[PDF] Top 20 A recurrent fuzzy cellular neural network system with automatic structure and template learning

... CNN system can solve more complex intel- ligent ...CNN system, in addition to the determination of a set of templates, another kernel problem is the way of ...the fuzzy in- ference ... See full document

... ESULTS AND D ISCUSSIONS The capability of the proposed RFCCNN is demonstrated on the real-world defect inspection ...process and gives each pixel of LCD its own ...texture and demand for high-speed ... See full document

... A Recurrent Self-Organizing Neural Fuzzy Inference Network Chia-Feng Juang and Chin-Teng Lin, Member, IEEE A recurrent self-organizing neural fuzzy ... See full document

... weights and then transform them into the ratioed A-template weights as the ratio memories for recognition of noisy input ...on template coefficients can store and recognize more ... See full document

... proposes a mutually recurrent interval type-2 neu- ral fuzzy system (MRIT2NFS) for dynamic system identifica- ...earlier, with an internal dynamics introduced in the consequent ... See full document

... NN, and recurrent type-1 ...is a self-constructing neural fuzzy inference net- work (SONFIN) [29], which is a powerful network with both structure and ... See full document

... integrates a Self-cOnstructing Neural Fuzzy Infer- ence Network (SONFIN) [26] into a multilayer recurrent neural network (RNN) [27], and can properly explore ... See full document

... link neural network bases. At the same time, the recurrent property is achieved by feeding the output of each membership function back to itself so that each membership value is influenced by its ... See full document

... paper, a direct adaptive iterative learning con- trol (DAILC) based on a new output-recurrent fuzzy neural net- work (ORFNN) is presented for a class of repeatable ... See full document

... through learning. With this property, the neural network-based controllers have been developed to compensate the effects of nonlinearities and system uncertainties, so that the ... See full document

... of a Takagi– Sugeno–Kang (TSK) or functional-link-based ...employs a functional link neural network (FLNN) to the consequent part of fuzzy rules for promoting the mapping ...Unlike ... See full document

... Electrical and Control Engineering, National Chiao-Tung University, Hsinchu, Taiwan, ROC Received July 1996; received in revised form March 1998 Abstract Although multilayered backpropagation neural ... See full document

... rock system for the small initial ...as with the parameters and chosen as 1 and ...parameters and the structure of the aerodynamic functions. The system parameters are ... See full document

... counterpropagation fuzzy-neural network (CFNN) can effectively solve highly non-linear control problems and robustly tune the complicated conversion of human intelligence to logical operating ... See full document

... economical network size and the learning speed and modeling ability are superior to ordinary neural ...networks. A key feature of the SONFIN structure is that a ... See full document

... supervised learning ofneural fuzzy sys- tems which receive only word teaching ...propose a basic structure of0ve-layered feed- forward network for the network realization of ... See full document

... In this section, we shall present the proposed two-phase learning scheme for realizing the N F C N from the given input-output training data sets. In phase one, a self-organize[r] ... See full document

... 144 IEEE TRANSACTIONS ON SYSTEMS, MAN, AND CYBERNETICS-PART B: CYBERNETICS, VOL. This system is able to process and learn numerical information as well as linguistic inf[r] ... See full document

... Given the supervised training data, the proposed learning algorithm first decides whether or not to perform the structure learning based on the fuzzy similarity measure o[r] ... See full document

... conventional neural network classifier represents training information in a one-pixel-one-class ...of a pixel cannot be taken into account resulting in poor classification ...dynamic ... See full document