Neuro-Fuzzy Architectures Based on the Mamdani Approach
Danuta Rutkowska · Studies in fuzziness and soft computing · 2002
The fuzzy inference neural networks (see Section 3.3) that realize the inference based on the Mamdani approach are the subject of this chapter. Different, multi-layer, architectures of the neuro-fuzzy systems are portrayed. The systems with various fuzzifiers (singleton, non-singleton), defuzzifiers, and inference operations, are considered. All these systems can be trained, when applied to solve practical problems, similarly to neural networks. Learning methods of neuro-fuzzy systems are presented in Chapter 6, including the architecture-based learning, proposed in Section 6.1.3. Interested readers may also be referred to [420], [434].