DISCRETE REPRESENTATION OF NONLINEAR PROCESSES USING TIME SERIES DATA.

Steven Hsin-Yi Lai, S. H. Hsieh

Research output: Contribution to conferencePaperpeer-review

Abstract

This paper presents a modeling technique for the discrete representation of nonlinear processes. The modeling technique is referred to as the Nonlinear Data Dependent System (NLDDS) which contains a nonlinear pattern classification procedure and a model search algorithm. The method uses some statistical and graphic techniques to generate various linear and nonlinear patterns for data classification. System dynamics are characterized in terms of nonlinear autoregressive moving average (NLARMA) models.

Original languageEnglish
Pages43-49
Number of pages7
Publication statusPublished - 1987 Dec 1

All Science Journal Classification (ASJC) codes

  • Engineering(all)

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