In this article, we investigate the application of wavelet packet transform as a novel spectrum sensing approach. The main attraction for wavelet packets is the tradeoffs they offer in terms of satisfying various performance metrics such as frequency resolution, variance of the estimated power spectral density (PSD) and complexity. The results of the experiments show that the wavelet based appr...

This article develops a wavelet decomposition of a stochastic process which parallels a time{localized Cram er (Fourier) spectral representation. We provide a time{scale instead of a time{frequency decomposition and, hence, instead of thinking as scale in terms of \inverse frequency" we start from genuine time{scale building blocks or \atoms". Using this class of locally stationary wavelet (LSW...

Data compression which can be lossy or lossless is required to decrease the storage requirement and better data transfer rate. One of the best image compression techniques is using wavelet transform. It is comparatively new and has many advantages over others. Wavelet transform uses a large variety of wavelets for decomposition of images. The state of the art coding techniques like EZW, SPIHT a...

In this paper, a novel reconfigurable discrete wavelet transform processor architecture is proposed to meet the diverse computing requirements of future generation multimedia SoC. The proposed architecture mainly consists of reconfigurable processing element array and reconfigurable address generator, featuring dynamically reconfigurable capability where the wavelet filters and wavelet decompos...

Wavelet-based signal processing has become commonplace in the signal processing community over the past decade.Wavelet analysis is often very effective because it provides a simple approach for dealing with local aspects of a signal. Electromyography (EMG) signals can be used for clinical/biomedical applications, Evolvable Hardware Chip (EHW) development, and modern human computer interaction. ...

Remote sensing imagery plays an important role in many fields. It has become an invaluable tool for diverse applications ranging from cartography to ecosystem management. In many of the images processed in these types of applications, semantic entities in the scene are correlated with textures in the image. In this paper, we propose a new method of analysing such textures based on adaptive prob...

The anisotropic wavelet packet transform is an extension of the conventional wavelet (packet) transform where the basis can have di erent scales in di erent dimensions. As there are certain kinds of images with di erent behaviour in horizontal and vertical direction, anisotropic wavelet packet bases can be adapted more precisely to these images. Zero-tree image compression has already proved it...

The design of filtration logic in wavelet transformation is been focused in this paper. The conventional wavelet transformation approaches are observed to be very effective in providing resolution information for each orientation. Though wavelets are been used as a prominent approach for image compression, the accuracy of the image processing is mainly depends on the filters used and their rela...

One of the most challenging tasks for which EMD could be useful is that of non-parametric signal denoising, an area in which wavelet thresholding has been the dominant technique for many years. In this paper, the major wavelet thresholding principle is used in the decomposition modes resulting from applying EMD to a signal. We show, that although a direct application of this principle in the EM...

A dynamically adaptive numerical method for solving multi-dimensional evolution problems with localized structures is developed. The method is based on the general class of multi-dimensional second-generation wavelets and is an extension of the second-generation wavelet collocation method of Vasilyev and Bowman to two and higher dimensions and irregular sampling intervals. Wavelet decomposition...