What is the concept of fractal dimension and how is it computed?

In summary, the conversation discusses the concept of fractal dimension and how it is computed. The Koch snowflake is used as an example, and it is explained that the number of features added at each iteration and the scaling factor are important factors in determining the fractal dimension. Other methods for approximating the fractal dimension are also mentioned.
  • #1
hedipaldi
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Hi,
Can someone give me a link to a clear and relatively basic and short matirial introducing the notion of fractal dimension (Hausdorff dimension)?
Thank's in advance.
 
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  • #2
To compute a fractal dimension, you have to know how the object is "constructed". Let's use the Koch snowflake as an example:

362px-KochFlake.svg.png


To compute the fractal dimension, you have to know:

1) how many new features are added at every iteration
2) what scale the new feature has at every iteration

At the 0th iteration (top left), there's 3 lines each of the same length (let's call it L).

At the first iteration, we see that there are now 4 features per old but there are all 1/3 of the previous line.

At the second iteration, we add replace with 16 new features (4 for each of the last 4) and multiply the new Length, and each of those are 1/3 of the previous 1/3.

So we see a trend, for each iteration, n:

4^n new things added
(1/3)^n is the scaling factor

So we would say N = 4 and e = 1/3 and compute the fractional dimension:

D = log(N)/log(1/e) = log(4)/log(3) ~ 1.2

There are other ways to approximate a fractal dimension, like the box dimension. They are especially useful when you don't have a nice simple shape like the Koch snowflake.

Some external links:

3.3 Fractal Dimension

Fractal Dimension

Fractals & the Fractal Dimension
 
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1. What is the Fractal (Hausdorff) dimension?

The Fractal (Hausdorff) dimension is a mathematical concept that measures the complexity or irregularity of a geometric shape. It is a non-integer dimension that is used to describe self-similar and infinitely complex patterns found in nature and mathematics.

2. How is the Fractal (Hausdorff) dimension calculated?

The Fractal (Hausdorff) dimension is calculated by taking the logarithm of the number of self-similar pieces needed to cover a shape at different scales and dividing it by the logarithm of the scale factor. This results in a fractional value that represents the fractal dimension of the shape.

3. What is the significance of the Fractal (Hausdorff) dimension?

The Fractal (Hausdorff) dimension is significant because it allows us to quantify and compare the complexity of different shapes and patterns. It also helps us better understand the structure and behavior of natural phenomena, such as coastlines, mountain ranges, and biological systems, that exhibit self-similarity and fractal properties.

4. How is the Fractal (Hausdorff) dimension used in real-world applications?

The Fractal (Hausdorff) dimension has numerous applications in various fields, including physics, biology, chemistry, and computer science. It is used to analyze and model complex systems, improve data compression and image processing techniques, and study the behavior of financial markets and the spread of diseases.

5. Can the Fractal (Hausdorff) dimension be greater than 3?

Yes, the Fractal (Hausdorff) dimension can be greater than 3. In fact, some fractal objects, such as the Sierpinski tetrahedron, have a dimension of 3.58. This is because the Fractal (Hausdorff) dimension is not limited to physical space and can represent the complexity of objects in abstract mathematical spaces.

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