Design of Fuzzy Respective Space-Based Neuro-Fuzzy Networks for Pattern Recognition
نویسندگان
چکیده
In this paper, we introduce the design of fuzzy respective space-based neuro-fuzzy networks for pattern recognition. The proposed networks are realized by partitioning of the fuzzy respective input space to generate the fuzzy rules. The respectively partitioned spaces using fuzzy respective input space express the rules of the networks. The consequence part of the rules is represented by polynomial functions. The coefficients of consequence part of the rules are learned by the back-propagation algorithm. And we also optimize the proposed networks using real-coded genetic algorithms. A numerical example is given to evaluate the validity of the proposed networks for pattern recognition. As a result, this paper shows that the proposed networks have the good result together with fewer rules.
منابع مشابه
Design of Neuro-Fuzzy Networks Based on Respective Input Space for Pattern Recognition
The design of neuro-fuzzy networks based on fuzzy respective input space for pattern recognition is introduced in this paper. The premise part of the rules of the proposed networks is realized by partitioning of the fuzzy respective input space. The respectively partitioned spaces express the rules of the networks. The consequence part of the rules is represented by polynomial functions. The co...
متن کاملGenetic Design of Fuzzy Neural Networks Based on Respective Input Spaces Using Interval Type-2 Fuzzy Set
In this paper, we propose the genetic design of fuzzy neural networks with multi-output based on interval type-2 fuzzy set (IT2FSFNNm) for pattern recognition. IT2FSFNNm is the networks of combination between the fuzzy neural networks (FNNs) and interval type-2 fuzzy set with uncertainty. The premise part of the networks is composed of the fuzzy partition of respective input spaces and the cons...
متن کاملANFIS Based Color Image Segmentation for Extraction of Salient Features: A Design Approach
Image segmentation is very essential and critical to image processing and pattern recognition. In this paper, a technique for color image segmentation called ‘Adaptive Neuro-Fuzzy Color Image Segmentation (ANFIS)’ is proposed. Adaptive Neuro-Fuzzy system is used for automatic multilevel image segmentation. This system consists of multilayer perceptron (MLP) like network that performs color imag...
متن کاملComparison Between Unsupervised and Supervise Fuzzy Clustering Method in Interactive Mode to Obtain the Best Result for Extract Subtle Patterns from Seismic Facies Maps
Pattern recognition on seismic data is a useful technique for generating seismic facies maps that capture changes in the geological depositional setting. Seismic facies analysis can be performed using the supervised and unsupervised pattern recognition methods. Each of these methods has its own advantages and disadvantages. In this paper, we compared and evaluated the capability of two unsuperv...
متن کاملOn neurobiological, neuro-fuzzy, machine learning, and statistical pattern recognition techniques
In this paper, we propose two new neuro-fuzzy schemes, one for classification and one for clustering problems. The classification scheme is based on Simpson's fuzzy min-max method (1992, 1993) and relaxes some assumptions he makes. This enables our scheme to handle mutually nonexclusive classes. The neuro-fuzzy clustering scheme is a multiresolution algorithm that is modeled after the mechanics...
متن کامل