Least-Squares and Minimax Design of Polynomial Impulse Response FIR Filters for Reconstruction of Two-Periodic Nonuniformly Sampled Signals

This paper proposes polynomial impulse response finite-impulse response filters for reconstruction of two-periodic nonuniformly sampled signals. The foremost advantages of using these reconstruction filters are that on-line filter design thereby is avoided and subfilters with fixed dedicated multipl...

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Bibliographic Details
Published in:IEEE transactions on circuits and systems. 1, Fundamental theory and applications Fundamental theory and applications, 2007-04, Vol.54 (4), p.877-888
Main Authors: Johansson, H., Lowenborg, P., Vengattaramane, K.
Format: Article
Language:English
Subjects:
Analog-digital conversion
Circuits
Costs
Design engineering
Finite impulse response filter
Finite-impulse response (FIR) filters
Impulse response
Least squares method
least-squares design
minimax design
Minimax technique
Minimax techniques
Nonuniform sampling
On-line systems
Optimization
periodic nonuniform sampling
Polynomials
Reconstruction
reconstruction filters
Sampling
Sampling methods
Signal design
TECHNOLOGY
TEKNIKVETENSKAP
time-interleaved analog-to-digital converters (TIADCs)
Transfer functions
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Summary:This paper proposes polynomial impulse response finite-impulse response filters for reconstruction of two-periodic nonuniformly sampled signals. The foremost advantages of using these reconstruction filters are that on-line filter design thereby is avoided and subfilters with fixed dedicated multipliers can be employed in an implementation. The overall implementation cost can in this way be reduced substantially in applications where the sampling pattern changes from time to time. The paper presents two different design techniques that yield optimum filters in the least-squares and minimax senses, respectively. Design examples are included that illustrate the benefits of the proposed filters
ISSN:1549-8328
1057-7122
1558-1268
1558-0806
DOI:10.1109/TCSI.2006.888765