A Neuro–Fuzzy Bibliography

Detlef Nauck

Technical University of Braunschweig, Dept. of Computer Science, Bueltenweg 74–75, D–38106 Braunschweig, Germany Tel: +49.531.391.3155, Fax: +49.531.391.5936 E-Mail: D.Nauck@tu-bs.de, URL: www.cs.tu-bs.de/∼nauck

May 20, 1996

This bibliography can be obtained on the Internet: via WWW at http://www.cs.tu-bs.de/ibr/fuzzy/papers.html via FTP at: ftp://ftp.ibr.cs.tu-bs.de/pub/local/papers/fuzzy-nn.bib

References

S. Abe and M.-S. Lan (1995a). Fuzzy Rule Extraction Directly from Numerical Data for Function Approximation. IEEE Trans. Systems, Man & Cybernetics, 25:119–129.

S. Abe and M.-S. Lan (1995b). A Method for Fuzzy Rules Extraction Directly from Numerical Data and Its Application to Pattern Classification. IEEE Trans. Fuzzy Systems, 3(1):18–28.

S. Abe, M.-S. Lan and R. Thawonmas (1996). Tuning of a Fuzzy Classifier Derived from Data. Int. J. Approximate Reasoning, 14(1):1–24.

C. von Altrock, B. Krause and H.-J. Zimmermann (1992). Advanced Fuzzy Logic Control Technologies in Automotive Applications. In Proc. IEEE Int. Conf. on Fuzzy Systems 1992 , pages 835–842, San Diego.

A. Amano, T. Aritsuka, N. Hataoka and A. Ichikawa (1989). On the Use of Neural Networks and Fuzzy Logic in Speech Recognition. In Int. Joint Conf. on Neural Networks 1989, Vol.1 , pages I301–I306.

P. Andlinger and E. R. Reichl (1991). Fuzzy-Neunet: A Non Standard Neural Network. In [Prieto et al., 1991], pages 173–180.

N. Archer and S. Wang (1991). Fuzzy Set Representation of Neural Net Classification Boundaries. IEEE Trans. Systems, Man & Cybernetics, 21:735–742.

K. Asakawa and H. Takagi (1994). Neural Networks in Japan. Communications of the ACM, 37(3):106–112.

A. G. Barto (1992). Reinforcement Learning and Adaptive Critic Methods. In [White and Sofge, 1992], pages 469–491. Van Nostrand Reinhold.

H. Berenji (1990). Neural Networks and Fuzzy Logic in Intelligent Control. In 5th IEEE Int. Symposium on Intelligent Control, Vol.2 , pages 916–920.

H. R. Berenji (1992). A Reinforcement Learning-Based Architecture for Fuzzy Logic Control. Int. J. Approximate Reasoning, 6:267 –292.

H. R. Berenji and P. Khedkar (1992a). Fuzzy Rules for Guiding Reinforcement Learning. In Int. Conf. on Information Processing and Management of Uncertainty in Knowledge-Based Systems (IPMU’92), pages 511–514, Mallorca.

H. R. Berenji and P. Khedkar (1992b). Learning and Tuning Fuzzy Logic Controllers Through Reinforcements. IEEE Trans. Neural Networks, 3:724–740.

H. R. Berenji and P. Khedkar (1993). Clustering in Product Space for Fuzzy Inference. In Proc. IEEE Int. Conf. on Neural Networks 1993 , pages 1402–1407, San Francisco.

H. R. Berenji, R. N. Lea, Y. Jani, P. Khedkar, A. Malkani and J. Hoblit (1993). Space Shuttle Attitude Control by Reinforcement Learning and Fuzzy Logic. In Proc. IEEE Int. Conf. on Neural Networks 1993 , pages 1396–1401, San Francisco.

H. R. Berenji, A. Malkani and C. Copeland (1995). Tether Control Using Fuzzy Reinforcement Learning. In Proc. IEEE Int. Conf. on Fuzzy Systems 1995 , pages 1315–1322, Yokohama.

H. Bersini, J.-P. Nordvik and A. Bonarini (1993). A Simple Direct Adaptive Fuzzy Controller Derived from its Neural Equivalent. In Proc. IEEE Int. Conf. on Fuzzy Systems 1993 , pages 345–350, San Francisco.

J. C. Bezdek, E. C.-K. Tsao and N. R. Pal (1992). Fuzzy Kohonen Clustering Networks. In Proc. IEEE Int. Conf. on Fuzzy Systems 1992 , pages 1035–1043, San Diego.

K. Brahim and A. Zell (1994). ANFIS–SNNS: Adaptive Network Fuzzy Inference System in the Stuttgart Neural Network Simulator. In [Kruse et al., 1994], pages 117–128. Vieweg, Braunschweig.

F. Bremner, M. Yost and V. Nasman (1989). Statistical analysis of fuzzy-set data from neuronal networks. Behav. Res. Methods. Comput., 21:209–212.

N. Bridgett, J. Brandt and C. Harris (1995). A Neurofuzzy Route to Breast Cancer Diagnosis and Treatment. In Proc. IEEE Int. Conf. on Fuzzy Systems 1995 , pages 641–648, Yokohama.

M. Brown, P. An and H. C.J. (1995a). On the Condition of Adaptive Neurofuzzy Models. In Proc. IEEE Int. Conf. on Fuzzy Systems 1995 , pages 663–670, Yokohama.

M. Brown, K. Bossley, D. Mills and H. C.J. (1995b). High Dimensional Neurofuzzy Systems: Overcoming the Course of Dimensionality. In Proc. IEEE Int. Conf. on Fuzzy Systems 1995 , pages 2139–2146, Yokohama.

M. Brown, R. Fraser, C. Harris and C. Moore (1991). Intelligent self-organizing controllers for autonomous guided vehicles: comparative aspects of fuzzy logic and neural nets. In Int. Conf. on Control, Vol.1 , pages 134–139.

J. J. Buckley and Y. Hayashi (1993a). Hybrid neural nets can be fuzzy controllers and fuzzy expert systems. Fuzzy Sets and Systems, 60:135–142.

J. J. Buckley and Y. Hayashi (1993b). Numerical relationships between neural networks, continuous functions, and fuzzy systems. Fuzzy Sets and Systems, 60:1–8.

J. J. Buckley and Y. Hayashi (1994a). Can fuzzy neural nets approximate continuous fuzzy functions?. Fuzzy Sets and Systems, 61:43–52.

J. J. Buckley and Y. Hayashi (1994b). Hybrid fuzzy neural nets are universal approximators. In Proc. IEEE Int. Conf. on Fuzzy Systems 1994 , pages 238–243, Orlando.

J. J. Buckley, Y. Hayashi and E. Czogala (1993). On the equivalence of neural nets and fuzzy expert systems. Fuzzy Sets and Systems, 53:129–134.

J. J. Buckley and Y. Hayashi (1994c). Fuzzy Neural Networks: A survey. Fuzzy Sets and Systems, 66:1–13.

J. J. Buckley and Y. Hayashi (1995). Neural Networks for Fuzzy Systems. Fuzzy Sets and Systems, 71:265–276.

G. A. Carpenter, S. Grossberg, N. Markuzon, J. H. Reynolds and D. B. Rosen (1992). Fuzzy ARTMAP: A Neural Network Architecture for Incremental Supervised Learning of Analog Multidimensional Maps. IEEE Trans. Neural Networks, 3(5):698–712.

T. Chen (1995). Fuzzy Neural Network Applications in Medicine. In Proc. IEEE Int. Conf. on Fuzzy Systems 1995 , pages 627–634, Yokohama.

O. Chorayan (1982). Identifying elements of the probabilistic neuronal ensembles from the standpoint of fuzzy sets theory. Fuzzy Sets and Systems, 8:141–147.

T. Culliere, A. Titli and J. Corrieu (1995). Neuro-Fuzzy Modelling of Nonlinear Systems for Control Purposes. In Proc. IEEE Int. Conf. on Fuzzy Systems 1995 , pages 2009– 2016, Yokohama.

A. da Rocha (1981). Neural Fuzzy Point Processes. Fuzzy Sets and Systems, 5:127–140.

V. Dabija and N. Tschichold-Gürman (1993). A Framework for Combining Symbolic and Connectionist Learning with Equivalent Concept Descriptions. In Proc. of the 1993 Int. Joint Conf. on Neural Networks (IJCNN-93), Nagoya.

C. H. Dağlĭ, S. R. Kumara and Y. C. Shin, eds. (1991). Proceedings of the Artifical Neural Networks in Engineering Conference, St. Louis. ASME.

F. d’Alché-Buc, V. Andrès and J.-P. Nadal (1992). Learning Fuzzy Control Rules with a Fuzzy Neural Network. Artificial Neural Networks, 2:715–719.

J. Diamond, R. McLeod and W. Pedrycz (1990). A fuzzy cognitive system: examination of a referential neural architecture. In Int. Joint Conf. on Neural Networks 1990, Vol.2 , pages 617–622.

H. Diekgerdes (1993). NEFCON-I: Entwurf und Implementierung einer Entwicklungsumgebung für Neuronale Fuzzy-Regler. Diplomarbeit, Technische Universität Braunschweig.

Y. Dote, A. Suyitno and M. Strefezza (1990). Fuzzy learning grasping force controller for manipulator hand. In IEEE Int. Conf. on Intelligent Motion Control, pages 87–93.

D. Dubois, R. Martin-Coulaire and H. Prade (1988). Practical computing in fuzzy logic. In [Gupta and Yamakawa, 1988], pages 11–34. North Holland.

R. Eckmiller, G. Hartmann and G. Hauske, eds. (1991). Parallel Processing in Neural Systems and Computers. Elsevier Science (North Holland), Amsterdam.

B. Eikens, V. Saucedo, M. Karim and A. Morris (1995). Waste Water Neutralization Using a Fuzzy Neural Network Controller. In Proc. American Control Conference 1995 .

P. Eklund (1993). GeDeMeDeS A Generic System for Developing Medical Decision Support. In Proc. First European Congress on Fuzzy and Intelligent Technologies (EU-FIT93), pages 801–803, Aachen.

P. Eklund (1994). Network Size versus Preprocessing. In [Yager and Zadeh, 1994]. Van Nostrand Reinhold.

P. Eklund, M. Fogström and J. Frosström (1992a). A Generic Neuro–Fuzzy Tool for Developing Medical Decision support. In P. Eklund, ed.: Proc. of the MEPP’92 , pages 11–27, Åbo. Åbo Akademi Press.

P. Eklund and R. Fullér (1993). A Neuro–Fuzzy Approach to Medical Diagnostics. In Proc. First European Congress on Fuzzy and Intelligent Technologies (EUFIT93), pages 810–813, Aachen.

P. Eklund and F. Klawonn (1992). Neural Fuzzy Logic Programming. IEEE Trans. Neural Networks, 3:815–818.

P. Eklund, F. Klawonn and D. Nauck (1992b). Distributing Errors in Neural Fuzzy Control. In Proc. 2nd Int. Conf. on Fuzzy Logic and Neural Networks (IIZUKA’92), pages 1139–1142.

W. Eppler (1990a). Implementation of Fuzzy Production Systems With Neural Networks. In [Eckmiller et al., 1991], pages 249–252. Elsevier Science (North Holland).

W. Eppler (1990b). Prestructuring of neural networks with fuzzy rules. In Neuro-Nimes’90. 3rd Int. Workshop on Neural Networks and Their Applications, pages 227–241.

A. O. Esogbue (1993). A Fuzzy Adaptive Controller Using Reinforcement Learning Neural Networks. In Proc. IEEE Int. Conf. on Fuzzy Systems 1993 , pages 178–183, San Francisco.

T. Feuring and W.-M. Lippe (1995a). Fuzzy neural networks are universal approximators. In Proc. 6th IFSA Congress (IFSA’95), Sao Paulo.

T. Feuring and W.-M. Lippe (1995b). A Goodness Function for trained fuzzy neural networks. In Proc. IEEE Int. Conf. on Neural Networks 1995 (ICNN’95), Perth.

S. Foerster (1993). Zu Kombinationen Neuronaler Netze und Fuzzy Systeme. Diplomarbeit, Technische Universität Braunschweig.

S. Fraleigh (1994). Fuzzy Logic and Neural Networks. PC AI, 8(3):16–21.

B. Freisleben and T. Kunkelmann (1993). Combining Fuzzy Logic and Neural Networks to Control an Autonomous Vehicle. In Proc. IEEE Int. Conf. on Fuzzy Systems 1993 , pages 321–326, San Francisco.

L.-M. Fu (1990). Backpropagation in neural networks with fuzzy conjunction units. In Int. Joint Conf. on Neural Networks 1990, Vol.1 , pages 613–618.

T. Furuya, A. Kokubu and T. Sakamoto (1988). FS: Neuro Fuzzy Inference System. In Int. Workshop on Fuzzy System Applications (IIZUKA’88), pages 219–230.

P.-Y. Glorennec (1990). Associating a neural network and fuzzy rules for dynamic process control. In Neuro-Nimes’90. 3rd Int. Workshop on Neural Networks and Their Applications, pages 211–225.

J. Godjevac (1993). State of the Art in the Neuro Fuzzy Field. Technical Report R93.25, LAMI–EPFL, Lausanne.

D. Goldberg (1989). Genetic Algorithms in Search, Optimization and Machine Learning. Addison–Wesley, Reading, MA.

A. Gonzales and R. Perez (1995). Structural Lerarning of Fuzzy Rules from Noised Examples. In Proc. IEEE Int. Conf. on Fuzzy Systems 1995 , pages 1322–1330, Yokohama.

P. Goode and M.-y. Chow (1994). A Hybrid Fuzzy/Neural System Used to Extract Heuristic Knowledge from a Fault Detection Problem. In Proc. IEEE Int. Conf. on Fuzzy Systems 1994 , pages 1731–1736, Orlando.

V. Gorrini, T. Salom and H. Bersini (1995). Self-Structuring Fuzzy Systems for Function Approximation. In Proc. IEEE Int. Conf. on Fuzzy Systems 1995 , pages 919–926, Yokohama.

M. M. Gupta (1992). Fuzzy logic and neural networks. In Proc. 2nd Int. Conf. on Fuzzy Logic and Neural Networks (IIZUKA’92).

M. M. Gupta and D. H. Rao (1994). On the principles of fuzzy neural networks. Fuzzy Sets and Systems, 61:1–18.

M. M. Gupta and T. Yamakawa, eds. (1988). Fuzzy Computing, Theory, Hardware and Applications. North Holland, Amsterdam.

M. Gupta (1990). Fuzzy neural network approach to control system. In IEEE 1990 American Control Conf., volume 3, pages 3019–3022.

M. Gupta and G. Knopf (1990). Fuzzy neural network approach to control systems. In First Int. Symposium on Uncertainty Modeling and Analysis.

S. K. Halgamuge (1995). Advanced Methods for Fusion of Fuzzy Systems and Neural Networks in Intelligent Data Processing. PhD thesis, Technische Hochschule Darmstadt.

S. K. Halgamuge and M. Glesner (1992). A Fuzzy–Neural Approach for Pattern Classification with the Generation of Rules based on Supervised Learning. In Proc. Neuro– Nimes 92 , pages 167–173, Nanterre.

S. K. Halgamuge and M. Glesner (1993). The Fuzzy Neural Controller FuNe II with a New Adaptive Defuzzification Strategy Based on CBAD Distributions. In Proc. First European Congress on Fuzzy and Intelligent Technologies (EUFIT93), pages 852–855, Aachen.

S. K. Halgamuge and M. Glesner (1994). Neural Networks in Designing Fuzzy Systems for Real World Applications. Fuzzy Sets and Systems, 65:1–12.

S. K. Halgamuge, A. Mari and M. Glesner (1994). Fast Perceptron Learning by Fuzzy Controlled Dynamic Adaption of Network Parameters. In [Kruse et al., 1994], pages 129–139. Vieweg, Braunschweig.

C. J. Harris, C. G. Moore and M. Brown (1993). Intelligent Controll: Aspects of fuzzy logic and neural networks. World Scientific Publishing, Singapore.

N. Hataoka, A. Amano, T. Aritsuka and A. Ichikawa (1990). Large vocabulary speed recognition using neural-fuzzy and concept networks. In Int. Conf. on Acoustics, Speech and Signal Processing, pages 513–516.

W. Hauptmann and K. Heesche (1995). A Neural Net Topologie for Bidirectional Fuzzy-Neuro Transformation. In Proc. IEEE Int. Conf. on Fuzzy Systems 1995 , pages 1511–1518, Yokohama.

H. Hayashi, J. Nasu, M. Strefezza and Y. Dote (1991). Neuro Fuzzy Transmission Control for Automobile. In [Dağlĭ et al., 1991], pages 283–288.

I. Hayashi, H. Nomura and N. Wakami (1989). Artificial-Neural-Network-Driven Fuzzy Control and its Application to the Learning of Inverted Pendulum System. In Proc. 3rd IFSA Congress, pages 610–613.

I. Hayashi, H. Nomura, H. Yamasaki and N. Wakami (1992a). Construction of Fuzzy Inference Rules by Neural Network Driven Fuzzy Reasoning and Neural Network Driven Fuzzy Reasoning With Learning Functions. Int. J. Approximate Reasoning, 6:241– 266.

Y. Hayashi, J. J. Buckley and E. Czogala (1992b). Fuzzy neural network with fuzzy signals and weights. In Proc. of the 1992 Int. Joint Conf. on Neural Networks (IJCNN-92), pages 696–701, Baltimore.

Y. Hayashi, J. J. Buckley and E. Czogala (1993). Fuzzy neural networks with fuzzy signals and weights. Int. Journal on Intelligent Systems, 8:527–537.

Y. Hayashi and A. Imura (1990). Fuzzy Neural Expert System with Automated Extraction of Fuzzy If-Then Rules from a Trained Neural Network. In First Int. Symposium on Uncertainty Modeling and Analysis, pages 489–494.

Y. Hayashi, E. Czogala and J. J. Buckley (1992c). Fuzzy Neural Controller. In Proc. IEEE Int. Conf. on Fuzzy Systems 1992 , pages 197–202, San Diego.

H. Hellendorn and R. Baudrexl (1995). Fuzzy-Neural Traffic Contol and Forecasting. In Proc. IEEE Int. Conf. on Fuzzy Systems 1995 , pages 2187–2194, Yokohama.

J. Hollatz (1995). Neuro-Fuzzy in Legal Reasoning. In Proc. IEEE Int. Conf. on Fuzzy Systems 1995 , pages 655–662, Yokohama.

J. Holtzman (1990). Coping with broadband traffic uncertainties: statistical uncertainty, fuzziness, neural networks. In IEEE Global Telecommunications Conf. and Exhibition 1990 - ’Communications: Connecting the Future’, Vol.1 , pages 7–11.

J. Hopf and F. Klawonn (1994). Learning the Rule Base of Fuzzy Controller by a Genetic Algorithm. In [Kruse et al., 1994], pages 63–73, Braunschweig. Vieweg.

F. Höppner, F. Klawonn and R. Kruse (1996). Fuzzy–Clustering–Methoden. Computational Intelligence. Vieweg, Braunschweig.

H. Ichihashi (1991). Iterative Fuzzy Modelling and a Hierarchical Network. In R. Lowen and M. Roubens, eds.: Proc. 4th IFSA Congress, volume Engineering, pages 49–52, Brussels.

H. Ichihashi, N. Harada and K. Nagasaka (1995). Selection of Optimum Number of Hidden Layers in Neuro-Fuzzy GMDH . In Proc. IEEE Int. Conf. on Fuzzy Systems 1995 , pages 1519–1526, Yokohama.

H. Ichihashi and I. Turksen (1995). Neuro-Fuzzy Data Analysis and Its Future Directions. In Proc. IEEE Int. Conf. on Fuzzy Systems 1995 , pages 1919–1925, Yokohama.

N. Imasaki, S. Kubo and S. Nakai (1995). Elevator Group Control System Tuned by a Fuzzy Neural Network Applied Method. In Proc. IEEE Int. Conf. on Fuzzy Systems 1995 , pages 1735–1740, Yokohama.

H. Ishibuchi, K. Morioka and H. Tanaka (1994). A fuzzy neural network with trapezoid fuzzy weights. In Proc. IEEE Int. Conf. on Fuzzy Systems 1994 , pages 227–233, Orlando.

H. Ishibuchi, H. Okada and H. Tanaka (1992a). An architecture on neural networks for input vectors of fuzzy numbers. In Proc. IEEE Int. Conf. on Fuzzy Systems 1992 , pages 1293–1300, San Diego.

H. Ishibuchi, H. Okada and H. Tanaka (1992b). Interpolation of fuzzy of fuzzy if-then rules by neural networks. In Proc. 2nd Int. Conf. on Fuzzy Logic and Neural Networks (IIZUKA’92), pages 337–340, Iizuka.

H. Ishibuchi, H. Okada and H. Tanaka (1993a). Fuzzy neural networks with fuzzy weights and fuzzy biases. In Proc. IEEE Int. Conf. on Neural Networks 1993 , pages 1650– 1655, San Francisco.

H. Ishibuchi, H. Tanaka and H. Okada (1993b). An architecture of neural networks with interval weights and its application to fuzzy regession analysis. Fuzzy Sets and Systems, 57:27–40.

T. Iwata, K. Machida and Y. Toda (1990). Fuzzy control using neural network techniques. In Int. Joint Conf. on Neural Networks 1990, Vol.3 , pages 365–370.

J.-S. R. Jang (1991a). Fuzzy Modeling Using Generalized Neural Networks and Kalman Filter Algorithm. In Proc. of the Ninth National Conf. on Artificial Intelligence (AAAI-91), pages 762–767.

J.-S. R. Jang (1991b). Rule Extraction Using Generalized Neural Networks. In R. Lowen and M. Roubens, eds.: Proc. 4th IFSA Congress, volume Artificial Intelligence, pages 82–85, Brussels.

J.-S. R. Jang (1992). Self-learning Fuzzy Controller Based on Temporal Back-Propagation. IEEE Trans. Neural Networks, 3:714–723.

J.-S. R. Jang (1993). ANFIS: Adaptive-Network-Based Fuzzy Inference Systems. IEEE Trans. Systems, Man & Cybernetics, 23:665–685.

J.-S. R. Jang and C.-T. Sun (1995). Neuro–Fuzzy Modelling and Control. Proc. of the IEEE, March 1995.

E. A. Johnson and C.-H. Wu (1994). A Real–Time Fuzzy Logic–Based Neural Facial Feature Extraction Technique. In Proc. IEEE Int. Conf. on Fuzzy Systems 1994 , pages 268–273, Orlando.

A. Kandel, ed. (1987). Fuzzy Expert Systems. Addison–Wesley, Reading, MA.

S. V. Kartalopoulos (1996). Understanding neural networks and Fuzzy Logic: Basic Concepts and Applications. IEEE Press, New York.

N. K. Kasabov (1995). Hybrid Fuzzy Connectionist Rule-based Systems and the Role of Fuzzy Rules Extraction. In Proc. IEEE Int. Conf. on Fuzzy Systems 1995 , pages 49–56, Yokohama.

J. Keller, R. Krishnapuram and F. Rhee (1992a). Evidence aggregation networks for fuzzy logic inference. IEEE Trans. Neural Networks, 3:761–769.

J. M. Keller (1991). Experiments on Neural Network Architectures for Fuzzy Logic. In [Lea and Villareal, 1991], pages 201–216.

J. M. Keller and H. Tahani (1992a). Backpropagation Neural Networks for Fuzzy Logic. Information Sciences, 62:205–221.

J. M. Keller and H. Tahani (1992b). Implementation of Conjunctive and Disjunctive Fuzzy Logic Rules with Neural Networks. Int. J. Approximate Reasoning, 6:221–240.

J. M. Keller, R. R. Yager and H. Tahani (1992b). Neural Network Implementation of Fuzzy Logic. Fuzzy Sets and Systems, 45:1–12.

J. Keller and D. Hunt (1985). Incorporating Fuzzy Membership Function into the Perceptron Algorithm. IEEE Trans. Pattern Analysis and Machine Intelligence, 7:693–699.

E. Khan and P. Venkatapuram (1993). Neufuz: Neural Network Based Fuzzy Logic Design Algorithms. In Proc. IEEE Int. Conf. on Fuzzy Systems 1993 , pages 647–654, San Francisco.

K. Kiguchi and T. Fukuda (1995). Fuzzy Neural Controller for Robot Manipulator Force Control. In Proc. IEEE Int. Conf. on Fuzzy Systems 1995 , pages 869–874, Yokohama.

J. Kinzel, F. Klawonn and R. Kruse (1994). Modifications of Genetic Algorithms for Designing and Optimizing Fuzzy Controllers. In Proc. IEEE Conference on Evolutionary Computation, pages 28–33, Orlando. IEEE.

F. Klawonn, D. Nauck and R. Kruse (1995). Generating Rules from Data by Fuzzy and Neuro–Fuzzy Methods. In Proc. Fuzzy–Neuro–Systeme’95 , pages 223–230, Darmstadt.

S.-G. Kong and B. Kosko (1990). Comparison of fuzzy and neural truck backer-upper control systems. In Int. Joint Conf. on Neural Networks 1990, Vol.3 , pages 349–358.

B. Kosko (1986). Fuzzy Cognitive Maps. Int. J. Man-Machine Studies, 24:65–75.

B. Kosko (1987). Fuzzy Associative Memories. In [Kandel, 1987]. Addison–Wesley, Reading, MA.

B. Kosko (1992). Neural Networks and Fuzzy Systems. A Dynamical Systems Approach to Machine Intelligence. Prentice–Hall, Englewood Cliffs.

B. Krause, C. von Altrock, K. Limper and W. Schäfers (1994). A Neuro–Fuzzy Adaptive Control Strategy for refuse incineration plants. Fuzzy Sets and Systems, 63:329–338.

R. Krishnapuram and J. Lee (1992). Fuzzy-Set-Based Hierarchichal Networks for Information Fusion in Computer Vision. Neural Networks, 3:335–350.

R. Kruse, J. Gebhardt and R. Palm, eds. (1994). Fuzzy Systems in Computer Science. Vieweg, Braunschweig.

R. Kruse and D. Nauck (1995a). Learning Methods for Fuzzy Systems. In Proc. Fuzzy– Neuro–Systeme’95 , pages 7–22, Darmstadt.

R. Kruse and D. Nauck (1995b). Neuronale Fuzzy–Systeme. In G. Dorffner, K. Möller, G. Paa”s and S. Vogel, eds.: Konnektionismus und Neuronale Netze. Beiträge zur Herbstschule HeKoNN95 , number 272 in GMD–Studien, pages 1–10, Münster/Westf. GMD–Forschungszentrum Informationstechnik GmbH.

R. Kruse, D. Nauck and F. Klawonn (1995). Neuronale Fuzzy–Systeme. Spektrum der Wissenschaft, Juli(Heft 6/1995):34–41.

D. Kuncicky (1989). A Fuzzy Interpretation of Neural Networks. In Proc. 3rd IFSA Congress, pages 113–116.

R. Langari and L. Wang (1995). Fuzzy Models, Modular Networks, and Hybrid Learning. In Proc. IEEE Int. Conf. on Fuzzy Systems 1995 , pages 1291–1298, Yokohama.

R. N. Lea and J. Villareal, eds. (1991). Proc. of the Second Joint Technology Workshop on Neural Networks and Fuzzy Logic, Lyndon B. Johnson Space Center, Houston, Texas. NASA.

C.-C. Lee (1990). A Self-Learning Rule-Based Controller Employing Approximate Reasoning and Neural Network Concepts. Int. J. Intell. Syst., 5.

M. Lee and H. Takagi (1993). Integrating Design Stages of Fuzzy Systems using Genetic Algorithms. In Proc. IEEE Int. Conf. on Fuzzy Systems 1993 , pages 612–617, San Francisco.

S. C. Lee and E. T. Lee (1975). Fuzzy neural networks. Int. Journal on Math. Bioscience, 23:151–177.

S. Lee and E. Lee (1974). Fuzzy sets and neural networks. J. Cybern., 4:83–103.

C. J. Li and J. C. Tzou (1992). Neural Fuzzy Point Processes. Fuzzy Sets and Systems, 48:297–303.

W. Li (1994). Optimization of a fuzzy controller using neural network. In Proc. IEEE Int. Conf. on Fuzzy Systems 1994 , pages 223–227, Orlando.

W. Li (1995). Neuro-Fuzzy Systems for Intelligent Robot Navigation and Control Under Uncertainty. In Proc. IEEE Int. Conf. on Fuzzy Systems 1995 , pages 1747–1754, Yokohama.

C. T. Lin and C. S. G. Lee (1993). Reinforcement Structure/Parameter Learning for Neural-Network-Based Fuzzy Logic Control Systems. In Proc. IEEE Int. Conf. on Fuzzy Systems 1993 , pages 88–93, San Francisco.

C.-J. Lin and C.-T. Lin (1995). Reinforcement Learning for ART-Based Fuzzy Adaptive Learning Control Networks. In Proc. IEEE Int. Conf. on Fuzzy Systems 1995 , pages 1299–1306, Yokohama.

C.-T. Lin and C. S. G. Lee (1991). Neural-Network-Based Fuzzy Logic Control and Decision System. IEEE Trans. Computers - Special Issue on Artificial Neural Networks, 40:1320–1336.

W.-M. Lippe, T. Feuring and A. Tenhagen (1994a). A fuzzy controlled, parallel coordinate descent in a backpropagation net. In Proc. World Congress on Neural Networks 1994 (WCNN’94), pages 340–345, San Diego.

W.-M. Lippe, T. Feuring and A. Tenhagen (1994b). A Hybrid Learning Rule for a Feedforward Network. Int. Journal on Artificial Intelligence Tools, 3:407–416.

D. P. Mandal and H. Tanaka (1995). Use of Fuzzy-If-Then Rules for Pattern Classification. In Proc. IEEE Int. Conf. on Fuzzy Systems 1995 , pages 1649–1656, Yokohama.

S. Mitra and S. Pal (1995). Fuzzy Multi–Layer Perceptron, Inferencing and Rule Generation. IEEE Trans. Neural Networks, 6:51–63.

S. Mitra (1994). Fuzzy MLP Based Expert System for Medical Diagnosis. Fuzzy Sets and Systems, 64.

S. Mitra and L. Kuncheva (1995). Improving Classification Performance Using Fuzzy MLP and Two–Level Selective Partitioning of the Feature Space. Fuzzy Sets and Systems, 70:1–13.

T. Miyoshi, S. Tano, Y. Kato and T. Arnould (1993). Operator Tuning in Fuzzy Production Rules using Neural Networks. In Proc. IEEE Int. Conf. on Fuzzy Systems 1993 , pages 641–646, San Francisco.

F. Mondada, E. Franzi and P. Ienne (1993). Mobile Robot Miniaturisation: A Tool for Investigation in Control Algorithms. In Proc. Third Int. Symposium on Experimental Robotics, Kyoto.

K. Nakamura (1995). Applications of Fuzzy Logical Thinking in Japan: Current and Future. In Proc. IEEE Int. Conf. on Fuzzy Systems 1995 , pages 1077–1082, Yokohama.

H. Narazaki and A. L. Ralescu (1991). A Synthesis Method for Multi-Layered Neural Network using Fuzzy Sets. In IJCAI-91: Workshop on Fuzzy Logic in Artificial Intelligence, pages 54–66, Sydney.

K. S. Narenda (1992). Adaptive Control of Dynamical Systems using Neural Networks. In [White and Sofge, 1992], pages 141–183. Van Nostrand Reinhold.

D. Nauck (1993). NEFCON-I: Eine Simulationsumgebung für Neuronale Fuzzy-Regler. In 1. GI-Workshop Fuzzy-Systeme ’93 , Braunschweig.

D. Nauck (1994a). Building Neural Fuzzy Controllers with NEFCON–I . In [Kruse et al., 1994], pages 141–151. Vieweg, Braunschweig.

D. Nauck (1994b). Building Neural Fuzzy Controllers with NEFCON–I . In R. Kruse, J. Gebhardt and R. Palm, eds.: Fuzzy Systems in Computer Science, pages 141–151. Vieweg, Braunschweig.

D. Nauck (1994c). Fuzzy Neuro Systems: An Overview. In [Kruse et al., 1994], pages 91–107. Vieweg, Braunschweig.

D. Nauck (1994d). Fuzzy Neuro Systems: An Overview. In R. Kruse, J. Gebhardt and R. Palm, eds.: Fuzzy Systems in Computer Science, pages 91–107. Vieweg, Braunschweig.

D. Nauck (1994e). A Fuzzy Perceptron as a Generic Model for Neuro–Fuzzy Approaches. In Proc. Fuzzy–Systeme’94 , Munich.

D. Nauck (1994f). Modellierung Neuronaler Fuzzy–Regler. PhD thesis, Technische Universität Braunschweig.

D. Nauck (1995). Beyond Neuro–Fuzzy: Perspectives and Directions. In Proc. Third European Congress on Intelligent Techniques and Soft Computing (EUFIT95), pages 1159–1164, Aachen.

D. Nauck, F. Klawonn and R. Kruse (1992). Fuzzy Sets, Fuzzy Controllers, and Neural Networks. Wissenschaftliche Zeitschrift der Humboldt-Universität zu Berlin, R. Medizin, 41(4):99–120.

D. Nauck, F. Klawonn and R. Kruse (1993). Combining Neural Networks and Fuzzy Controllers. In E. P. Klement and W. Slany, eds.: Fuzzy Logic in Artificial Intelligence (FLAI93), pages 35–46, Berlin. Springer–Verlag.

D. Nauck, F. Klawonn and R. Kruse (1994a). Neuronale Netze und Fuzzy–Systeme. Vieweg, Wiesbaden.

D. Nauck, F. Klawonn and R. Kruse (1994b). Neuronale Netze und Fuzzy–Systeme (Neural Networks and Fuzzy Systems [in German]). Vieweg, Wiesbaden.

D. Nauck, F. Klawonn and R. Kruse (1996a). Foundations of Neuro–Fuzzy Systems. Wiley, Chichester. To be published.

D. Nauck, F. Klawonn and R. Kruse (1996b). Neuronale Netze und Fuzzy–Systeme, 2. erweiterte Auflage. Vieweg, Wiesbaden.

D. Nauck and R. Kruse (1992a). Interpreting Changes in the Fuzzy Sets of a Self-Adaptive Neural Fuzzy Controller. In Proc. Second Int. Workshop on Industrial Applications of Fuzzy Control and Intelligent Systems (IFIS’92), pages 146–152, College Station, Texas.

D. Nauck and R. Kruse (1992b). A Neural Fuzzy Controller Learning by Fuzzy Error Propagation. In Proc. Workshop of North American Fuzzy Information Processing Society (NAFIPS92), pages 388–397, Puerto Vallarta.

D. Nauck and R. Kruse (1993). A Fuzzy Neural Network Learning Fuzzy Control Rules and Membership Functions by Fuzzy Error Backpropagation. In Proc. IEEE Int. Conf. on Neural Networks 1993 , pages 1022–1027, San Francisco.

D. Nauck and R. Kruse (1994a). Choosing Appropriate Neuro-Fuzzy Models. In Proc. Second European Congress on Fuzzy and Intelligent Technologies (EUFIT94), pages 552–557, Aachen.

D. Nauck and R. Kruse (1994b). NEFCON–I: An X–Window based Simulator for Neural Fuzzy Controllers. In Proc. IEEE Int. Conf. Neural Networks 1994 at IEEE WCCI’94 , pages 1638–1643, Orlando.

D. Nauck and R. Kruse (1995). NEFCLASS – A Neuro–Fuzzy Approach for the Classification of Data. In K. George, J. H. Carrol, E. Deaton, D. Oppenheim and J. Hightower, eds.: Applied Computing 1995. Proc. of the 1995 ACM Symposium on Applied Computing, Nashville, Feb. 26–28 , pages 461–465. ACM Press, New York.

D. Nauck and R. Kruse (1996a). Designing Neuro–Fuzzy Systems Through Backpropagation. In W. Pedrycz, ed.: Fuzzy Modelling: Paradigms and Practice. Kluwer.

D. Nauck and R. Kruse (1996b). Neuro–Fuzzy Classification with NEFCLASS. In P. Kleinschmidt, A. Bachem, U. Derigs, D. Fischer, U. Leopold-Wildburger and R. Möhring, eds.: Operations Research Proceedings 1995 , pages 294–299, Berlin. Springer–Verlag.

D. Nauck and R. Kruse (1996c). Neuro–Fuzzy Systems Research and Applications outside of Japan (in Japanese). In M. Umano, I. Hayashi and T. Furuhashi, eds.: Fuzzy– Neural Networks (in Japanese), Soft Computing Series. Asakura Publ., Tokyo.

D. Nauck, R. Kruse and R. Stellmach (1995). New Learning Algorithms for the Neuro– Fuzzy Environment NEFCON–I . In Proc. Neuro–Fuzzy–Systeme’95 , pages 357–364, Darmstadt.

D. Nauck, U. Nauck and R. Kruse (1996c). Generating Classification Rules with the Neuro–Fuzzy System NEFCLASS. In Proc. Biennial Conference of the North American Fuzzy Information Processing Society NAFIPS’96 , Berkeley. to appear.

H. Nomura, I. Hayashi and N. Wakami (1992). A Learning Method of Fuzzy Inference Rules by Descent Method. In Proc. IEEE Int. Conf. on Fuzzy Systems 1992 , pages 203–210, San Diego.

A. Nowé and R. Vepa (1993). A Reinforcement Learning Algorithm based on ‘Safety’. In E. P. Klement and W. Slany, eds.: Fuzzy Logic in Artificial Intelligence (FLAI93), pages 47–58, Berlin. Springer–Verlag.

M. O’Hagan (1990). A fuzzy neuron based upon maximum entropy ordered weighted averaging. In Int. Conf. on Information Processing and Management of Uncertainty in Knowledge-Based Systems (IPMU’90), pages 598–609.

S. Pal and S. Mitra (1992). Multi–layer Perceptron, Fuzzy Sets and Classification. IEEE Trans. Neural Networks, 3:683–697.

A. Patrikar and J. Provence (1990). A self-organizing controller for dynamic processes using neural networks. In Int. Joint Conf. on Neural Networks 1990, Vol.3 , pages 359–364.

W. Pedrycz (1990). Fuzzy Sets and Neurocomputations: Knowledge Representation and Processing in Intelligent Controllers. In 5th IEEE Int. Symposium on Intelligent Control, Vol.1 , pages 626–630.

W. Pedrycz (1991a). Neurocomputations in Relational Systems. IEEE Trans. Pattern Analysis and Machine Intelligence, 13:289–297.

W. Pedrycz (1991b). A Referential Scheme of Fuzzy Decision Making and its Neural Network Structure. IEEE Trans. Systems, Man & Cybernetics, 21:1593–1604.

W. Pedrycz and H. C. Card (1992). Linguistic Interpretation of Self-Organizing Maps. In Proc. IEEE Int. Conf. on Fuzzy Systems 1992 , pages 371–378, San Diego.

W. Pedryzc (1993). Fuzzy Neural Networks and Neurocomputation. Fuzzy Sets and Systems, 56:1–28.

W. Pedryzc (1994). Logic–Based Neurons: Extensions, Uncertainty Representation and Development of Fuzzy Controllers. Fuzzy Sets and Systems, 66:251–266.

A. Prieto, G. Goos and J. Hartmanis, eds. (1991). Artificial Neural Networks Int. Workshop IWANN’91, Granada, Spain, sep 1991 Proceedings, Berlin. Springer–Verlag.

W. Z. Qiao, W. P. Zhuang, T. H. Heng and S. S. Shan (1992). A Rule Self-Regulating Fuzzy Controller. Fuzzy Sets and Systems, 47:13–21.

P. Ramamoorthy and S. Huang (1991). Cerebellar Model Articulation Controller Neural Network – A Simple Fuzzy Expert System in Disguise?. In [Dağlĭ et al., 1991], pages 261–266.

A. Rueda and W. Pedrycz (1994). A Hierachical Fuzzy–Neural–PD Controller for Robot Manipulators. In Proc. IEEE Int. Conf. on Fuzzy Systems 1994 , pages 672–677, Orlando.

E. Sanchez (1990). Fuzzy Connectionist Expert Systems. In Proc. 1st Int. Conf. on Fuzzy Logic & Neural Networks (IIZUKA’90), pages 31–35, Iizuka.

T. Sarkodie-Gyan and H.-P. Willumeit (1995). Neuro-Fuzzy Based Autonomous Vehicles. In Proc. IEEE Int. Conf. on Fuzzy Systems 1995 , pages 855–862, Yokohama.

H. Schreiber and S. Heine (1994). Einsatz von Neuro–Fuzzy–Technologien für die Prognose des Elektroenergieverbrauches an “besonderen” Tagen. In Proc. 4. Dortmunder Fuzzy– Tage, Dortmund.

S. Sekine, N. Imasaki and E. Tsunekazu (1995). Application of Fuzzy Neural Network Control to Automatic Train Operation and Tuning of Its Control Rules. In Proc. IEEE Int. Conf. on Fuzzy Systems 1995 , pages 1741–1746, Yokohama.

S. Shao (1988). Fuzzy Self-Organizing Controller and its Application for Dynamic Processes. Fuzzy Sets and Systems, 26:151–164.

L. Shiue and R. Grondin (1987). On designing fuzzy learning neural-automata. In IEEE Int. Conf. on Neural Networks 1987, Vol.2 , pages 299–307.

P. Simpson (1991). Fuzzy Min-Max Classification with Neural Networks. J. Knowledge Engineering, 4:1–9.

P. Simpson (1992a). Fuzzy Min-Max Neural Networks – Part 1: Classification. IEEE Trans. Neural Networks, 3:776–786.

P. Simpson (1992b). Fuzzy Min-Max Neural Networks – Part 2: Clustering. IEEE Trans. Fuzzy Systems, 1:32–45.

H. Steinmüller (1994). Fuzzy Control und NeuroFuzzy bei Waschautomaten. In H.-J. Zimmermann and C. von Altrock, eds.: Fuzzy Logic. Band2: Anwendungen, pages 155–168. Oldenbourg Verlag, München.

H. Steinmüller and O. Wick (1993). Fuzzy and Neuro Fuzzy Applications in European Wahing Machines. In Proc. First European Congress on Fuzzy and Intelligent Technologies (EUFIT93), pages 1031–1035, Aachen.

R. Stellmach (1995). NEFCON–I: Entwurf und Implementierung einer Erweiterung des Softwaretools NEFCON–I für Neuronale Fuzzy–Regler. Diplomarbeit, Technische Universität Braunschweig.

S. P. Stoeva (1992). A Weight-Learning Algorithm for Fuzzy Production Systems with Weighting Coefficients. Fuzzy Sets and Systems, 48:87–97.

S. M. Sulzberger, N. N. Tschichold-Gürman and S. J. Vestli (1993). FUN: Optimization of Fuzzy Rule Based Systems using Neural Networks. In Proc. IEEE Int. Conf. on Neural Networks 1993 , pages 312–316, San Francisco.

C.-T. Sun and J.-S. R. Jang (1992). Adaptive Network Based Fuzzy Classification. In Proc. of the Japan–U.S.A. Symposium on Flexible Automation. (Forthcoming).

C.-T. Sun and J.-S. Jang (1993). A Neuro-Fuzzy Classifier and Its Applications. In Proc. IEEE Int. Conf. on Neural Networks 1993 , pages 94–98, San Francisco.

R. Swiniarski, A. Knafel and M. Zaremba (1991). Neural-fuzzy variable structure control systems. Advances in Modeling & Simulation, 25:51–64.

H. Takagi (1990). Fusion Technology of Fuzzy Theory and Neural Networks - Survey and Future Directions. In Proc. 1st Int. Conf. on Fuzzy Logic & Neural Networks (IIZUKA’90), pages 13–26.

H. Takagi (1992). Application of Neural Networks and Fuzzy Logic to Consumer Products. In Proc. Int. Conf. on Industrial Fuzzy Electronics, Control, Instrumentation, and Automation (IECON’92), volume 3, pages 1629–1639, San Diego.

H. Takagi (1995). Applications of Neural Networks and Fuzzy Logic to Consumer Products. In [Yen et al., 1995], pages 93–104. IEEE Press.

H. Takagi and I. Hayashi (1991). NN–Driven Fuzzy Reasoning. Int. J. Approximate Reasoning, 5:191–212.

H. Takagi and M. Lee (1993). Neural Networks and Genetic Algorithms. In E. P. Klement and W. Slany, eds.: Fuzzy Logic in Artificial Intelligence (FLAI93), pages 68–79, Berlin. Springer–Verlag.

H. Takagi, N. Suzuki, T. Koda and Y. Kojima (1992). Neural Networks Designed on Approximate Reasoning Architecture and Their Applications. IEEE Trans. Neural Networks, 3(5):752–760.

H. Takahashi and H. Minami (1989). Subjective Evaluation Modeling using Fuzzy Logic and a Neural Network. In Proc. 3rd IFSA Congress, pages 520–523.

Z. Tang, M. Komori, O. Ishizuka, K. Tanno and H. Matsumoto (1995). An Adaptive ULR Fuzzy Contoller Through Reinforcement Learning. In Proc. IEEE Int. Conf. on Fuzzy Systems 1995 , pages 1307–1314, Yokohama.

R. Thawonmas, S. Abe and M.-S. Lan (1995). Tuning of a Fuzzy Classifier by Solving Inequalities. In Proc. IEEE Int. Conf. on Fuzzy Systems 1995 , pages 1657–1664, Yokohama.

N. Tschichold-Gürman (1995). Generation and Improvement of Fuzzy Classifiers with Incremental Learning using Fuzzy RuleNet. In K. George, J. H. Carrol, E. Deaton, D. Oppenheim and J. Hightower, eds.: Applied Computing 1995. Proc. of the 1995 ACM Symposium on Applied Computing, Nashville, Feb. 26–28 , pages 466–470. ACM Press, New York.

N. Tschichold-Gürman (1996). RuleNet – A New Knowledge–Based Artificial Neural Network Model with Application Examples in Robotics. PhD thesis, ETH Zürich.

N. Tschichold-Gürman and V. Dabija (1993). Meaning-Based Handling of Don’t Care Attributes in Artificial Neural Networks. In Proc. IEEE Int. Conf. on Neural Networks 1993 , pages 281–286, San Francisco.

N. Tschichold-Gürman, M. Ghazvini and D. Diez (1992). M-RCE: A Self-Configuring ANN with Rule-Extraction Capabilities. In Proc. of 1992 Int. Conf. on Artificial Neural Networks (ICANN-92), Brighton.

A. V. Vasilakos and K. C. Zikidis (1995). A.S.A.F.ES.2: A Novel, Neuro-Fuzzy Architecture for Fuzzy Computing, Based on Functional Reasoning. In Proc. IEEE Int. Conf. on Fuzzy Systems 1995 , pages 671–678, Yokohama.

P. Vuorimaa (1994). Fuzzy Self–Organizing Map. Fuzzy Sets and Systems, 66:223–231.

B. Wang and G. Vachtsevanos (1990). Fuzzy Associative Memories: Identification and Control of Complex Systems. In 5th IEEE Int. Symposium on Intelligent Control, volume 2, pages 910–915.

P. J. Werbos (1992a). Approximate Dynamic Programming for Real-Time Control and Neural Modeling. In [White and Sofge, 1992], pages 493–526. Van Nostrand Reinhold.

P. J. Werbos (1992b). Neurocontrol and Fuzzy Logic: Connections and Designs. Int. J. Approximate Reasoning, 6:185 – 220.

P. J. Werbos (1992c). Neurocontrol and Supervised Learning: An Overview and Evaluation. In [White and Sofge, 1992], pages 65–89. Van Nostrand Reinhold.

P. J. Werbos (1992d). Neurocontrol: Where it is Going and Why it is Crucial. Artificial Neural Networks, 2:61–68.

D. A. White and D. A. Sofge, eds. (1992). Handbook of Intelligent Control. Neural, Fuzzy, and Adaptive Approaches. Van Nostrand Reinhold, New York.

G. Wöhlke (1994). A Neuro–Fuzzy based System Architecture for the Intelligent Control of Multi–Finger Robot Hands. In Proc. IEEE Int. Conf. on Fuzzy Systems 1994 , pages 64–69, Orlando.

F. Wong, P. Wang and H. Teh (1991). A stock selection strategy using fuzzy neural networks. Computer Science in Economics and Management, 4:77–89.

R. R. Yager and D. P. Filev (1992a). Adaptive Defuzzification for Fuzzy Logic Controllers. BUSEFAL, 49:50–57.

R. R. Yager and D. P. Filev (1992b). Adaptive Defuzzification for Fuzzy System Modelling. In Proc. Workshop of North American Fuzzy Information Processing Society (NAFIPS92), pages 135–142, Puerto Vallarta.

R. R. Yager and L. A. Zadeh, eds. (1994). Neural Networks and Soft Computing. Van Nostrand Reinhold.

R. Yager (1988). On the interface of fuzzy sets and neural networks. In Int. Workshop on Fuzzy System Applications (IIZUKA’88), pages 215–216.

T. Yamaguchi, K. Goto, T. Takagi, K. Doya and T. Mita (1992). Intelligent Control of a Flying Vehicle using Fuzzy Associative Memory System. In Proc. IEEE Int. Conf. on Fuzzy Systems 1992 , pages 1139–1149, San Diego.

T. Yamaguchi, N. Imasaki and K. Haruki (1990). Fuzzy Rule Realization on Associative Memory System. In Int. Joint Conf. on Neural Networks 1990, Vol.2 , pages 720–723.

T. Yamakawa (1989). A membership function circuit and its applications to a singletonconsequent fuzzy logic controller and a fuzzy neuron. In 5th Fuzzy Syst. Symp., pages 13–18.

T. Yamakawa (1990). Pattern Recognition Hardware System Employing a Fuzzy Neuron. In Proc. 1st Int. Conf. on Fuzzy Logic & Neural Networks (IIZUKA’90), pages 943– 948, Iizuka.

T. Yamakawa and M. Furukawa (1992). A Design of Membership Functions for a Fuzzy Neuron Using Example Based Learning. In Proc. IEEE Int. Conf. on Fuzzy Systems 1992 , pages 75–82, San Diego.

T. Yamakawa and S. Tomoda (1989). A Fuzzy Neuron and its Application to Pattern Recognition. In J. C. Bezdek, ed.: Proc. 3rd IFSA Congress, pages 30–38, Seattle.

T. Yamakawa and S. Tomoda (1992). A Neo Fuzzy Neuron and its Applications to System Identification and Prediction of the System Behaivour. In Proc. 2nd Int. Conf. on Fuzzy Logic and Neural Networks (IIZUKA’92), pages 477–483, Iizuka.

Q. Yang and V. Bhargava (1990). Building expert systems by a modified perception network with rule-transfer algorithms. In Int. Joint Conf. on Neural Networks 1990, Vol.2 , pages 77–82.

C.-C. Yao and Y.-H. Kuo (1995). A Fuzzy Neural Network Model with Three-layerd Structure. In Proc. IEEE Int. Conf. on Fuzzy Systems 1995 , pages 1503–1510, Yokohama.

J. Yen, R. Langari and L. A. Zadeh, eds. (1995). Industrial Applications of Fuzzy Logic and Intelligent Systems. IEEE Press, Piscataway.

J. Yen, H. Wang and W. C. Daugherty (1992). Design Issues of a Reinforcment-based Self-Learning Fuzzy Controller for Petrochemical Process Control. In Proc. Workshop of North American Fuzzy Information Processing Society (NAFIPS92), pages 135–142, Puerto Vallarta.