From shrinking to percolation in an optimization model

J. Van Mourik*, K. Y.Michael Wong, D. Bollé

*Corresponding author for this work

Research output: Contribution to journalLetter, comment or opinionpeer-review

Abstract

A model of noise reduction for signal processing and other optimization tasks is introduced. Each noise source puts a symmetric constraint on the space of the signal vector within a tolerance bound. When the number of noise sources increases sequences of transitions take place, causing the solution space to vanish. We find that the transition from an extended solution space to a shrunk space is retarded because of the symmetry of the constraints, in contrast with the analogous problem of pattern storage. For low tolerance, the solution space vanishes by volume reduction, whereas for high tolerance, the vanishing becomes more and more like percolation.

Original languageEnglish
Article numberL53
JournalJournal of Physics A: Mathematical and General
Volume33
Issue number7
DOIs
Publication statusPublished - 2000

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