We present some greedy learning algorithms for building sparse nonlinear regression and
classification models from observational data using Mercer kernels. Our objective is to …

In this paper, we provide an essentially complete answer to the question of minimal initial
data required to solve an overdetermined system of linear partial difference equations with …

In this article we investigate a Lyapunov approach to the stability of finite-dimensional 2D
systems. We use the behavioural framework and consider a notion of stability following the …

In this paper, we show that every discrete 2D autonomous system, that is described by a set
of linear partial difference equations with constant real coefficients, admits a finite union of …

In this paper we study finite support convolutional codes over Z pr by means of an input-state-
output representation. We show that the set of finite weight input-state-output trajectories …

The aim of this contribution is to characterize the set of feasible initial conditions on a
diagonal line in order to compute the solutions of a 2D discrete state-space system (defined …

This paper calculates the degree of autonomy of a generic autonomous nD system defined
by the kernel of a partial difference operator. The calculation implies that attaching a generic …

An important question for multidimensional systems is to characterize the minimum
information required to uniquely specify a 'trajectory'. For a discrete nD system described by …

In this paper, we look into restrictions of the solution set of a system of PDEs to 1-d
subspaces. We bring out its relation with certain intersection modules. We show that the …

The issue of initial/boundary conditions for a general system of partial difference equations
(PDEs)—called a discrete-D system—is resolved through the notion of characteristic sets …