We consider two types of Besov spaces on the Koch curve, defined by traces and with the help of the snowflaked transform. We compare these spaces and give their characterization in terms of Daubechies wavelets.

BACKGROUND Compressed sensing is a novel signal compression technique in which signal is compressed while sensing. The compressed signal is recovered with the only few numbers of observations compared to conventional Shannon-Nyquist sampling, and thus reduces the storage requirements. In this study, we have proposed the 1-D discrete wavelet transform (DWT) based sensing matrices for speech sign...

The paper formulates and proves a second order interpolation result for square-integrable functions by means of locally nite series of Daubechies' wavelets. Sample values of a suuciently smooth function can be used as coeecients of a wavelet expansion at a ne scale, and the corresponding wavelet interpolation function converges in Sobolev norms of rst order to the original function. This has ap...

In this paper, we present a method with a low complexity for analysing short and dynamic biomedical sequences. The method uses the Daubechies D4 wavelet in combination with similarity fitness schemes for retrieval. The method has been shown to outperform Fourier based methods in retrieving biomedical sequences of dynamic lengths, as well as the Haar wavelet.

We investigate three approaches to VLSI implementation of wavelet lters. The direct form structure, the lattice form structure, and an algebraic structure are used to derive diierent architectures for wavelet lters. The algebraic structure exploits conjugacy properties in number elds. All approaches are explained in detail for the Daubechies 4-tab lters. We outline the philosophy of a design me...

Recently, there has k e n a growing interest in investigating signal-adaptive multirate filter banks. I n this paper, we propose a direct method of constructing signal-adaptive orthogonal wavelet filter banks with better energy compaction performance than that of Daubechies wavelet filters of same length. 'The speed of this method is fast. so i t can be constructed in real time.

In this paper, we present two new methods for the Electroencephalography signal analysis and those are Discrete Wavelet Transform and Daubechies Wavelet Transform and their comparison is done as to find the better efficient signal analysis technique. And the signals are classified into seizure and non-seizure signals by applying neural network classifier which is easier to implement and more ef...

Audio fingerprinting is the process to obtain a compact content-based signature that summarizes the essence of an audio clip. In general, existing audio fingerprinting schemes based on wavelet transforms are not robust against large linear speed changes. The authors present a novel framework for contentbased audio retrieval based on the audio fingerprinting scheme that is robust against large l...