Skip to main content

1995 | OriginalPaper | Buchkapitel

Unsupervised Learning of Temporal Sequences by Neural Networks

verfasst von : B. Gas, R. Natowicz

Erschienen in: Artificial Neural Nets and Genetic Algorithms

Verlag: Springer Vienna

Aktivieren Sie unsere intelligente Suche um passende Fachinhalte oder Patente zu finden.

search-config
loading …

We propose to define a new model of formal neural network. This model extends existing Hopfield networks to process temporal data and achieve a non-supervised learning of them. We propose a learning law to adress in this context the sensitivity to input changes. A spatial representation of network’s temporal activity is given by which learnt sequences can be identified. An example of such a network is given and the results of the simulation are presented.

Metadaten
Titel
Unsupervised Learning of Temporal Sequences by Neural Networks
verfasst von
B. Gas
R. Natowicz
Copyright-Jahr
1995
Verlag
Springer Vienna
DOI
https://doi.org/10.1007/978-3-7091-7535-4_67

Neuer Inhalt