As the internet search evolves toward multimedia content based search, audio content identification and retrieval will likely become one of the key components of next generation internet search machines. In this paper we develop and evaluate a methodology for the identification (classification) of unknown highly complex audio pieces from within the same genre (classical music). Our methodology ...

Orthonormal wavelet expansions are applied to atmospheric surface layer velocity and temperature measurements above a uniform bare soil ‘surface that exhibit a long inertial subrange energy spectrum. In order to investigate intermittency effects on Kolmogorov’s theory, a direct relation between the &h-order structure function and the wavelet coefficients is derived. This relation is used to exa...

Speech compression is an area of digital processing that is focusing on reducing bit rate of the speech signal for transmission or storage without significant loss of quality. The focus of this paper is to compress the digital speech using wavelet transform. The uncompressed digital speech requires huge amount of memory. The main idea behind the speech compression algorithm is to represent this...

We apply Renormalization Group (RG) techniques to Classical Information Theory, in the limit of large codeword size n. In particular, we apply RG techniques to (1) noiseless coding (i.e., a coding used for compression) and (2) noisy coding (i.e., a coding used for channel transmission). Shannon’s “first” and “second” theorems refer to (1) and (2), respectively. Our RG technique uses composition...

Purpose of this study — analysis the possibility using convolutional neural networks as a model for detecting epileptic seizures on real EEG data Methods. In paper, wavelet is used time-frequency analysis. To localize discharges, task them was reduced to classification and ResNet18 architecture network used. Techniques were augment balance biomedical dataset under consideration. Wavelet problem...

Wavelet analysis has been found to be a powerful tool for the nonparametric estimation of spatially-variable objects. We discuss in detail wavelet methods in nonparametric regression, where the data are modelled as observations of a signal contaminated with additive Gaussian noise, and provide an extensive review of the vast literature of wavelet shrinkage and wavelet thresholding estimators de...

The motivation for this work is a recently constructed family of generators of shift-invariant spaces with certain optimal approximation properties, but which are not refinable in the classical sense. We try to see whether, once the classical refinability requirement is removed, it is still possible to construct meaningful wavelet decompositions of dilates of the shift invariant space that are ...

We study the quantum group gauge theory developed elsewhere in the limit when the base space (spacetime) is a classical space rather than a general quantum space. We show that this limit of the theory for gauge quantum group Uq(g) is isomorphic to usual gauge theory with Lie algebra g. Thus a new kind of gauge theory is not obtained in this way, although we do find some differences in the coupl...

The bas ic principles of the group properti es of physical quantities are reviewed. The proble ms assoc iated with th e dimensions of angle and logarithm are solved by using functional equations, ins tead of a nalytic express ions , for de fining functions of non numerical quantities. It is concluded that the neper and radian are related by Np= j rad , so that when the radian is considered as a...

We examine the applicability of group testing to wavelet-based image compression. We first review some recent image compression techniques and explain the group testing framework. We then explain how group testing already has been applied in image compression. In particular, we show that group testing is a generalization of the zerotree coding technique, and that Hwang’s group testing algorithm...