Filtro estimador por deconvolución a través de la inversa

This paper presents a deconvolution filter technique using a diagonal block inverse in order to learn the internal dynamics of a black-box model with bounded response and time-invariant evolution. Instead of using a pseudoinverse in deconvolution on problems of inversion and singularity, we propose a separation by matrix blocks and application of an inverse to achieve a lower algorithmic complexity and less error of direct estimation without losing the stability properties. With this in mind, we present a deconvolution filter applying its transformation into a diagonal form considering matrix diagonalization, diagonal filter description, functional error, algorithm complexity analysis, and diagonal deconvolution applied to filter simulation.