Related Experiment Video
Updated: Jun 14, 2025

Statistical Modelling of Cortical Connectivity Using Non-invasive Electroencephalograms
Published on: November 1, 2019
Spectral energy transfer on complex networks: a filtering approach
Theodore MacMillan1, Nicholas T Ouellette2
1Department of Civil and Environmental Engineering, Stanford University, Stanford, CA, 94305, USA.
Abstract:
The spectral analysis of dynamical systems is a staple technique for analyzing a vast range of systems. But beyond its analytical utility, it is also the primary lens through which many physical phenomena are defined and interpreted. The turbulent energy cascade in fluid mechanics, a dynamical consequence of the three-dimensional Navier-Stokes equations in which energy "cascades" from large injection scales to smaller dissipation scales, is a well-known example that is precisely defined only in reciprocal space. Related techniques in the context of networked dynamical systems have been employed with great success in deriving reduced order models. But what such techniques gain in analytical tractability, they often lose in interpretability and locality, as the lower degree of freedom system frequently contains information from all nodes of the network. Here, we demonstrate that a network of nonlinear oscillators exhibits spectral energy transfer facilitated by an effective force akin to the Reynolds stress in turbulence, an example of an emergent higher order interaction. Then, introducing a filter-based decomposition motivated by large eddy simulation, we show that such higher order interactions can be localized to individual nodes and study the effects of local topology on such interactions.
Related Concept Videos
Network Function of a Circuit
Energy and Power Signals
Aliasing
If the sampling frequency is below the Nyquist rate, these replicas overlap, preventing the original...
State Space to Transfer Function
The transformation process begins with the state-space representation, characterized by the state equation and the output equation. These equations are typically represented as:
Parseval's Theorem for Fourier transform
To understand Parseval's theorem, it is essential to first comprehend how signal energy is typically calculated. When considering a...
Active Filters

