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Preconditioned Diffusion Multitask Clustering Graph Filters

Published: 28 March 2022 Publication History

Abstract

In this work, we are interested in the design of node-variant FIR graph filters, in which the graph filter estimates the filter coefficients from the stream data. Considering the estimation of filter coefficients as a task, we introduce concept of the multitask into graph filters. The filter coefficients can be divided into different clusters, and the cooperation between clusters is beneficial. Then, a multitask graph diffusion LMS algorithm is proposed. In order to improve convergence speed and performance, a multitask graph diffusion preconditioned algorithm is proposed. The simulation results verify the feasibility of algorithms.

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ICIGP '22: Proceedings of the 2022 5th International Conference on Image and Graphics Processing
January 2022
391 pages
ISBN:9781450395465
DOI:10.1145/3512388
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 28 March 2022

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Author Tags

  1. distributed
  2. graph filters
  3. graph signal processing
  4. multitask

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