An algorithm for computation of inter-pattern interference noise in BAM

Dilip Sarkar

Research output: Contribution to journalArticlepeer-review


Standard Bidirectional Associative Memory (BAM) stores sum-of-the-correlation-matrices of the pairs of patterns. When a pattern of an encoded pair is presented, the other is expected to be recalled. It has been shown that standard BAM cannot correctly recall a pattern pair if it is not at local minima of the energy function. To overcome this problem, novel methods for encoding have been proposed. The efficient novel-encoding methods require knowledge of the interference noise in the standard BAM. In this paper, we propose an algorithm for computing the exact amount of interference noise in standard encoding of BAM. The computational complexity of the algorithm is the same as that of computing the correlation matrix for the standard BAM.

Original languageEnglish (US)
Pages (from-to)67-73
Number of pages7
JournalNeural Network World
Issue number1
StatePublished - Jan 1 2002


  • Bidirectional associative memory (BAM)
  • Coding strategies
  • Interference noise
  • Multiple training

ASJC Scopus subject areas

  • Software
  • Neuroscience(all)
  • Hardware and Architecture
  • Artificial Intelligence


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