Neural Networks and Neuro-Fuzzy Systems

  • Danuta Rutkowska
Part of the Studies in Fuzziness and Soft Computing book series (STUDFUZZ, volume 85)


This chapter presents an overview of neural networks and neuro-fuzzy systems. The latter are a fusion of neural networks and fuzzy techniques, introduced in [293], initially developed in [66], [408], [87], and then in [167], [166], [491], [273], [169], [157], [228], [503], [270], and others. Neuro-fuzzy systems have been applied in many consumer products [492], [493]. They incorporate some merits of both neural networks and fuzzy systems. In the neuro-fuzzy combinations we distinguish fuzzy neural networks (see Section 3.2), obtained by introducing fuzziness directly into neural networks [169], and fuzzy inference neural networks (see Section 3.3), which are representations of fuzzy systems in the form of connectionist networks [513], similar to neural networks. Of course, different types of neuro-fuzzy systems can be found in the literature, e.g. [493], [300], [53], [162], [361], [243], [347], [582], [229], [223], [496], [244], [56], [141], [101].


Neural Network Learning Rule Radial Basis Function Neural Network Radial Basis Function Network Fuzzy Neural Network 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2002

Authors and Affiliations

  • Danuta Rutkowska
    • 1
  1. 1.Department of Computer EngineeringTechnical University of CzestochowaCzestochowaPoland

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