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Window Properties (By Name) (G Dataflow)

Version:
    Last Modified: January 9, 2017

    Computes the coherent gain and equivalent noise bandwidth of a window according to the window type.

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    size

    Window size.

    size must be greater than 0.

    Default: 0

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    window type

    Type of window for calculating the properties.

    Name Value Description
    Rectangle 0 Applies a rectangle window.
    Hanning 1 Applies a Hanning window.
    Hamming 2 Applies a Hamming window.
    Blackman-Harris 3 Applies a Blackman-Harris window.
    Exact Blackman 4 Applies an Exact Blackman window.
    Blackman 5 Applies a Blackman window.
    Flat Top 6 Applies a Flat Top window.
    4 Term B-Harris 7 Applies a 4 Term B-Harris window.
    7 Term B-Harris 8 Applies a 7 Term B-Harris window.
    Low Sidelobe 9 Applies a Low Sidelobe window.
    Blackman Nutall 11 Applies a Blackman Nutall window.
    Cosine Tapered 12 Applies a Cosine Tapered window.
    Triangle 30 Applies a Triangle window.
    Bartlett-Hanning 31 Applies a Bartlett-Hanning window.
    Bohman 32 Applies a Bohman window.
    Parzen 33 Applies a Parzen window.
    Welch 34 Applies a Welch window.
    Kaiser 60 Applies a Kaiser window.
    Dolph-Chebyshev 61 Applies a Dolph-Chebyshev window.
    Gaussian 62 Applies a Gaussian window.
    Force 64 Applies a Force window.
    Exponential 65 Applies a Exponential window.

    Default: Rectangle

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    error in

    Error conditions that occur before this node runs. The node responds to this input according to standard error behavior.

    Default: No error

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    window parameter

    A value that affects the output coefficients when window type is Kaiser, Gaussian, or Dolph-Chebyshev.

    If window type is any other type of window, this node ignores this input.

    This input represents the following information for each type of window:

    • Kaiser—Beta parameter
    • Gaussian—Standard deviation
    • Dolph-Chebyshev—The ratio, s, of the main lobe to the side lobe

    Default: NaN—Causes this node to set beta to 0 for a Kaiser window, the standard deviation to 0.2 for a Gaussian window, and s to 60 for a Dolph-Chebyshev window

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    eq noise bw

    Equivalent noise bandwidth of the window defined by the window type.

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    coherent gain

    Coherent gain of the window defined by the window type.

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    error out

    Error information. The node produces this output according to standard error behavior.

    Algorithm for Window Properties

    The following equations define the coherent gain (CG) and equivalent noise bandwidth (ENBW) of a given window:

    C G = i = 0 n 1 w i n
    E N B W = n i = 0 n 1 w i 2 ( i = 0 n 1 w i ) 2

    where wi are the window coefficients and n is the number of coefficients.

    Where This Node Can Run:

    Desktop OS: Windows

    FPGA: Not supported


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