The aim of this study is to design a non-parametric identifier for homogeneous systems based on class artificial neural networks with continuous dynamics. identification algorithm developed input-affine uncertain gains and diverse degrees homogeneity. One the main contributions extension universal approximation property systems. Another contribution development differential novel concept networ...

Floyd gave an example of a minimal dynamical system which was extension odometer and the fibres associated factor map were either singletons or intervals. Gjerde Johansen showed that could be replaced by any Cantor system. Here, we show further intervals can generalized to cubes arbitrary dimension attractors certain iterated function systems. We discuss applications.

We investigate non-homogeneous Hamiltonian operators composed of a first order Dubrovin–Novikov operator and an ultralocal one. The study such turns out to be fundamental for the inverted system equations associated with class scalar equations. Often, involved are degenerate in term. For this reason, complete classification leading coefficient systems two three components is presented.