Abstract
The continuous general linear group in n dimensions can be decomposed into two Lie groups: (1) an n(n-1) dimensional ‘Markov type’ Lie group that is defined by preserving the sum of the components of a vector, and (2) the n dimensional Abelian Lie group, A(n), of scaling transformations of the coordinates. With the restriction of the first Lie algebra parameters to nonnegative values, one obtains exactly all Markov transformations in n dimensions that are continuously connected to the identity. In this work we show that every network, as defined by its C matrix, is in one to one correspondence to one element of the Markov monoid of the same dimensionality. It follows that any network matrix, C, is the generator of a continuous Markov transformation that can be interpreted as producing an irreversible flow among the nodes of the corresponding network.
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© 2005 Springer-Verlag Berlin Heidelberg
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Johnson, J.E. (2005). Networks, Markov Lie Monoids, and Generalized Entropy. In: Gorodetsky, V., Kotenko, I., Skormin, V. (eds) Computer Network Security. MMM-ACNS 2005. Lecture Notes in Computer Science, vol 3685. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11560326_10
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DOI: https://doi.org/10.1007/11560326_10
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-29113-8
Online ISBN: 978-3-540-31998-6
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