On the Inverse of Forward Adjacency Matrix

11/25/2017
by   Pritam Mukherjee, et al.
0

During routine state space circuit analysis of an arbitrarily connected set of nodes representing a lossless LC network, a matrix was formed that was observed to implicitly capture connectivity of the nodes in a graph similar to the conventional adjacency matrix, but in a slightly different manner. This matrix has only 0, 1 or -1 as its elements. A sense of direction (of the graph formed by the nodes) is inherently encoded in the matrix because of the presence of -1. Calling this matrix as forward adjacency matrix, it was found that its inverse also displays useful and interesting physical properties when a specific style of node-indexing is adopted for the nodes in the graph. The graph considered is connected but does not have any closed loop/cycle (corresponding to closed loop of inductors in a circuit) as with its presence the matrix is not invertible. Incidentally, by definition the graph being considered is a tree. The properties of the forward adjacency matrix and its inverse, along with rigorous proof, are presented.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
10/20/2019

Spectral Analysis of the Adjacency Matrix of Random Geometric Graphs

In this article, we analyze the limiting eigenvalue distribution (LED) o...
research
06/28/2023

Finding the connected components of the graph using perturbations of the adjacency matrix

The problem of finding the connected components of a graph is considered...
research
05/12/2020

Functions and eigenvectors of partially known matrices with applications to network analysis

Matrix functions play an important role in applied mathematics. In netwo...
research
07/25/2020

Support of Closed Walks and Second Eigenvalue Multiplicity of the Normalized Adjacency Matrix

We show that the multiplicity of the second normalized adjacency matrix ...
research
03/20/2019

Modelling Graph Errors: Towards Robust Graph Signal Processing

The first step for any graph signal processing (GSP) procedure is to lea...
research
12/07/2017

Core Discovery in Hidden Graphs

Massive network exploration is an important research direction with many...
research
10/06/2022

An SIE Formulation with Triangular Discretization and Loop Analysis for Parameter Extraction of Arbitrarily Shaped Interconnects

A surface integral equation (SIE) formulation under the magneto-quasi-st...

Please sign up or login with your details

Forgot password? Click here to reset