title: The optimal encodings for biased association in linear associative memories.
abstract: In this paper, optimal encoding schemes for linear associative memories are derived for biased association under both the white-noise and colored-noise situations. Analysis and simulation results all show that the biased encodings thus derived are optimal and superior to existing models in their performance. Together with the Wee-Kohonen unbiased encoding, the study settles the optimality issue of linear associative memories and enhances their practicalities.
authors.affiliation: Department of Geography and Centre for Enviromental Studies, The Chinese University of Hong Kong, Shatin, Hong Kong
authors.forename: Yee
authors.initials: Y
authors.lastname: Leung
authors.forename: Tian Xin
authors.initials: TX
authors.lastname: Dong
authors.forename: Zong Ben
authors.initials: ZB
authors.lastname: Xu