Detail publikace

# Algorithms for Segmentwise Computation of Forward and Inverse Discrete-time Wavelet Transform

Originální název

Algorithms for Segmentwise Computation of Forward and Inverse Discrete-time Wavelet Transform

Anglický název

Algorithms for Segmentwise Computation of Forward and Inverse Discrete-time Wavelet Transform

Jazyk

en

Originální abstrakt

The paper describes a method of segmented wavelet transform (SegWT) that makes it possible to compute the discrete-time wavelet transform of a signal segment-by-segment, with exactly the same result as if the whole signal were transformed at once. Due to its generality, the method can be utilized in many situations: for wavelet-type processing of a signal in real time or in case we want to process the signal in parallel or in case we need to process a long signal, but the available memory capacity is insufficient (e.g. in the DSPs). In the paper, the background theory and the emerging principles of both the forward and the inverse SegWT are explained.

Anglický abstrakt

The paper describes a method of segmented wavelet transform (SegWT) that makes it possible to compute the discrete-time wavelet transform of a signal segment-by-segment, with exactly the same result as if the whole signal were transformed at once. Due to its generality, the method can be utilized in many situations: for wavelet-type processing of a signal in real time or in case we want to process the signal in parallel or in case we need to process a long signal, but the available memory capacity is insufficient (e.g. in the DSPs). In the paper, the background theory and the emerging principles of both the forward and the inverse SegWT are explained.

Dokumenty

BibTex

``````
@article{BUT46907,
author="Pavel {Rajmic}",
title="Algorithms for Segmentwise Computation of Forward and Inverse Discrete-time Wavelet Transform",
annote="The paper describes a method of segmented wavelet transform (SegWT) that makes it possible to compute the discrete-time wavelet transform of a signal segment-by-segment, with exactly the same result as if the whole
signal were transformed at once. Due to its generality, the method can be utilized in many situations: for wavelet-type processing of a signal in real time or in case we want to process the signal in parallel or in case
we need to process a long signal, but the available memory capacity is insufficient (e.g. in the DSPs). In the paper, the background theory and the emerging principles of both the forward and the inverse SegWT are explained.",