What is the Inner Product Space for Square-Integrable Functions?

Therefore, in summary, the inner product space of square integrable functions is defined by the integral of the product of a function and its complex conjugate, and this allows for the definition of both the norm and the inner product.
  • #1
mekarim
1
0
http://en.wikipedia.org/wiki/Square-integrable_function


According to the tutorial: it says
g*(x) is the complex conjugate of g

but I can't get the idea from where this g(x) function comes, than why is it the complex conjugate?

And it seems i can't visualize the inner product space? Some practical example would help me a lot.

Thanks!
 
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  • #2
The idea of square integrable functions is that the integral of the squared magnitude converges. For complex valued functions, |f(x)|^2 = ∫ f(x) f*(x) dx, which suggests a natural way to define both the "norm" and the "product" in the space of square integrable functions. You just say that the inner product <f, g> has to satisfy the property that |f|^2 = <f, f> and therefore <f, g> = ∫ f(x) g*(x) dx.
 
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  • #3
In particular, you want [itex]|f|= <f , f>[/itex]. Since the "norm" is defined as [itex]\int f(x)f^*(x)dx= <f,f>[/itex] the natural way to define the "inner product" of two such functions, f and g, is [itex]<f, g>= \int f(x)g^*(x)dx[/itex].
 

Related to What is the Inner Product Space for Square-Integrable Functions?

What is the Short Time Fourier Transform (STFT)?

The Short Time Fourier Transform (STFT) is a mathematical method used to analyze signals and determine their frequency and amplitude over time. It is a time-frequency representation of a signal which breaks down the signal into its individual frequency components at different time intervals.

What is the difference between STFT and Fourier Transform?

The main difference between STFT and Fourier Transform is that STFT is a time-varying representation of a signal, while Fourier Transform is a time-invariant representation. This means that STFT takes into account the changes in a signal over time, while Fourier Transform only considers the signal as a whole.

How does the window function affect the STFT?

The window function is used in STFT to break down a signal into smaller segments. The choice of window function can affect the accuracy and resolution of the STFT. A wider window can provide better frequency resolution but lower time resolution, while a narrower window can provide better time resolution but lower frequency resolution.

What are the applications of STFT?

STFT has various applications in signal processing and analysis, including speech and audio processing, image analysis, and vibration analysis. It is also commonly used in the field of acoustics and music to analyze and modify sound signals.

What are the limitations of STFT?

One limitation of STFT is that it assumes that the signal is stationary, meaning that its statistical properties do not change over time. This may not always be the case for real-world signals. Additionally, the choice of window function and its size can affect the accuracy and resolution of the STFT.

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