This paper investigates the mathematical framework of multiresolution analysis based on irregularly spaced knots sequence. Our presentation is based on the construction of nested nonuniform spline multiresolution spaces. From these spaces, we present the construction of orthonormal scaling and wavelet basis functions on bounded intervals. For any arbitrary degree of the spline function, we prov...

A novel method for learning optimal, orthonormal wavelet bases for representing 1and 2D signals, based on parallels between the wavelet transform and fully connected artificial neural networks, is described. The structural similarities between these two concepts are reviewed and combined to a “wavenet”, allowing for the direct learning of optimal wavelet filter coefficient through stochastic gr...

Numerical algorithms using wavelet bases are similar to other transform methods in that vectors and operators are expanded into a basis and the computations take place in the new system of coordinates. As in all transform methods, such approach seeks an advantage in that the computation is faster in the new system of coordinates than in the original domain. However, due to the recursive definit...

This paper presents an algebraic approach to construct Mband orthogonal wavelet bases. A system of constraint equations is obtained for M-band orthonormal filters, and then a solution based on SVD (Singular Value Decomposition) is developed to enable us to produce innumerable wavelet bases of given length. Also the property of 2 vanishing moments is integrated into our wavelet construction proc...

Principal angles between subspaces (PABS) (also called canonical angles) serve as a classical tool in mathematics, statistics, and applications, e.g., data mining. Traditionally, PABS are introduced via their cosines. The cosines and sines of PABS are commonly defined using the singular value decomposition. We utilize the same idea for the tangents, i.e., explicitly construct matrices, such tha...

In the first part of this paper we construct an algorithm for implementing the discrete wavelet transform by means of matrices in SO2(R) for orthonormal compactly supported wavelets and matrices in SLm(R),m ≥ 2, for compactly supported biorthogonal wavelets. We show that in 1 dimension the total operation count using this algorithm can be reduced to about 50% of the conventional convolution and...

There has recently been interest in the use of orthonor-mal bases for the purposes of SISO system identiication. Concurrently, but separately, there has also been vigorous work on estimation of MIMO systems by computa-tionally cheap and reliable schemes. These latter ideas have collectively become known as`4SID' methods. This paper is a contribution overlapping these two schools of thought by s...

The purpose of this paper is to generalize a result byDonoho, Huo, Elad and Bruckstein on sparse representations of signals/images in a union of two orthonormal bases. We consider general (redundant) dictionaries in finite dimension, and derive sufficient conditions on a signal/image for having a unique sparse representation in such a dictionary. In particular, it is proved that the result of D...

We introduce a sparse image representation that takes advantage of the geometrical regularity of edges in images. A new class of one-dimensional wavelet orthonormal bases, called foveal wavelets, are introduced to detect and reconstruct singularities. Foveal wavelets are extended in two dimensions, to follow the geometry of arbitrary curves. The resulting two dimensional “bandelets” define orth...

We consider sparse representations of signals from redundant dictionaries which are unions several orthonormal bases. The spark introduced by Donoho and Elad plays an important role in representations. However, numerical computations sparks generally combinatorial. For bases, two lower bounds on the via mutual coherence were established previous work. constructively prove that both them tight. ...