In this paper, which is the sequel to [16], we study inverse estimates of the Bernstein type for nonlinear approximation with structured redundant dictionaries in a Banach space. The main results are for blockwise incoherent dictionaries in Hilbert spaces, which generalize the notion of joint block-diagonal mutually incoherent bases introduced by Donoho and Huo. The Bernstein inequality obtained for such dictionaries is proved to be sharp, but it has an exponent that does not match that of the corresponding Jackson inequality. Udgivelsesdato: SEPIn this paper, which is the sequel to [16], we study inverse estimates of the Bernstein type for nonlinear approximation with structured redundant dictionaries in a Banach space. The main results ar...
We study nonlinear approximation in the Triebel-Lizorkin spaces with dictionaries formed by dilating...
AbstractWe study the efficiency of greedy type algorithms with regard to redundant dictionaries in H...
In this paper we study nonlinear approximation and data representation with redundant function dicti...
In this paper we study inverse estimates of the Bernstein type for nonlinear approximation with stru...
International audienceIn this paper, which is the sequel to [R. Gribonval and M. Nielsen. Nonlinear ...
ABSTRACT. We study various approximation classes associated with m-term approximation by elements fr...
We study various approximation classes associated with m-term approximation by elements from a (poss...
We study various approximation classes associated with $m$-term approximation by elements from a (po...
International audienceWe study various approximation classes associated with m-term approximation by...
We study nonlinear m-term approximation with regard to a redundant dictionary D in a Banach space. I...
International audienceIt is now well known that sparse or compressible vectors can be stably recover...
AbstractIt is now well known that sparse or compressible vectors can be stably recovered from their ...
AbstractWe study nonlinear m-term approximation with regard to a redundant dictionary D in a Banach ...
AbstractWe study the efficiency of greedy algorithms with regard to redundant dictionaries in Hilber...
International audienceTen years ago, Mallat and Zhang proposed the Matching Pursuit algorithm : sinc...
We study nonlinear approximation in the Triebel-Lizorkin spaces with dictionaries formed by dilating...
AbstractWe study the efficiency of greedy type algorithms with regard to redundant dictionaries in H...
In this paper we study nonlinear approximation and data representation with redundant function dicti...
In this paper we study inverse estimates of the Bernstein type for nonlinear approximation with stru...
International audienceIn this paper, which is the sequel to [R. Gribonval and M. Nielsen. Nonlinear ...
ABSTRACT. We study various approximation classes associated with m-term approximation by elements fr...
We study various approximation classes associated with m-term approximation by elements from a (poss...
We study various approximation classes associated with $m$-term approximation by elements from a (po...
International audienceWe study various approximation classes associated with m-term approximation by...
We study nonlinear m-term approximation with regard to a redundant dictionary D in a Banach space. I...
International audienceIt is now well known that sparse or compressible vectors can be stably recover...
AbstractIt is now well known that sparse or compressible vectors can be stably recovered from their ...
AbstractWe study nonlinear m-term approximation with regard to a redundant dictionary D in a Banach ...
AbstractWe study the efficiency of greedy algorithms with regard to redundant dictionaries in Hilber...
International audienceTen years ago, Mallat and Zhang proposed the Matching Pursuit algorithm : sinc...
We study nonlinear approximation in the Triebel-Lizorkin spaces with dictionaries formed by dilating...
AbstractWe study the efficiency of greedy type algorithms with regard to redundant dictionaries in H...
In this paper we study nonlinear approximation and data representation with redundant function dicti...