In most north temperate lakes, phytoplankton biomass oscillates on an annual scale. While phytoplankton seasonal succession within a year has been described for many lakes, much less is known about variability in seasonal succession over multiple years. Here, we describe how continuous wavelet transforms can be used to identify variation in the periodicity in phytoplankton time series at multip...

Wavelet transforms and other multi-scale analysis functions have been used for compact signal and image representations in de-noising, compression and feature detection processing problems for about twenty years. Numerous research works have proven that space-frequency and spacescale expansions with this family of analysis functions provided a very efficient framework for signal or image data. ...

We investigate the reconstruction of embedded time-series from chaotic dynamical systems using wavelets. The standard wavelet transforms are not applicable because of the embedding, and we use a basis pursuit method which on its own does not perform very well. When this is combined with a continuous optimizer, however, we obtain very good models. We discuss the success of this method and apply ...

BACKGROUND One of the most important limitations of standard pulse oximeters is the inability to detect changes in respiratory rate until oxygenation is affected. This study sought to determine if analysis of the plethysmogram by wavelet transforms would enable the determination of changes in respiratory rate at an earlier stage. METHODS Ten healthy adult volunteers were monitored, breathing ...

This paper presents a computer based manipulating and analyzing a digital images. The proposed method is used wavelet transform, this transformation arrange orthogonal series of both imaginary and real values. In this paper we are proposes a two algorithms one is dual tree complex wavelet transforms (DTCWT), and second one is dual tree complex wavelet transform with orthogonal shift property th...

This work explores the use of a discrete wavelet transform, a feature extractor mechanism for speech recognition. Speech recognition is a fascinating application of digital signal processing offering unparalleled opportunities. The real-world applications deploying speech recognition and its implications can be varied across various fields. Speech recognition can automate many tasks that previo...

In a series of papers, Donoho and Johnstone develop a powerful theory based on wavelets for extracting nonsmooth signals from noisy data. Several nonlinear smoothing algorithms are presented which provide high performance for removing Gaussian noise from a wide range of spatially inhomogeneous signals. However, like other methods based on the linear wavelet transform, these algorithms are very ...

This paper continues the development of a new framework for the construction of motion compensated wavelet transforms for highly scalable video compression. The current authors recently proposed a motion adaptive wavelet transform based on motioncompensated lifting steps. This approach overcomes several limitations of existing methods. In particular, frame warping and block displacement methods...

Recently, images and video are being extensively used in numerous areas such as video-conferencing, multimedia documentation, telemedicine, high definition television (HDTV) etc. These diverse applications can benefit from the design of a family of image compression algorithms that address their specific needs. We propose a framework for wavelet-based image compression that leads to a family of...

Pre-processing of speech signals is considered a crucial step in the development of a robust and efficient speech or speaker recognition system. This paper deals with different speech processing techniques and the recognition accuracy with respect to wavelet transforms. It is shown that by applying wavelet transform to the conventional methods the signal recognition accuracy will be increased b...