Abstract
Graph signal processing (GSP) can be understood as a branch in which signal processing, a branch in electrical engineering, collaborates with graph theory, a branch in mathematics. In GSP, digitalized signals are represented by graphs and it gives a simple representation of sampled data with vertices and edges of the graph. GSP employs a method called subsampling in which a subset of the original data set is selected which serves to reduce the size of the data [9]. This work selects the dominating set of the graph as the subsample, in deviation from the previous works on GSP. We are using the properties of dominating vertices to draw the advantages of such a subsampling. A more efficient subsampling process to ‘efficient dominating set’ is also presented and an upper bound for the number of vertices in such a subsampling is found. The case when efficient dominating set does not exist is also discussed. We also described some special cases of subsampling.
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Dhanya, E., Thomas, G., Mathew, J.K. (2022). Subsampling in Graph Signal Processing Based on Dominating Set. In: Raj, J.S., Shi, Y., Pelusi, D., Balas, V.E. (eds) Intelligent Sustainable Systems. Lecture Notes in Networks and Systems, vol 458. Springer, Singapore. https://doi.org/10.1007/978-981-19-2894-9_56
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DOI: https://doi.org/10.1007/978-981-19-2894-9_56
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