Abstract
The discrete prolate spheroidal (DPS) filter is one of the class of nonrecursive finite impulse response (FIR) filters. The DPS filter, first introduced by Tufts and Francis [1], is superior to other filters in this class in that it has maximum energy concentration in the frequency passband and minimum ringing in the time domain. Slepian [2] gives a complete discussion of DPS function properties. We give a mathematical development of the DPS filter properties, provide information required to easily and accurately construct even many coefficient filters, and compare the properties of this filter with those of the more commonly used filters of the same class. We note that use of the DPS filter allows for particularly useful statements of data time/frequency resolution “cell” values and that overall it forms an especially useful, though little known tool for digital signal processing.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 1471-1478 |
| Number of pages | 8 |
| Journal | IEEE Transactions on Acoustics, Speech, and Signal Processing |
| Volume | 33 |
| Issue number | 6 |
| DOIs | |
| State | Published - Jan 1 1985 |
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All Science Journal Classification (ASJC) codes
- Signal Processing
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The Discrete Prolate Spheroidal Filter as a Digital Signal Processing Tool. / Mathews, John David; Breakall, James Kenneth; Karawas, Georg K.
In: IEEE Transactions on Acoustics, Speech, and Signal Processing, Vol. 33, No. 6, 01.01.1985, p. 1471-1478.Research output: Contribution to journal › Article
TY - JOUR
T1 - The Discrete Prolate Spheroidal Filter as a Digital Signal Processing Tool
AU - Mathews, John David
AU - Breakall, James Kenneth
AU - Karawas, Georg K.
PY - 1985/1/1
Y1 - 1985/1/1
N2 - The discrete prolate spheroidal (DPS) filter is one of the class of nonrecursive finite impulse response (FIR) filters. The DPS filter, first introduced by Tufts and Francis [1], is superior to other filters in this class in that it has maximum energy concentration in the frequency passband and minimum ringing in the time domain. Slepian [2] gives a complete discussion of DPS function properties. We give a mathematical development of the DPS filter properties, provide information required to easily and accurately construct even many coefficient filters, and compare the properties of this filter with those of the more commonly used filters of the same class. We note that use of the DPS filter allows for particularly useful statements of data time/frequency resolution “cell” values and that overall it forms an especially useful, though little known tool for digital signal processing.
AB - The discrete prolate spheroidal (DPS) filter is one of the class of nonrecursive finite impulse response (FIR) filters. The DPS filter, first introduced by Tufts and Francis [1], is superior to other filters in this class in that it has maximum energy concentration in the frequency passband and minimum ringing in the time domain. Slepian [2] gives a complete discussion of DPS function properties. We give a mathematical development of the DPS filter properties, provide information required to easily and accurately construct even many coefficient filters, and compare the properties of this filter with those of the more commonly used filters of the same class. We note that use of the DPS filter allows for particularly useful statements of data time/frequency resolution “cell” values and that overall it forms an especially useful, though little known tool for digital signal processing.
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U2 - 10.1109/TASSP.1985.1164732
DO - 10.1109/TASSP.1985.1164732
M3 - Article
AN - SCOPUS:0022216475
VL - 33
SP - 1471
EP - 1478
JO - IEEE Transactions on Signal Processing
JF - IEEE Transactions on Signal Processing
SN - 1053-587X
IS - 6
ER -