Publication

Perfect reconstruction FIR filter banks: some properties and factorizations

Martin Vetterli
1989
Journal Articles

Abstract

Perfect reconstruction finite impulse-response (FIR) filter banks are analyzed both in the z-transform and time domains, showing the alternatives between designs in the two domains. Various classes of perfect reconstruction schemes are indicated, and relations between previously known systems are given. Windowed modulated filter banks with low computational complexity and perfect reconstruction are shown. New factorizations of polyphase filter matrices leading in particular to linear-phase filters, are given. The computational complexity and the architecture of the new structures are indicated

Official source

https://infoscience.epfl.ch/entities/publication/29ce0e7a-33b6-4849-8edb-53570311f0b1

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Martin Vetterli
1989
Journal Articles

Abstract

Official source

https://infoscience.epfl.ch/entities/publication/29ce0e7a-33b6-4849-8edb-53570311f0b1

About this result

Related concepts (32)

Filter bank

In signal processing, a filter bank (or filterbank) is an array of bandpass filters that separates the input signal into multiple components, each one carrying a single frequency sub-band of the original signal. One application of a filter bank is a graphic equalizer, which can attenuate the components differently and recombine them into a modified version of the original signal.

Computational complexity

In computer science, the computational complexity or simply complexity of an algorithm is the amount of resources required to run it. Particular focus is given to computation time (generally measured by the number of needed elementary operations) and memory storage requirements. The complexity of a problem is the complexity of the best algorithms that allow solving the problem. The study of the complexity of explicitly given algorithms is called analysis of algorithms, while the study of the complexity of problems is called computational complexity theory.

Linear filter

Linear filters process time-varying input signals to produce output signals, subject to the constraint of linearity. In most cases these linear filters are also time invariant (or shift invariant) in which case they can be analyzed exactly using LTI ("linear time-invariant") system theory revealing their transfer functions in the frequency domain and their impulse responses in the time domain. Real-time implementations of such linear signal processing filters in the time domain are inevitably causal, an additional constraint on their transfer functions.

Related publications (32)

Perfect reconstruction FIR filter banks: some properties and factorizations

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