Sign least mean squares-based deconvolution technique for ultrasonic testing

Mohammed Siddig (Corresponding Author), Kim Ki-Seong

Research output: Contribution to journalArticleScientificpeer-review

1 Citation (Scopus)


Sign LMS algorithms, members of the simplified adaptive least-mean-squares class, have been developed to reduce computational complexity and simplify hardware implementation. These advantages make them suitable to utilize in ultrasonic testing units, a class of applications requiring simple and efficient signal processing algorithms. This paper proposes a specific sign LMS adaptive filters-based deconvolution technique for ultrasonic straight beam pulse-echo inspections. It extracts only two of the interface echoes multiple reflections for enhanced resolution and quality-enriched presentation; this technique is named "selective deconvolution". Resolution enhancement and presentation's quality enrichment performance among the different sign LMS algorithms were investigated by experiments, and based on performance, the methods themselves were compared. Computational requirements are also presented. The proposed technique with the various adaptive sign LMS filters gave satisfactory results.

Original languageEnglish
Pages (from-to)609-613
JournalRussian Journal of Nondestructive Testing
Issue number10
Publication statusPublished - Oct 2012
MoE publication typeA1 Journal article-refereed


  • adaptive LMS
  • resolution
  • selective deconvolution
  • sign LMS


Dive into the research topics of 'Sign least mean squares-based deconvolution technique for ultrasonic testing'. Together they form a unique fingerprint.

Cite this