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Main-Lobe Bandwidth
We saw in the previous section that our ability to resolve two closely
spaced sinusoids is determined by the main-lobe width of the
window transform we are using. We will now study this relationship in
more detail.
For starters, let's define main-lobe width very simply (and
somewhat crudely) as the distance between the first
zero-crossings on either side of the main lobe, as shown in
Fig.1.16 for a rectangular-window transform. Let
denote this width in Hz. In normalized radian frequency units, as
used in the frequency axis of Fig.1.16,
Hz translates to
radians per sample, where
denotes the sampling rate in Hz.
Figure 1.16:
Window transform with main lobe width marked.
 |
For the length-
unit-amplitude rectangular window defined in
§1.5, the DTFT is given analytically by
 |
(2.7) |
where

is frequency in Hz, and

is the
sampling interval in
seconds (

). The main lobe of the rectangular-window
transform is thus ``two sidelobes wide,'' or
as can be seen in Fig.
1.16.
Recall from §1.5.1 that the side-lobe width in a
rectangular-window transform (
Hz) is given in radians
per sample by
As Fig.
1.16 illustrates, the rectangular-window transform
main-lobe width is

radians per sample (two side-lobe
widths). Table
1.1 lists the main-lobe widths for a
variety of window types (which are defined and discussed further in
Chapter
3).
Table 1.1:
Main-lobe bandwidth for various windows.
| Window Type |
Main-Lobe Width (rad/sample) |
| Rectangular |
 |
| Hamming |
 |
| Hann |
 |
| Generalized Hamming |
 |
| Blackman |
 |
-term Blackman-Harris |
 |
| Kaiser |
depends on  |
| Chebyshev |
depends on ripple spec |
|
Subsections
Previous:
One Sine and One Cosine ``Phase Quadrature'' CaseNext:
Other Definitions of Main Lobe Width
written by Julius Orion Smith III
Julius Smith's background is in electrical engineering (BS Rice 1975, PhD Stanford 1983). He is presently Professor of Music and Associate Professor (by courtesy) of Electrical Engineering at
Stanford's Center for Computer Research in Music and Acoustics (CCRMA), teaching courses and pursuing research related to signal processing applied to music and audio systems. See
http://ccrma.stanford.edu/~jos/ for details.