Piecewise linear approximations of multivariate functions: A multiresolution-based compression algorithm suitable for circuit implementation

This paper is concerned with a multiresolution approach to the piecewise-linear approximation of multivariate nonlinear continuous functions. The proposed technique has no restrictions on the number of variables the functions depend on, and is based on the use of piecewise-linear "hat" functions. The approximation levels are related to nested function spaces. The multiresolution approach allows one to define a simple model reduction strategy that is based on a proper error definition. The interest in the piecewise-linear approximations and in the hat functions is motivated by the simplicity of their circuit implementations. The efficiency of the method is tested via two benchmark examples, one of which concerns the approximation of the vector field of a nonlinear dynamical system.