Multivariate refinement equations and convergence of subdivision schemes
SIAM Journal on Mathematical Analysis
Analysis and construction of optimal multivariate biorthogonal wavelets with compact support
SIAM Journal on Mathematical Analysis
Approximation properties and construction of Hermite interpolants and biorthogonal mutliwavelets
Journal of Approximation Theory
Vector cascade algorithms and refinable function vectors in Sobolev spaces
Journal of Approximation Theory
Interpolatory orthogonal multiwavelets and refinable functions
IEEE Transactions on Signal Processing
Interpolating multiwavelet bases and the sampling theorem
IEEE Transactions on Signal Processing
Journal of Approximation Theory
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Interpolating scalar refinable functions with compact support are of interest in several applications such as sampling theory, signal processing, computer graphics, and numerical algorithms. In this paper, we shall generalize the notion of interpolating scalar refinable functions to compactly supported interpolating d-refinable function vectors with any multiplicity r and dilation factor d. More precisely, we are interested in a d-refinable function vector @f=[@f"1,...,@f"r]^T such that @f is an rx1 column vector of compactly supported continuous functions with the following interpolation property @f"@?(mr+k)=@d"k@d"@?"-"1"-"m,@?k@?Z,m=0,...,r-1,@?=1,...,r, where @d"0=1 and @d"k=0 for k0. Now for any function f:R@?C, the function f can be interpolated and approximated by f@?=@?@?=1r@?k@?Zf(@?-1r+k)@f"@?(@?-k)=@?k@?Z[f(k),f(1r+k),...,f(r-1r+k)]@f(@?-k). Since @f is interpolating, f@?(k/r)=f(k/r) for all k@?Z, that is, f@? agrees with f on r^-^1Z. Moreover, for r=2 or d2, such interpolating refinable function vectors can have the additional orthogonality property: =r^-^1@d"@?"-"@?"^"'@d"k"-"k"^"' for all k,k^'@?Z and 1=