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What people are saying - Write a reviewWe haven't found any reviews in the usual places. Related booksCommon terms and phrasesantecedent fuzzy sets approximation capability arbitrary ARTx attractive basins attractor choose compact set connection weight matrix continuous function converges Corollary corresponding define defuzzification denazification denote error function FAM's fault-tolerance feedforward neural networks following fact holds fuzzy ART fuzzy inference networks fuzzy logic fuzzy matrix fuzzy neural networks fuzzy operators fuzzy pattern pair fuzzy rule fuzzy sets fuzzy valued functions fuzzy weights gray levels Hongxing Hopfield networks I/O relationship IEEE IEEE Trans imply impulse noise inference rules input patterns Internat Ishibuchi learning algorithm Lemma Liu Puyin Mamdani fuzzy system Moreover neuro-fuzzy neuron node obtain output parameters pattern pair family polygonal FNN's Proc Proof regular FNN's regular fuzzy respectively Sets and Systems shown in Figure Similarly stochastic process Suppose T-S fuzzy system Theorem trapezoidal fuzzy numbers universal approximation vector Popular passagesPage xi - the well-known Hammer Principle: When the only tool you have is a hammer, everything looks like a nail. Page 67 - Hirota K, Fast solving method of fuzzy relational equation and its application to lossy image compression/reconstruction, IEEE Page 3 - has since led to an evolving series of realtime neural network models for unsupervised category learning and pattern recognition. Page 3 - which can carry out parallel search, or hypothesis testing, of distributed recognition codes in a multi-level network hierarchy Page 327 - Fuzzy inference system can simulate and realize natural language and logic inference mechanic. The subjects related, such as how fuzzy rule base can be constructed by given linguistic and data information, whether the systems related can adaptively match fuzzy rules, and so on attract many scholar's attention Page xi - which underlies soft computing is that, in general, better results can be obtained by employing the constituent methodologies of soft computing in combination rather Page 327 - Defuzzification is a procedure by which a fuzzy set is transformed into one crisp value of being able to describe the fuzzy set. In fuzzy control, it turns a fuzzy decision into a concrete control value and system control Page 194 - Jam RC, A robust back propagation learning algorithm for function approximation, IEEE Trans. on Neural Networks, Page 66 - Fuzzy adaptive learning control network with on-line neural learning, Fuzzy Sets and Systems, References to this bookFrom Google ScholarFuzzy Time Series Prediction Method Based on Fuzzy Recurrent ...Rafik Aliev, Bijan Fazlollahi, Rashad Aliev, Babek Guirimov Linguistic time series forecasting using fuzzy recurrent neural ...R A Aliev, B Fazlollahi, R R Aliev, B Guirimov - 2008 - Soft Computing-A Fusion of Foundations, Methodologies and Applications An application of incline matrices in dynamic analysis of ...Song-Chol Han, Yun-Dong Gu, Hong-Xing Li - 2007 - Fuzzy Sets and Systems Application of a Fuzzy Neural Network for Modeling of the Mass ...Mitko Petrov, Tatiana Ilkova, Stoyan Tzonkov, Uldis Viesturs References from web pagesFUZZY NEURAL NETWORK THEORY AND APPLICATION Libro - Puyin Liu - Fuzzy Neural Network Theory and Application ... Fuzzy Neural Network Theory and Application ห้องสมุด สถาบันเทคโนโลยีปทุมวัน Bibliographic information
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