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September 10, 2025Filomat1 citationsOpen Access

Fusion frame, relay fusion frame and signal reconstruction

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GHGuoqing Hong

Key Points

  • Signal recovery is achieved stably through fusion frames, with controlled deviation in approximate solutions.
  • Utilizing different norms enhances guarantees of robustness and stability, improving reconstruction outcomes.
  • Theoretical guarantees for recovery are established using operator theory to analyze relay fusion frames.
  • The study clarifies the connection between relay fusion frames and compressed sensing, expanding existing frameworks.

Abstract

In this paper, we demonstrate that any signal exhibiting a certain sparse pattern can be recovered in a stable and resilient manner through the utilization of the fusion frame approach. The theoretical analysis highlights that the deviation of the approximate solution is effectively controlled. Furthermore, the adoption of different norms contributes to further reinforcing the guarantees of robustness and stability. Driven by the ideas of compressed sensing and fusion frames, we extend the setting to relay fusion frames. With the help of operator theory, we provide several recovery guarantee conditions based on the relay fusion frames. Finally, the relationship between relay fusion frames and compressed sensing is elucidated.

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Cite This Study

Guoqing Hong (2025) studied this question.

synapsesocial.com/papers/68c1c62f54b1d3bfb60f1ad8https://doi.org/10.2298/fil2506797h
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Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1A Mathematical Introduction to Compressive Sensing2013 · 2,634 citations
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  3. 3Relay fusion frames and bridging results for fusion frames2020 · 6 citations
  4. 4Sparse Approximate Solutions to Linear Systems1995 · 2,846 citations
  5. 5Robust uncertainty principles: exact signal reconstruction from highly incomplete frequency information2006 · 15,903 citations