On inference of network time constants from impulse response data: Graph-theoretic Cramer-Rao bounds

Abstract:

We examine the role played by a linear dynamical network's topology in inference of its eigenvalues from noisy impulse-response data. Specifically, for a canonical linear timeinvariant network dynamics, we relate the Cramer-Rao bounds on eigenvalue estimator performance (from impulse-response data) to structural properties of the transfer function, and in turn to the network's topological structure. We focus especially on networks with a slow-coherence structure, in which case we find that stimulus and observation in each strongly-connected network component is needed for high-fidelity estimation. ©2009 IEEE.

Año de publicación:

2009

Keywords:

Fuente:

scopus