The time dimension of neural network models

Richard Rohwer

    Research output: Contribution to journalArticlepeer-review


    This review attempts to provide an insightful perspective on the role of time within neural network models and the use of neural networks for problems involving time. The most commonly used neural network models are defined and explained giving mention to important technical issues but avoiding great detail. The relationship between recurrent and feedforward networks is emphasised, along with the distinctions in their practical and theoretical abilities. Some practical examples are discussed to illustrate the major issues concerning the application of neural networks to data with various types of temporal structure, and finally some highlights of current research on the more difficult types of problems are presented.
    Original languageEnglish
    Pages (from-to)36-44
    Number of pages9
    JournalSigart bulletin
    Issue number3
    Publication statusPublished - Jul 1994


    • time
    • neural network model
    • recurrent and feedforward networks


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