Designing neural network architectures for pattern recognition

Research output: Contribution to journalArticlepeer-review

3 Scopus citations


An appropriately designed architecture of a neural network is essential to many realistic pattern-recognition tasks. A choice of just the right number of neurons, and their interconnections, can cut learning costs by orders of magnitude, and still warrant high classification accuracy. Surprisingly, textbooks often neglect this issue. A specialist seeking systematic information will soon realize that relevant material is scattered over diverse sources, each with a different perspective, terminology and goals. This brief survey attempts to rectify the situation by explaining the involved aspects, and by describing some of the fundamental techniques.

Original languageEnglish (US)
Pages (from-to)151-170
Number of pages20
JournalKnowledge Engineering Review
Issue number2
StatePublished - Jun 1 2000
Externally publishedYes

ASJC Scopus subject areas

  • Software
  • Artificial Intelligence


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