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| [[Image:KaiserWindow.jpg|right]]
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| The '''Kaiser window''', also known as the '''Kaiser-Bessel window''', was developed by James Kaiser at [[Bell Laboratories]]. It is a one-parameter family of [[window function]]s used for [[digital signal processing]], and is defined by the formula
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| ,<ref name="f.harris">
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| {{cite journal
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| | doi = 10.1109/PROC.1978.10837
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| | last = Harris
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| | first = Fredric j.
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| | coauthors =
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| | title = On the use of Windows for Harmonic Analysis with the Discrete Fourier Transform
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| | journal = Proceedings of the IEEE
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| | volume = 66
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| | issue = 1
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| | pages = 73–74
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| |date=Jan 1978
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| | url=http://web.mit.edu/xiphmont/Public/windows.pdf}} Article on FFT windows which introduced many of the key metrics used to compare windows.</ref><ref>{{cite journal|last=Kaiser|first=James F.|coauthors=Ronald W. Schafer|title=On the Use of the I0-Sinh Window for Spectrum Analysis|journal=IEEE Transactions on Acoustics, Speech and Signal Processing|date=February 1980|volume=ASSP-28|issue=1|pages=105–107}}</ref>''':'''
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| :<math>
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| w[n] =
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| \left\{
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| \begin{matrix}
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| \frac{I_0\left(\pi \alpha \sqrt{1 - \left(\frac{2n}{N-1}-1\right)^2}\right)} {I_0(\pi \alpha)},
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| & 0 \leq n \leq N-1 \\ \\ | |
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| 0 & \mbox{otherwise}, \\
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| \end{matrix}
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| \right.
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| </math>
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| where:
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| * ''N'' is the length of the sequence.
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| * ''I''<sub>0</sub> is the zeroth order [[Modified Bessel function]] of the first kind.
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| * ''α'' is an arbitrary, non-negative real number that determines the shape of the window. In the frequency domain, it determines the trade-off between main-lobe width and side lobe level, which is a central decision in window design.
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| When ''N'' is an odd number, the peak value of the window is <math>\scriptstyle w[(N-1)/2] = 1,</math> and when ''N'' is even, the peak values are <math>\scriptstyle w[N/2-1]\ =\ w[N/2]\ <\ 1.</math>
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| ==Fourier transform==
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| Underlying the discrete sequence is this continuous-time function and its Fourier transform''':'''
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| :<math>\underbrace{\frac{I_0\left(\pi \alpha \sqrt{1 - \left(\frac{2t}{(N-1)T}\right)^2}\right)} {I_0(\pi \alpha)}}_{w_0(t)}
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| \quad \stackrel{\mathcal{F}}{\Longleftrightarrow}\quad
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| \underbrace{\frac{(N-1)T\cdot\sinh\left(\pi \sqrt{\alpha^2-\left((N-1)T\cdot f\right)^2}\right)}{I_0(\pi \alpha)\cdot\pi \sqrt{\alpha^2-\left((N-1)T\cdot f\right)^2}}}_{W_0(f)}.
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| </math>
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| [[Image:Kaiser-Window-Spectra.jpg|right|thumb|452px|Fourier transforms of Kaiser windows for typical values of parameter α]]
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| The maximum value of ''w''<sub>''0''</sub>(''t'') is ''w''<sub>''0''</sub>(0) = 1. The ''w''[n] sequence defined above are the samples of''':'''
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| :<math>w_0\left(t-\tfrac{(N-1)T}{2}\right)\cdot \operatorname{rect}\left(\tfrac{t-(N-1)T/2}{NT}\right),</math> sampled at intervals of '''T''',
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| and where rect() is the [[rectangle function]]. The first null after the main lobe of ''W''<sub>''0''</sub>(''f'') occurs at''':'''
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| :<math>f = \frac{\sqrt{1+\alpha^2}}{NT},</math> which in units of DFT bins is just <math>\scriptstyle \sqrt{1+\alpha^2}.</math><ref>{{cite doi|10.1109/TASSP.1980.1163349}}</ref> | |
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| ''α'' controls the tradeoff between main-lobe width and side-lobe area. As ''α'' increases, the main lobe of ''W''<sub>''0''</sub>(''f'') increases in width, and the side lobes decrease in amplitude, as illustrated in the figure at right. ''α'' = 0 corresponds to a rectangular window. For large ''α'', the shape of the Kaiser window (in both time and frequency domain) tends to a [[Gaussian function|Gaussian]] curve. The Kaiser window is nearly optimal in the sense of its peak's concentration around frequency ''0'' (Oppenheim ''et al.'', 1999).
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| ==Kaiser-Bessel derived (KBD) window==
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| [[File:Kbd-window.jpg|right]]
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| A related window function is the '''Kaiser-Bessel derived (KBD)''' window, which is designed to be suitable for use with the [[modified discrete cosine transform]] (MDCT). The KBD window function is defined in terms of the Kaiser window of length ''M''+1, by the formula''':'''
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| :<math>
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| d_n =
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| \left\{\begin{matrix}
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| \sqrt{\frac{\sum_{i=0}^{n} w[i]} {\sum_{i=0}^M w[i]}}
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| & \mbox{if } 0 \leq n < M \\ \\
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| \sqrt{\frac{\sum_{i=0}^{2M-1-n} w[i]} {\sum_{i=0}^M w[i]}}
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| & \mbox{if } M \leq n < 2M \\ \\
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| 0 & \mbox{otherwise}. \\
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| \end{matrix}
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| \right.
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| </math>
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| This defines a window of length 2''M'', where by construction ''d''<sub>''n''</sub> satisfies the Princen-Bradley condition for the MDCT (using the fact that ''w''<sub>''M''−''n''</sub> = ''w''<sub>''n''</sub>): ''d''<sub>''n''</sub><sup>2</sup> + ''d''<sub>''n'' + ''M''</sub><sup>2</sup> = 1 (interpreting ''n'' and ''n'' + ''M'' [[modular arithmetic|modulo]] 2''M''). The KBD window is also symmetric in the proper manner for the MDCT: ''d''<sub>''n''</sub> = ''d''<sub>2''M''−1−''n''</sub>.
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| ===Applications===
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| The KBD window is used in the [[Advanced Audio Coding]] digital audio format.
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| ==Notes==
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| <references />
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| ==References==
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| * {{cite book | author=Oppenheim, A. V.; Schafer, R. W.; and Buck J. R. | title=Discrete-time signal processing | location=Upper Saddle River, N.J. | publisher=Prentice Hall | year=1999 | isbn=0-13-754920-2}}
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| * Kaiser, J. F. (1966). Digital Filters. In Kuo, F. F. and Kaiser, J. F. (Eds.), ''System Analysis by Digital Computer'', chap. 7. New York, Wiley.
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| * Craig Sapp, [http://ccrma.stanford.edu/courses/422/projects/kbd/ Kaiser-Bessel Derived Window Examples and C-language Implementation], ''Music 422 / EE 367C: Perceptual Audio Coding'' (Stanford University course page, 2001).
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| ==External links==
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| [[Category:Signal processing]]
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