2016Unpublished venueRequires access

Laplacian dynamics on signed networks

Lulu Pan, Haibin Shao, Mehran Mesbahi

Open publisher page 22 citations

Abstract

In this paper, we examine the properties of the Laplacian matrix defined on signed networks, referred to as the signed Laplacian matrix, from a graph-theoretic perspective. The connection between the stability of the signed Laplacian with the cut set of the network is established. This is then followed by relating and the number of negative eigenvalues of the signed Laplacian to the number of negatively weighted edges in the network. In order to stabilize the signed Laplacian dynamics, a distributed diagonal compensation approach is proposed; we show that this compensation is closely related to the structural balance of the network. Furthermore, the influence of the external input exerted on the signed Laplacian dynamics is investigated.

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What this paper is about

In this paper, we examine the properties of the Laplacian matrix defined on signed networks, referred to as the signed Laplacian matrix, from a graph-theoretic perspective. The connection between the stability of the signed Laplacian with the cut set of the network is established. This is then followed by relating and the number of negative eigenvalues of the signed Laplacian to the number of negatively weighted edges in the network. In order to stabilize the signed Laplacian dynamics, a distributed diagonal compensation approach is proposed; we show that this compensation is closely related to the structural balance of the network. Furthermore, the influence of the external input exerted on the signed Laplacian dynamics is investigated.

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OpenAlex reports 22 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

In this paper, we examine the properties of the Laplacian matrix defined on signed networks, referred to as the signed Laplacian matrix, from a graph-theoretic perspective. The connection between the stability of the signed Laplacian with the cut set of the network is established. This is then followed by relating and the number of negative eigenvalues of the signed Laplacian to the number of negatively weighted edges in the network. In order to stabilize the signed Laplacian dynamics, a distributed diagonal compensation approach is proposed; we show that this compensation is closely related to the structural balance of the network. Furthermore, the influence of the external input exerted on the signed Laplacian dynamics is investigated.

Key concepts: Laplacian matrix, Laplace operator, Signed graph, Eigenvalues and eigenvectors, Diagonal, Mathematics, Diagonal matrix, Stability (learning theory)

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