Wavelet transforms for discrete-time periodic signals are developed. In this nite-dimensional context, key ideas from the continuous-time papers of Daubechies and of Cohen, Daubechies, and Feauveau are isolated to give a concise, rigorous derivation of the discrete-time periodic analogs of orthonormal and symmetric biorthogonal bases of compactly supported wavelets. These discrete-time periodic...

One-persistent backoff: Intuitively, the backoff delay of packets that fail by channel errors can be further optimised if the channel is sensed persistently after aborting transmission for the end of channel errors after which retransmission is initiated. For a fading channel, all users must thus be capable of end-of-fade detection, which in practice may be implemented through some form of rece...

A continuous wavelet transform, with Morlet wavelets as the basis functions, is used to map speech into the time-frequency domain. Forward and inverse FFT routines are used to implement the wavelet transforms. A coefficient covariance matrix is defined and an Eigenvalue decomposition is used to optimally determine significant wavelet based filters that accurately represent speech and potentiall...

a cochlear implant is an implanted electronic device used to provide a sensation of hearing to a person who is hard of hearing. the cochlear implant is often referred to as a bionic ear. this paper presents an undecimated wavelet‑based speech coding strategy for cochlear implants, which gives a novel speech processor. the undecimated wavelet packet transform (uwpt) is computed like the wavelet ...

The wavelet transform is a widely used time-frequency tool for signal processing. However, with some rare exceptions, its use in signal processing is limited to discrete-time critically sampled transforms, which are particular cases of subband coding. On the other hand, interest in continuous wavelet analyses has been repeatedly demonstrated in the literature. However, implementation challenges...

Analysis of circadian oscillations that exhibit variability in period or amplitude can be accomplished through wavelet transforms. Wavelet-based methods can also be used quite effectively to remove trend and noise from time series and to assess the strength of rhythms in different frequency bands, for example, ultradian versus circadian components in an activity record. In this article, we desc...