A hierarchical clustering method for the multiple constant multiplication problem

Akihiro Matsuura, Mitsuteru Yukishita, Akira Nagoya

Research output: Contribution to journalArticlepeer-review

8 Citations (Scopus)


In this paper, we propose an efficient solution for the Multiple Constant Multiplication (MCM) problem. The method uses hierarchical clustering to exploit common subexpressions among constants and reduces the number of shifts, additions, and subtractions. The algorithm defines appropriate weights, which indicate operation priority, and selects common subexpressions, resulting in a minimum number of local operations. It can also be extended to various high-level synthesis tasks such as arbitrary linear transforms. Experimental results for several error-correcting codes, digital filters and Discrete Cosine Transforms (DCTs) have shown the effectiveness of our method.

Original languageEnglish
Pages (from-to)1767-1773
Number of pages7
JournalIEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences
Issue number10
Publication statusPublished - Jan 1 1997
Externally publishedYes


  • Common subexpression
  • Constant multiplication
  • High-level synthesis
  • MCM problem

ASJC Scopus subject areas

  • Signal Processing
  • Computer Graphics and Computer-Aided Design
  • Electrical and Electronic Engineering
  • Applied Mathematics


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