A new objective function for neural net classifier design is presented, which has more free parameters than the classical objective function. An iterative minimization technique f...
Jiang Li, Michael T. Manry, Li-min Liu, Changhua Y...
We develop new algorithms for designing matched wavelets and matched scaling functions using a new parametrization of compactly supported orthonormal wavelets that is developed in...
Abstract. Viewing discrete-time causal linear systems as (Mealy) coalgebras, we describe their semantics, minimization and realisation as universal constructions, based on the fin...
In this paper, the problem of an optimal transformation of the input space for function approximation problems is addressed. The transformation is defined determining the Mahalanob...
Amaury Lendasse, Francesco Corona, Jin Hao, Nima R...
Several optimization problems require finding a permutation of a given set of items that minimizes a certain cost function. These problems are naturally modelled in graph-theory t...
Livio Bertacco, Lorenzo Brunetta, Matteo Fischetti