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- Sudeep Stephen, Bharati Rajan, Joseph F. Ryan, Cyriac Grigorious, Albert William
- J. Discrete Algorithms
- 2015

- Cyriac Grigorious, Paul D. Manuel, Mirka Miller, Bharati Rajan, Sudeep Stephen
- Applied Mathematics and Computation
- 2014

- Sudeep Stephen, Bharati Rajan, Cyriac Grigorious, Albert William
- Applied Mathematics and Computation
- 2015

Let G = (V,A) be a directed graph without parallel arcs, and let S ⊆ V be a set of vertices. Let the sequence S = S0 ⊆ S1 ⊆ S2 ⊆ · · · be defined as follows: S1 is obtained from S0 by adding all out-neighbors of vertices in S0. For k > 2, Sk is obtained from Sk−1 by adding all vertices w such that for some vertex v ∈ Sk−1, w is the unique out-neighbor of v… (More)

- Cyriac Grigorious, Sudeep Stephen, Bharati Rajan, Mirka Miller, Albert William
- Inf. Process. Lett.
- 2014

- Patrick Andersen, Cyriac Grigorious, Mirka Miller
- Discrete Math., Alg. and Appl.
- 2016

A metric basis is a set W of vertices of a graph G(V,E) such that for every pair of vertices u, v of G, there exists a vertex w ∈ W with the condition that the length of a shortest path from u to w is different from the length of a shortest path from v to w. The minimum cardinality of a metric basis for G is called the metric dimension. A pair of vertices… (More)

- Bharati Rajan, Indra Rajasingh, Cyriac Grigorious, Sudeep Stephen
- 2012 Second International Conference on Digital…
- 2012

Eigenvalues of a graph are the eigenvalues of its adjacency matrix. The multiset of eigenvalues is called the spectrum. There are many properties which can be explained using the spectrum like energy, connectedness, vertex connectivity, chromatic number, and perfect matching etc. So it is very useful to calculate the spectrum of any graph. The energy of a… (More)

- Cyriac Grigorious, Sudeep Stephen, Bharati Rajan, Mirka Miller
- Comput. J.
- 2017

Eigenvalues of a graph are the eigenvalues of its adjacency matrix. The multiset of eigenvalues is called its spectrum. There are many properties which can be explained using the spectrum like energy, connectedness, vertex connectivity, chromatic number, perfect matching etc. Laplacian spectrum is the multiset of eigenvalues of Laplacian matrix. The… (More)