Automatically assigned DDC number: 00632

Manually assigned DDC number: 00632

Number of references: 4

Title: Tau Net: A Neural Network for Modeling Temporal Variability

Author:

Subject: Garrison W. Cottrell Tau Net: A Neural Network for Modeling Temporal Variability

Description: The ability to handle temporal variation is important when dealing with real-world dynamic signals. In many applications, inputs do not come in as fixed-rate sequences, but rather as signals with time scales that can vary from one instance to the next; thus, modeling dynamic signals requires not only the ability to recognize sequences but also the ability to handle temporal changes in the signal. This paper discusses "Tau Net," a neural network for modeling dynamic signals, and its application to speech. In Tau Net, sequence learning is accomplished using a combination of prediction, recurrence and time-delay connections. Temporal variability is modeled by having adaptable time constants in the network, which are adjusted with respect to the prediction error. Adapting the time constants changes the time scale of the network, and the adapted value of the network's time constant provides a measure of temporal variation in the signal. Tau Net has been applied to several simple signals: se...

Contributor: The Pennsylvania State University CiteSeer Archives

Publisher: unknown

Date: 1997-09-11

Pubyear: unknown

Format: ps

Identifier: http://citeseer.ist.psu.edu/144361.html

Source: http://www-cse.ucsd.edu/users/gary/pubs/m.ps

Language: en

Relation:

Relation:

Relation:

Relation:

Rights: unrestricted

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