# Difference between revisions of "Field:Fractals"

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Click here to learn more about [[Iterated Functions]] and its mathematical implications. | Click here to learn more about [[Iterated Functions]] and its mathematical implications. | ||

− | ==Examples of fractals== | + | ====Examples of fractals== |

There are four main types of fractals that are categorized by how they are generated. In addition, numerous fractals occur naturally, including lightening, broccoli, blood vessels, and in landscapes. | There are four main types of fractals that are categorized by how they are generated. In addition, numerous fractals occur naturally, including lightening, broccoli, blood vessels, and in landscapes. | ||

− | * | + | *Iterated function systems (IFS) |

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::Fractals created with IFS are always exactly self-similarity, so that these fractals are essential constructed of infinitely many infinitely smaller pieces of itself that overlap. The IFS consists of one of more functions or methods that describe the behavior of the fractal. | ::Fractals created with IFS are always exactly self-similarity, so that these fractals are essential constructed of infinitely many infinitely smaller pieces of itself that overlap. The IFS consists of one of more functions or methods that describe the behavior of the fractal. | ||

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+ | *Strange attractors | ||

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+ | ::Fractals that are considered strange attractors are generated from a set of functions called attractor maps or systems. These systems are chaotic, because the functions map points in a seemingly random order. These points are actually not completely random and are in fact evolving towards a structure that can eventually be seen as the form of the attractor. | ||

+ | ::Examples include: [[Lorenzo Attractor]], [[Henon Attractor]], [[Cantor Dust]] , and [[Rossler Attractor]]. | ||

+ | }} | ||

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+ | *Random fractals | ||

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+ | ::These fractals are created through stochastic methods, meaning there are no set functions that determine the behavior of the fractals. Although the fractals still must have rules that they follow, they are unlike chaotic IFS fractals because chaotic fractals are governed by a set of functions that are picked according to probability and these follow some sort of a pattern (and grow exponentially), while random fractals are simply random (and grow randomly). | ||

+ | ::Examples include: [[Levy Flights]], [[Brownian Motion]], [[Brownian Tree]], and fractal landscapes. | ||

+ | }} | ||

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+ | * Escape-time (“orbit”) fractals | ||

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+ | ::Escape-time fractals are created in the <balloon title = “For more information, click here [[Complex Numbers]]” style = “green”> complex plane <\balloon> with a single <balloon title = “such as <math>f(z) = z^2 + c<\math>, where z is a complex number and c is any number” > function<\balloon>, where each pixel corresponds to a complex number. Each complex number value is iterated into the function until it reaches infinite or until it is clear that value will converge to zero. The colors assigned to each complex number value or pixel are black if the value converges to zero or a color based on the number of iterations (aka. escape time) it took for the values to reach infinity. | ||

+ | ::The boundary between black and colorful pixels is infinite and increasing complex. And the intermediary numbers that arise from the iterations are referred to as their “orbit”. | ||

+ | ::Examples include: [[Mandelbrot Set]], [[Julia Sets]], and [[Lyapunov Fractal]]. | ||

+ | }} | ||

+ | }} | ||

*'''Strange attractors''' | *'''Strange attractors''' | ||

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## Revision as of 14:03, 1 June 2009

# Fractals

A fractal is often defined as a geometry shape that is self-similarity>, or whose magnified parts look like a smaller copy of the whole. It was coined by Benoit Mandelbolt in 1975 from the latin term ‘’fractus’’ meaning ”fragmented” or “irregular”.

This concept can be explained in a commonly used nature analogy involving the coastline of an island:

Suppose you wanted to measure the total perimeter of an island. You could begin by roughly estimating the perimeter of the island by measuring the border of the island from a high vantage point like an airplane and using miles as units. Next, to be more accurate, you could walk along the island's borders and measure around its various coves and bays using a measuring tape. Then, if you wanted to be really accurate, you could carefully measurement around every single protruding rock and detail of the island with a yardstick or even a foot-long ruler.

Clearly, the perimeter of the island would grow as you decrease the size of your measuring device and increase the accuracy of your measurements. Also, the island would more or less like similar (in terms of becoming more and more jagged and complex) as you continued to decrease your measuring device.

## Contents |
[[Image:|300px|thumb|right|]] |

**Strange attractors**

**Random fractals**

**Escape-time (“orbit”) fractals**