Spectral analysis based on neural field theory is used to analyze dynamic connectivity via
methods based on the physical eigenmodes that are the building blocks of brain dynamics …

In this paper, we enhance a recent algorithm for approximate spectral factorization of matrix
functions, extending its capabilities to precisely factorize rational matrices when an exact …

It is shown how the brain's linear transfer function provides a means to systematically
analyze brain connectivity and dynamics, and to infer connectivity, eigenmodes, and activity …

Janashia–Lagvilava algorithm is a relatively new method of matrix spectral factorization. In
our previous publications on this topic, we demonstrated that the algorithm is capable to …

The power-law exponents of observed size and lifetime distributions of near-critical neural
avalanches are calculated from neural field theory using diagrammatic methods. This brings …

Spectral factorization is a prominent tool with several important applications in various areas
of applied science. Wiener and Masani proved the existence of matrix spectral factorization …

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In this paper, we extend the basic idea of the Janashia–Lagvilava algorithm to adapt it for
the spectral factorization of positive-definite polynomial matrices on the real line. This …

Bump attractors are wandering localized patterns observed in in vivo experiments of
spatially extended neurobiological networks. They are important for the brain's navigational …

We propose a superfast method for constructing orthogonal matrices MEO (n, q) in finite
fields GF (q). It can be used to construct n× n orthogonal matrices in Z, with very high values …