# Window Properties (By Name) (G Dataflow)

Version:

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

## size

Window size.

size must be greater than 0.

Default: 0

## 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

## error in

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

Default: No error

## 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

## eq noise bw

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

## coherent gain

Coherent gain of the window defined by the window type.

## 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:

$CG=\frac{\underset{i=0}{\overset{n-1}{\sum }}{w}_{i}}{n}$
$ENBW=\frac{n\underset{i=0}{\overset{n-1}{\sum }}{w}_{i}^{2}}{{\left(\underset{i=0}{\overset{n-1}{\sum }}{w}_{i}\right)}^{2}}$

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

Where This Node Can Run:

Desktop OS: Windows

FPGA: Not supported