VLSI design of approximate message passing for signal restoration and compressive sensing

Patrick Maechler, Christoph Studer, David E. Bellasi, Arian Maleki, Andreas Burg, Norbert Felber, Hubert Kaeslin, Richard G. Baraniuk

Research output: Contribution to journalArticlepeer-review

64 Scopus citations


Sparse signal recovery finds use in a variety of practical applications, such as signal and image restoration and the recovery of signals acquired by compressive sensing. In this paper, we present two generic very-large-scale integration (VLSI) architectures that implement the approximate message passing (AMP) algorithm for sparse signal recovery. The first architecture, referred to as AMP-M, employs parallel multiply-accumulate units and is suitable for recovery problems based on unstructured (e.g., random) matrices. The second architecture, referred to as AMP-T, takes advantage of fast linear transforms, which arise in many real-world applications. To demonstrate the effectiveness of both architectures, we present corresponding VLSI and field-programmable gate array implementation results for an audio restoration application. We show that AMP-T is superior to AMP-M with respect to silicon area, throughput, and power consumption, whereas AMP-M offers more flexibility.

Original languageEnglish (US)
Article number6331565
Pages (from-to)579-590
Number of pages12
JournalIEEE Journal on Emerging and Selected Topics in Circuits and Systems
Issue number3
StatePublished - 2012


  • Approximate message passing (AMP)
  • compressive sensing (CS)
  • ell-norm minimization
  • fast discrete cosine transform (DCT)
  • field-programmable gate array (FPGA)
  • signal restoration
  • sparse signal recovery
  • very-large scale integration (VLSI)

ASJC Scopus subject areas

  • Electrical and Electronic Engineering


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