. Quasi-self-similar fractals contain small copies of the entire
fractal in distorted and degenerate forms. Fractals defined by
recurrence relations are usually quasi-self-similar but not exactly selfsimilar.
Statistical self-similarity — This is the weakest type of self-similarity;
the fractal has numerical or statistical measures which are preserved
across scales. Most reasonable definitions of "fractal" trivially imply
some form of statistical self-similarity. (Fractal dimension itself is a
numerical measure which is preserved across scales.) Random fractals
are examples of fractals which are statistically self-similar, but neither
exactly nor quasi-self-similar.
Approximate fractals are easily found in nature.
These objects display self-similar structure over an extended, but
finite, scale range. Examples include clouds, snow flakes, crystals,
mountain ranges, lightning, river networks, cauliflower or broccoli, and
systems of blood vessels and pulmonary vessels. Coastlines may be
loosely considered fractal in nature. Trees and ferns are fractal in
nature and can be modelled on a computer by using a recursive algorithm.
This recursive nature is obvious in these examples — a branch from a
tree or a frond from a fern is a miniature replica of the whole: not
identical, but similar in nature.
In 1999, certain self similar fractal shapes were shown to have a
property of "frequency invariance" — the same electromagnetic
properties no matter what the frequency
Fractal that models the surface of a mountain
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ISBN 0-7167-1186-9.
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FOR FREQUENCY INDEPENDENCE IN ANTENNAE ", Fractals, Vol. 7, No. 1 (1999) 7984
Richard Taylor, Adam P. Micolich and David Jonas. Fractal Expressionism : Can Science Be
Used To Further Our Understanding Of Art?
A Panorama of Fractals and Their Uses by Michael Frame and Benoit B. Mandelbrot
Ron Eglash. African Fractals: Modern Computing and Indigenous Design. New Brunswick:
Rutgers University Press 1999.
Peng, Gongwen; Decheng Tian (21 July 1990). "The fractal nature of a fracture surface".
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