What the terms orthogonal & basis function denote in case of signals

In summary, basis functions are a set of linearly independent functions that can be combined to form any signal, whether simple or complex, through a process called summation. In the context of signals, basis functions are often orthogonal, meaning that they have no overlap, which makes them useful for representing signals in a unique and efficient way. The use of basis functions has important physical implications, as it allows for the mathematical analysis and manipulation of signals, leading to a better understanding and control of various physical systems.
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ramdas
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I am a beginer. I have read that any given signal whether it simple or complex one,can be represented as summation of orthogonal basis functions.Here, what the terms orthogonal and basis functions denote in case of signals? Can anyone explain concept with an example?Also,what are the physical implications of basis functions?
 
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  • #3
ramdas said:
I am a beginer. I have read that
any given signal whether it simple
or complex one,can be
represented as summation of
orthogonal basis functions.Here, what the terms orthogonal
and basis functions denote in
case of signals?
One set of basis functions that is used a lot in Fourier series is the set ##\{\sin(t), \sin(2t), \sin(3t), \dots, \sin(nt), \dots\}##. These functions are orthogonal on the interval ##[0, \pi]##, which means that the inner product of any two distinct functions in this set is zero. In other words, ##\int_0^{\pi} \sin(kt) \sin(mt)~dt = 0##, if ##k \neq m##.

The term basis is linear algebra terminology that has to do with vector spaces (or function spaces, which are nearly the same as vector spaces). For a given space, a basis is a set of vectors (or functions) that are (1) linearly independent and (2) span the space.

For a simple example of these concepts, let's take R2, the plane. This space (it's a vector space) has a natural basis, {<1, 0>, <0, 1>}. Every vector in R2 can be written as a linear combination of the two vectors in the basis. For example, <3, 4> = 3<1, 0> + 4<0, 1>. In a similar way, a function that represents a signal can be written as a linear combination of the basis functions.
ramdas said:
How basis functions can be
explained mathematically and what
are the physical implications of it?
 
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Related to What the terms orthogonal & basis function denote in case of signals

1. What does the term "orthogonal" mean in relation to signals?

The term "orthogonal" refers to two signals being perpendicular to each other. In other words, the two signals have no correlation or similarity between them.

2. How are orthogonal signals useful in signal processing?

Orthogonal signals are useful in signal processing because they can be easily separated and analyzed individually without interference from each other. This makes it easier to understand and manipulate complex signals.

3. What is the significance of basis functions in signal processing?

Basis functions are fundamental building blocks that can be combined to create more complex signals. They provide a way to represent a signal in a simpler form and make it easier to analyze and process.

4. Can you give an example of a basis function in signal processing?

One example of a basis function is the sine wave. This simple function can be combined with other basis functions, such as cosine waves, to represent more complex signals. The combination of these basis functions can be adjusted to accurately represent a wide range of signals.

5. How do orthogonal signals and basis functions relate to each other?

Orthogonal signals can serve as basis functions in signal processing. This means that they can be used as building blocks to construct more complex signals. Additionally, orthogonal basis functions have the advantage of being easy to manipulate and analyze separately, making them a useful tool in signal processing.

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