A Digital Antennal Lobe for Pattern Equalization: Analysis and Design

Part of Advances in Neural Information Processing Systems 15 (NIPS 2002)

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Alex Holub, Gilles Laurent, Pietro Perona


Re-mapping patterns in order to equalize their distribution may greatly simplify both the structure and the training of classifiers. Here, the properties of one such map obtained by running a few steps of discrete-time dynamical system are explored. The system is called 'Digital Antennal Lobe' (DAL) because it is inspired by recent studies of the antennallobe, a structure in the olfactory sys(cid:173) tem of the grasshopper. The pattern-spreading properties of the DAL as well as its average behavior as a function of its (few) de(cid:173) sign parameters are analyzed by extending previous results of Van Vreeswijk and Sompolinsky. Furthermore, a technique for adapting the parameters of the initial design in order to obtain opportune noise-rejection behavior is suggested. Our results are demonstrated with a number of simulations.