Motivated by the fact that transfer functions do not contain structural information about networks (dependency of state variables), dynamical structure functions were introduced to capture causal relationships between measured nodes in networks. From the dynamical structure functions, (a) we show that the actual number of hidden states can be larger than the number of hidden states estimated from the corresponding transfer function; (b) we can obtain partial information about the true state-space equation, which cannot in general be obtained from the transfer function. Based on these properties, this paper proposes algorithms to find minimal realisations for a given dynamical structure function. This helps to estimate the minimal number of ...
Abstract — Network reconstruction, i.e. obtaining network structure from input-output information, i...
This paper considers the problem of inferring an unknown network of dynamical systems driven by unkn...
This paper considers the problem of inferring an unknown network of dynamical systems driven by unkn...
Motivated by the fact that transfer functions do not contain structural information about networks, ...
peer reviewedMotivated by the fact that transfer functions do not contain structural information abo...
Motivated by the fact that transfer functions do not contain structural information about networks, ...
Network reconstruction, i.e., obtaining network structure from data, is a central theme in systems b...
peer reviewedNetwork reconstruction, i.e., obtaining network structure from data, is a central theme...
The dynamical structure function of a linear time invariant (LTI) system reveals causal dependencies...
The dynamical structure function of a linear time invariant (LTI) system reveals causal dependencies...
This research explores the role and representation of network structure for LTI systems with partial...
peer reviewedNetwork reconstruction, i.e. obtaining network structure from input-output information,...
peer reviewedThis research explores the role and representation of network structure for LTI systems...
Network reconstruction, i.e. obtaining network structure from input-output information, is a central...
The dynamical structure function of a linear time invariant (LTI) system reveals causal dependencies...
Abstract — Network reconstruction, i.e. obtaining network structure from input-output information, i...
This paper considers the problem of inferring an unknown network of dynamical systems driven by unkn...
This paper considers the problem of inferring an unknown network of dynamical systems driven by unkn...
Motivated by the fact that transfer functions do not contain structural information about networks, ...
peer reviewedMotivated by the fact that transfer functions do not contain structural information abo...
Motivated by the fact that transfer functions do not contain structural information about networks, ...
Network reconstruction, i.e., obtaining network structure from data, is a central theme in systems b...
peer reviewedNetwork reconstruction, i.e., obtaining network structure from data, is a central theme...
The dynamical structure function of a linear time invariant (LTI) system reveals causal dependencies...
The dynamical structure function of a linear time invariant (LTI) system reveals causal dependencies...
This research explores the role and representation of network structure for LTI systems with partial...
peer reviewedNetwork reconstruction, i.e. obtaining network structure from input-output information,...
peer reviewedThis research explores the role and representation of network structure for LTI systems...
Network reconstruction, i.e. obtaining network structure from input-output information, is a central...
The dynamical structure function of a linear time invariant (LTI) system reveals causal dependencies...
Abstract — Network reconstruction, i.e. obtaining network structure from input-output information, i...
This paper considers the problem of inferring an unknown network of dynamical systems driven by unkn...
This paper considers the problem of inferring an unknown network of dynamical systems driven by unkn...