✦ LIBER ✦

Minimum distance automata in parallel networks for optimum classification

✍ Scribed by Jack H. Winters; Christopher Rose

Publisher: Elsevier Science
Year: 1989
Tongue: English
Weight: 478 KB
Volume: 2
Category: Article
ISSN: 0893-6080
DOI: 10.1016/0893-6080(89)90029-4

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✦ Synopsis

Abstraet--ln this paper we study the parallel implementation of optimum classifiers. Specifically, we present a parallel implementation of the optimum (or maximum likelihood Gaussian) classifier that uses a cellular automaton to very rapidly find the output vector with minimum Euclidean distance from the input vector. This implementation also has the feature of easily cascadable chips allowing the number of output vectors to easily grow to arbitrary size.

📜 SIMILAR VOLUMES

On parallel networks for optimum classif

On parallel networks for optimum classification: Jack H. Winters and Christopher Rose. AT&T Bell Laboratories, Holmdel NJ 07733 USA

📂 Article 📅 1988 🏛 Elsevier Science 🌐 English ⚖ 66 KB

In this paper we study the parallel implementation of optimum classifiers. We present a parallel implementation of the optimum (or maximum likelihood Gaussian) classifier that finds the output vector with minimum Euclidean distance from the input vector very rapidly. The classifier is shown in the f