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Function approximation of Seidel aberrations by a neural network

Rossella Cancelliere, Mario Gai (2004)

Bollettino dell'Unione Matematica Italiana

This paper deals with the possibility of using a feedforward neural network to test the discrepancies between a real astronomical image and a predefined template. This task can be accomplished thanks to the capability of neural networks to solve a nonlinear approximation problem, i.e. to construct an hypersurface that approximates a given set of scattered data couples. Images are encoded associating each of them with some conveniently chosen statistical moments, evaluated along the x , y axes; in this...

General Haar systems and greedy approximation

Anna Kamont (2001)

Studia Mathematica

We show that each general Haar system is permutatively equivalent in L p ( [ 0 , 1 ] ) , 1 < p < ∞, to a subsequence of the classical (i.e. dyadic) Haar system. As a consequence, each general Haar system is a greedy basis in L p ( [ 0 , 1 ] ) , 1 < p < ∞. In addition, we give an example of a general Haar system whose tensor products are greedy bases in each L p ( [ 0 , 1 ] d ) , 1 < p < ∞, d ∈ ℕ. This is in contrast to [11], where it has been shown that the tensor products of the dyadic Haar system are not greedy bases in L p ( [ 0 , 1 ] d ) for 1...

Linear combinations of partitions of unity with restricted supports

Christian Richter (2002)

Studia Mathematica

Given a locally finite open covering of a normal space X and a Hausdorff topological vector space E, we characterize all continuous functions f: X → E which admit a representation f = C a C φ C with a C E and a partition of unity φ C : C subordinate to . As an application, we determine the class of all functions f ∈ C(||) on the underlying space || of a Euclidean complex such that, for each polytope P ∈ , the restriction f | P attains its extrema at vertices of P. Finally, a class of extremal functions on the metric space...

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