sigwin.tukeywin Class
Namespace: sigwin
Construct Tukey window object
Description
Note
The use of sigwin.tukeywin
is not recommended.
Use tukeywin
instead.
sigwin.tukeywin
creates a handle to a Tukey
window object for use in spectral analysis and FIR filtering by the
window method. Object methods enable workspace import and ASCII file
export of the window values.
The following equation defines the N–point Tukey window:
where x is a N–point
linearly spaced vector generated using linspace
.
The parameter α is the ratio of cosine-tapered section length
to the entire window length with 0 ≤α≤1.
For example, setting α=0.5 produces
a Tukey window where 1/2 of the entire window length consists of segments
of a phase-shifted cosine with period 2α=1.
If you specify α≤0,
an N-point rectangular window is returned. If you
specify α≥1,
a von Hann window (sigwin.hann
) is returned.
Construction
H = sigwin.tukeywin
returns a Tukey or
cosine-tapered window object H
of length 64 with Alpha
parameter
equal to 0.5.
H = sigwin.tukeywin(
returns
a Tukey window object Length
)H
of length Length
with Alpha
parameter
equal to 0.5. Length
requires a positive
integer. Entering a positive noninteger value for Length
rounds
the length to the nearest integer.
H = sigwin.tukeywin(
returns
a Tukey window object with the ratio of the tapered section length
to the entire window length Length
,Alpha
)Alpha
. Alpha
defaults
to 0.5. As Alpha
approaches zero, the Tukey
window approaches a rectangular window. As Alpha
approaches
one, the Tukey window approaches a Hann window.
Properties
|
Tukey window length. The window length must be a positive integer.
Entering a positive noninteger value for |
|
The ratio of tapered window section to constant section. As
a ratio, |
Methods
generate | Generates Tukey window |
info | Display information about Tukey window object |
winwrite | Save Tukey window in ASCII file |
Copy Semantics
Handle. To learn how copy semantics affect your use of the class, see Copying Objects in the MATLAB® Programming Fundamentals documentation.
Examples
References
[1] Bloomfield, P. Fourier Analysis of Time Series: An Introduction. New York: Wiley-Interscience, 2000.