What is a non-linear gaussian?

In summary, the conversation discusses the meaning and implications of a "linear Gaussian" and its potential applications, specifically in image filtering. There is also a discussion on the use of the term "non-linear" and its interpretation. The conversation concludes with the suggestion to research more on image filtering as a way to gain a better understanding of the concept of a linear Gaussian.
  • #1
stabu
26
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Googling this has only given me fairly detailed scientific papers and wikipedia (unusually) doesn't come up. Does anybody have a cheap and cheerful definition?
Deducing these terms literally is not risk-free, but I suppose it involves a Gaussian probability distribution N(mu,sigma) where mu and sigma (may be one, may be both) do not vary linearly with a certain parameter .. potentially, time.

Still, that leaves it too general ... I expect it may implicitly refer to some methods. Certainly, image filtering seems to be one of its more salient applications.

However, I have to admit that I'm not very happy with usage of the term "non-linear". For me it has always meant "not specifically linear", which only implies to me a more general case.

Anyhow, any clues welcome, thank you.
 
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  • #2
What's a linear gaussian, and is a noun missing?
 
  • #3
thanks for the question ...he,he.

I can answer a little and say that there is always something missing from any title or label. The missing bit is usually found implicitly n the background or context.

A Gaussian ... well the noun is implicit. It could be a distribution, but also a process. The linearity or non-linearity must refer to the variables that define the Gaussian, and how they change with reference to some parameter, which can often be time t.

As you have asked off somebody who also originally asked a question, this thread can quickly descend into the blind leading the blind, and end up with a bunch of mush as its result.

However, I am surmising so may be I'm not miles away. A Gaussian can also easily be a process which may be an iterated application of the normal probability distribution, where each time the mean and variance ([itex]\sigma^2[/itex] not "sigma" as I said previously) vary each time the iteration is applied. That variation may be linear or non-linear.

I think I'll run off now and check out the Image filtering application, maybe that's the best way to find out.
 

1. What does "non-linear gaussian" mean?

A non-linear gaussian refers to a type of mathematical function or distribution that is non-linear, meaning it does not follow a straight line, and is characterized by a bell-shaped curve known as a gaussian or normal distribution.

2. How is a non-linear gaussian different from a linear gaussian?

A linear gaussian follows a straight line, whereas a non-linear gaussian does not. Additionally, a linear gaussian has equal variance across all values, while a non-linear gaussian typically has varying variance.

3. What is the significance of a non-linear gaussian in scientific research?

Non-linear gaussian functions are commonly used to model and understand complex systems in various fields, such as physics, biology, and economics. They can provide insights into the behavior of these systems and help make predictions and inferences.

4. How is a non-linear gaussian function represented mathematically?

A non-linear gaussian function is typically represented by the formula f(x) = A * exp(-(x - B)^2 / 2C^2), where A, B, and C are parameters that determine the shape and location of the curve.

5. Can non-linear gaussian functions be used for data analysis?

Yes, non-linear gaussian functions can be used for data analysis, especially when the data follows a bell-shaped distribution. They can be used to fit and analyze data, identify outliers, and make predictions about future data points.

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