PROCEEDINGS OF THE 2NDINTERNATIONAL CONFERENCE ON

FUZZY LOGIC AND NEURAL NETWORKS

[ IIZUKA '92 ]July. 17-22

Vol .1

I I ISOFT

CONTENTS

OPENING LECTURES

1. Interpolative Reasoning as a Common Basis for Inference in Fuzzy Logic,Neural Network : Theory and the Calculus of Fuzzy If-Then Rules 1

Prof. Lotfi A. ZadehUniversity of California, Berkeley (U.S.A.)

2 . The Physiology of Perception : Functional Architectures of BiologicalSensorimotor control Systems 3

Prof. Walter J, FreemanUniversity of California, Berkeley (U.S.A.)

3 . Towards Developing a Human-like Computer 9Prof. Gen MatsumotoElectrotechnical Laboratory (Japan)

PLENARY LECTURES

1. Genetic Algorithms, Neural Networks and Fuzzy Logic Systems 17Prof. Elie SanchezInstitut Mediterranean de Technologie (France)

2. Chaos in Fuzzy Systems and Signals 21Prof. Horia-Nicolai TeodorescuPolytechnic Institute of Iasi (Romania)

3 . Chaos and Fuzzy Representations of Dynamical Systems 51Prof. Phil DiamondUniversity of Queensland (Australia)

4 . Adaptive Fuzzy Systems 59Prof. Bart KoskoUniversity of Southern California (U.S.A.)

5. Functional Chaotic Devices 61Dr. Peter DavisATR Optical and Radio Communications Research Laboratories (Japan)

6. Adaptive Models for the Defuzzification Process 65Prof. Ronald R. YagerIona College (U.S.A.)

INVITED/ORDINARY SESSIONS

A-l FUZZY NEURAL NETWORKS PART I (INVITED)Organizer : James J. Buckley

The University of Alabama, Birmingham (U.S.A.)

1. Direct Fuzzification of Neural Network and Fuzzified Delta Rule 73Yoichi Hayashi*, James J. Buckley** and Ernest Czogala**** Ibaraki University (Japan)

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** The University of Alabama, Birmingham (U.S.A.)•••Technical University of Silesia (U.S.A.)

2 . Two-Degree-of-Freedom Fuzzy Model using Associative Memories 77Toru Yamaguchi, Kenji Goto and Tomohiro TakagiLaboratory for International Fuzzy Engineering Research (Japan)

3 . Learning in Fuzzy Neural Networks Utilizing Additive Hybrid Operators....85James M. Keller and Zhihong ChenUniversity of Missouri-Columbia (U.S.A.)

4 . Approximations Between Nets, Controllers, Expert Systems andProcesses 89

James J. BuckleyThe University of Alabama, Birmingham (U.S.A.)

A-2 FUZZY NEURAL NETWORKS PART II

1. Automatic Control of Sewerage Pumpstation by Using Fuzzy Controlsand Neural Networks 91

Hong Chen, Masaharu Mizumoto and Yun-fei LingOsaka Electro-Communication University (Japan)

2 . Learning of Expert's Knowledge by Neural Network and Deduction ofFuzzy Rules by Powell's Method 95

Hiroshi Isshiki and Hideichi EndoHitachi Zosen Corp. (Japan)

3 . Knowledge Implementation Multilayer Neural Networks with FuzzyLogic 99

Hiroyuki Okada*, Nobuo Watanabe^, Akira Kawamura^ and Kazuo Asakawa*,Tetsuo Taira**, Katsuyo Ishida**, Tohru Kaji*** and Masataka Narita*^* Fujitsu Laboratories Ltd.(Japan)*• The Nikko Research Center, Ltd.•••The Nikko System Center, Ltd.

4 . An Emotion Processing System Based on Fuzzy Inference and ItsSubjective Observations 103

Torao Yanaru, Toyohiko Hirota and Naoki KimuraKyushu Institute of Technology (Japan)

A-3 FUZZY NEURAL NETWORKS PART III

1. Very Fuzzy Cognitive Maps 107Julio Rives and Rafael PereiraINISEL (Spain)

2 . Construction Theory for a Subjective Observation Model Based on AffineMapping and Its Application to Neural Networks I l l

Torao Yanaru, Toyohiko Hirota and Masahiro SirahaKyushu Institute of Technology (Japan)

3 . Fuzzy Simulation of a Chemical Reactor by an Artificial NeuralNetwork 115

A. Bulsari and A. KrastawskiLappeenranta University of Technology (Finland)

4 . Fuzzy Logic and Neural Networks for Quantitative Chemical Analysis

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(Invited) 119Matthias OttoBergakademie Freiberg (Germany)

A-4 FUZZY NEURAL NETWORKS PART IV

1. Learning Mechanism and an Application of FFS-Network ReasoningSystem 123

M. Tokunaga, K. Kohno, Y. Hashizume, K. Hamatani, M. Watanabe,K. Nakamura and Y. AgeishiAdln Research, Inc. (Japan)

2 . Fuzzy Network Production System -Fuzzy Filtered Synapse Network andIntensive Learning by Accumulated Fuzzy Indication 127

Ken Nakamura, Toshihide Fujimaki, Ryuji Horikawa and Youichi AgeishiAdln Research, Inc. (Japan)

3 . Architecture and Training of a Hybrid Neural-Fuzzy System 131Lee A. Feldkamp, G. V. Puskorius, F. Yuan and L. I. Davis, Jr.Ford Motor Company (U.S.A.)

4 . Approximation between Fuzzy Expert Systems and Neural Networks 135Yoichi Hayashi^, James J. Buckley%+and Ernest Czogala^^• Ibaraki University (Japan)•• The University of Alabama, Birmingham (U.S.A.)*** Technical University of Silesia (U.S.A.)

A-5 CHAOTIC FUZZY SYSTEMS

1. Hierarchical and Recurrent Networks of Fuzzy Models 141Hidetomo IchihashiUniversity of Osaka Prefecture (Japan)

2. Transitions of Fuzzy Number through Nonlinear Dynamical Systems(Invited) 145

Takeshi Yamakawa, Eiji Uchino, Tsutomu Miki and Tomokazu NakamuraKyushu Institute of Technology (Japan)

3 . New Mechanism to Transfer Schemata Caused by Transfer Crises 149Kazuo Sakai*, Tsuyoshi Katayama^, Kotaro Oiwa*^ and Satoshi Wada+

• Meiji University (Japan)** Japan Automobile Research Institute, Inc. (Japan)•••Oita University (Japan)

4 . Chaotic Fuzzy Models in Economy 153J. Gil Aluja*, Horia-Nicolai Teodorescu**, A. M. Gil Lafuente*and Al. P. Tacu*^• University of Barcelona (Spain)** Polytechnic Institute of Iasi (Romania)•••Center for Economic Studies (Romania)

A-6 FUZZY NEURAL COMPUTING SYSTEMS PART I (INVITED)Organizer : Madan M. Gupta

University of Saskatchewan (Canada)

1. Fuzzy Logic and Neural Networks 157Madan M. Gupta

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University of Saskatchewan (Canada)

Computation and Learning Paradigms for Biologically Inspired IntelligentComput ing 161

Panos A. LigomenidesUniversity of Maryland (U.S.A.)

Chaotic Neural Networks and Their Possible Application to BiologicalSystem .Modeling 165

M. Bodruzzaman and Mohan J. MalkaniTennessee State University (U.S.A.)

On Fuzzy Structures : Sets, Relations and Graphs 169Kiran R. BhutaniThe Catholic University of America (U.S.A.)

FUZZY NEURAL COMPUTING SYSTEMS PART II (INVITED)Organizer : Madan M. Gupta

University of Saskatchewan (Canada)

Synaptic and Somatic Adaptations in Dynamic Neural Networks 173Madan M. Gupta and D. H. RaoUniversity of Saskatchewan (Canada)

Neurocomputing and Infinite-valued Logic 177Djuro Koruga and Stuart HameroffUniversity of Arizona (U.S.A.)

Neural Network Learning by Tolerance Optimization 181V&clav Sebesta and Mirko Nov£kInstitute of Computer and Information Science (U.S.A.)

A Learning Method of Fuzzy Inference Rules with Neural Networksand its Application 185

Masao Mukaidono and Masato YamaokaMeiji University (Japan)

Organizer : Yee LeungThe Chinese University of Hong Kong (Hong Kong)

1. Inference Network for Optimization Applications 189K. P. Lam+ and C. J. Su**• The Chinese University of Hong Kong (Hong Kong)••The University of British Columbia (Canada)

2 . Logical Processing with Perceptrons 193Yee Leung+ and Zhiqiao Wu++

* The Chinese University of Hong Kong (Hong Kong)** Shenzhen University (China)

3 . Modeling of Fuzzy Dynamics : A Differential-Geometric Approach 197C. P. KwongThe Chinese University of Hong Kong (Hong Kong)

4 . Rule Learning in Expert Systems using Genetic Algorithm :1. Concepts 201

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2. Empirical Studies 205Kwong Sak Leung*, Yee Leung*, Leo So%+ and Kin Fai Yam+

The Chinese University of Hong Kong (Hong Kong)University of Arizona (U.S.A.)

A-9 NEURAL NETS AND FUZZY SYSTEMS PART I (INVITED)Organizer : Armando F. RochaUniversidade Estadual de Campinas (Brazil)

1. A Neuro-Fuzzy Inference System Designed for Implementation on aNeural Chip 209

P. Y. GlorennecInstitute National des Sciences Appliqu6es (France)

2 . Neurofuzzy Controllers 213Fernando Gomide and Armando F. RochaUniversidade Estadual de Campinas (Brazil)

3 . Distributed Modelling 217W. Pedrycz* and Armando F. Rocha* •• University of Manitoba (Canada)••State University of Campinas (Brazil)

4 . A Proposal for Approximate Case-based Reasoning on Neural Networks....221Zuliang Shen, Ho Chung Lui and Liya DingNational University of Singapore (Singapore)

A-10 NEURAL NETS AND FUZZY SYSTEMS PART II (INVITED)Organizer : Armando F. Rocha

Universidade Estadual de Campinas (Brazil)

1. A Connectionist Architecture for Production Rules with Variables 225Katsuaki Sanou, Steve G. Romaniuk and Lawrence O. HallUniversity of South Florida (U.S.A.)

2 . Neurofuzzy Interpolation : I. The Theoretical Background 229F. J. V. Zuben^, M. Regattieri^ and Armando F. Rocha+%

• Universidade Estadual de Campinas (Brazil)••Research on Natural and Artificial Intelligence (Brazil)

3 . Using Boundary Shape Data for Efficient Adaptive RuleModifications 233

Hideyuki TakagiUniversity of California, Berkeley (U.S.A.)

4 . A Proposal of Parallel Resolution Inference on Neural Logic Network 237Liya DingNational University of Singapore (Singapore)

B-l LEARNING ALGORITHM FOR FUZZY SYSTEMS (INVITED)Organizer : Miguel Delgado and Antonio Gonzalez

Universidad de Granada (Spain)

1. The Frequency on Fuzzy Domains and its Application to the SystemIdentification 241

Miguel Delgado and Antonio GonzalezUniversidad de Granada (Spain)

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2 . Empirical Learning for Fuzzy Knowledge Acquisition 245Elisabetta BinaghiI F C T R -C.N.R. (Italy)

3 . Learning Rules for A Fuzzy Inference Model 253Luis M. de Campos and Serafin MoralUniversidad de Granada (Spain)

4 . A Knowledge Base Structure for Fuzzy Controllers 257Ricardo Garcia Rosa, M1 Teresa de Pedro and Marco Tulio de AndradeInstituto de Autom&ica Industrial, CSIC (Spain)

B-2 KNOWLEDGE ACQUISITION AND TOOLS FOR EXPERT SYSTEMSTECHNOLOGY (INVITED)

Organizer : H.-J. ZimmermannRWTH Aachen (germany)

1. Fuzzy Similar Informations in Fuzzy Information Techniques 261Hubert FrankUniversity of Dortmund (Germany)

2 . Fuzzy-ID3 : A Class of Methods for Automatic Knowledge Acquisition 265Richard WeberElite-European Laboratory for Intelligent Techniques Engineering (Germany)

3 . Online Development Tools for Fuzzy Knowledge-Based Systems of HigherO r d e r 269

C. von. Altrock and B. KrauseINFORM Software Corp., Aachen (Germany)

4 . Reasoning with Uncertainty in the Knowledge Engineering EnvironmentKEE© 273

Rudolf Felix^*, Claudio Moraga* and Bernd Reusch*• University of Dortmund (Germany)**Fuzzy Demonstration Centre Dortmund.(Germany)

B-3 APPROXIMATE REASONING PART I (INVITED)Organaizer : I. B. Turksen

Tokyo Institute of Technology (Japan)

1. Classification and Representation of Ambiguity in Language Usage 277Toshihiko YokogawaLaboratory for International Fuzzy Engineering Research (Japan)

2 . Search Strategies using Fuzzy Sets 281Makishi Nakayama* and Anca Ralescu*^• Kobe Steel Ltd (Japan)••LIFE (Japan)

3 . Sensitivity Analysis in Fuzzy Systems 287I. B. Turksen^ and Q. Wang^• Tokyo Institute of Technology (Japan)••University of Toronto (Canada)

4 . A Syllogistic Reasoning as a Multi-Objective Default Expectation Process

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291Hiroshi Narazaki and I. B. TurksenTokyo Institute of Technology (Japan)

1-4 APPROXIMATE REASONING PART II

1. Analytical Inference Results for Triangular Fuzzy Data (Invited) 295B. De Baets and E. E. KerreUniversity of Gent (Belgium)

2 . An Attempt to Methods for Approximate Reasoninig based on FuzzyEntropy's Theory (Invited) 301

Akio ShimizuUbe Industries, Ltd. (Japan)

3 . Revision Principle for Approximate Reasoning : Based on Linear RevisingMethod 305

Liya Ding+, Zuliang Shen+ and Masao Mukaidono^+

• Institute of Systems Science, National University of Singapore (Singapore)••Meiji University Japan)

4 . A Method of Approximate Reasoninig with Certainty Factor 309Yutaka Hata, Kiyotaka Miyai, Fujio Miyawaki and Kazuharu YamatoHimeji Institute of Technology (Japan)

B-5 APPROXIMATE REASONING PART III

1. Fuzzy Matching and Fuzzy Comparison in Fuzzy Expert System 313Keon-Myung Lee, Kyoung-A Seong and Hyung Lee-KwangKorea Advanced Institute of Science and Technology (Korea)

2 . Fuzzy Logic Controllers with Flexible Structure 317 vRonald R. Yager and Dimitar P. FilevMachine Intelligence Inst., Iona College (U.S.A)

3 . Pruning Fuzzy Decision Trees 321Joseph M. BaroneLoki Software, Inc. (U.S.A)

4 . Decision Making under Fuzziness with Multiple Objectives and ItsApplication to Design Problem Solving 325

Masaaki Ida, Osamu Katai, Tetsuo Sawaragi and Sosuke IwaiKyoto University (Japan)

1. Analogical Fuzzy Reasoning and Gradual Inference Rules 329Ldszl6 T. K6czy^ and Kaoru Hirota^* Technical University of Budapest (Hungary)**Hosei University (Japan)

2 . Neural Network-based Fuzzy Production Rule Generation and itsApplication to an Approximate Reasoning Approach 333

Hyun-Jung Yi and Kyung-Whan OhSoGang University (Korea)

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3 . Interpolation of Fuzzy If-Then Rules by Neural Networks 337Hisao Ishibuchi, Hidehiko Okada and Hideo TanakaUniversity of Osaka Prefecture (Japan)

4 . Interpolation of Noisy Signal Data by using Fuzzy Inference (Invited) 341Eiji Uchino, Takeshi Yamakawa, Tsutomu Miki and Shin NakamuraKyushu Institute of Technology (Japan)

B-7 FUZZY MODELING

1. Auto-Tuning Method of Fuzzy Membership Functions Using NeuralNetwork Learning Algorithm : Application to Water Flow Forecastingfor Reservoir 345

Ryoichi Ichikawa^, Kazuo Nishimura+, Masahiko Kunugi^, Kazue Shimada^,Yasuharu Shimakura^, Yohei Fujisawa++ and Yasuhisa Matsunoki^• TOSHIBA Corporation (Japan)••HOKURIKU ELECTRIC POWER Co., INC (Japan)

2 . Fuzzy Logic Based Modeling and Optimization 349Yu Qian, Patrick Tessier and Guy A. DumontThe University of British Columbia (Canada)

3 . A Study on the Fuzzy Selective Relational Algebra (FSRA) 353Doheon Lee, Hyung Lee-Kwang and Myoung Ho KimKorea Advanced Institute of Science and Technology (Korea)

4 . A Self Generating and Tuning Method for Fuzzy Modeling using InteriorPenalty Method 357

Ryu Katayama, Yuji Kajitani and Yukiteru NishidaSanyo Electric Co., Ltd.(Japan)

B-8 FUZZY ENGINEERING APPLICATIONS (INVITED)Organizer : I. B. Turksen

University of Toronto(Japan)

1. Architecture of A Fuzzy-Inference-System Shell 361I. B. Turksen, Lizhu Guo and K. C. SmithUniversity of Toronto (Canada)

2 . Incremental Learning of Complex Concepts 365Marcellina M. T. Mileti* and Anca Ralescu**• University of Cincinnati (U.S.A.)••Laboratory for International Fuzzy Engineering Research (Japan)

3 . Fuzzy Logic Expert System Scheduler 371I. B. Turksen and T. YurtseverUniversity of Toronto (Canada)

4 . Inductive Learning of Conceptual Fuzzy Sets 375Tomohiro Takagi, Atsushi Imura, Hirohide Ushida and Toru YamaguchiLIFE (Japan)

B-9 DIAGNOSTIC SYSTEMS BY FUZZY LOGIC

1. Supporting Method for Optimum Maintenance Policy Selection by the

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Fuzzy Logic 381Toshio Toyota and Peng ChenKyushu Institute of Technology (Japan)

2 . Fault Diagnosis Method by Using Fuzzy Rule Based Models 385Gancho Vachkov^ and Hisayoshi Matsuyama^* Sofia Technological University (Bulgaria)••Kyushu University (Japan)

3 . Detection of Earthquake Precursors by Fuzzy Theoretical Methods 389Hidemi M. Ito and Akihiko WakayamaMeteorological Research Institute (Japan)

4 . Reliability Prediction of Electronic Equipment with Fuzzy Inference 393Tadashi MurataRyukyu University (Japan)

B-10 SAFETY RELIABILITY AND NOISE IMMUNITY OF FUZZY / NEURALSYSTEMS

1. Fuzzy Risk Index-Theory and Application 397C. Preyssl^ and Y. Nishiwaki^* European Space Agency (The Netherlands)••University Vienna (Austria)

2 . Fuzzy Fault Tree Analysis : A Case Study 401A.W.Deshpande*, U. A. Deshpande** and P. Khanna** National Environmental Engineering Research Institute (India)••Indian Institute of Technology (India)

3 . On Subjectivity of Fuzzy Sets Operations in Fuzzy Reliability Analysis 405Takehisa OnisawaUniversity of Tsukuba (Japan)

4 . Design and Robustness of Winner-Take-All Cellular Neural Networks 409Gerhard Seiler and Josef A. NossekTechnische Universitat Miinchen (Germany)

C-l FUZZY LOGIC CONTROL PART I

1. Uncertainty as Objective Function in Fuzzy Control (Invited) 413Arthur RamerUniversity of New South Wales (Australia)

2 . On Fuzzy Inference Based on Intuitionistic Logic (Invited) 417Toyohiko Hirota and Torao YanaruKyushu Institute of Technology (Japan)

3 . Comparison of Several Fuzzy Reasoning Methods on Driving Control of a...Model Car (Invited) 421

K.Nishimori, H.Tokutaka, S.Hirakawa, S.Kishida and N.IshiharaTottori University (Japan)

4 . Fuzzy Control Rules and Stability Conditions 425S.Takahara^, K.Ikeda^* and S.Miyamoto*** Kagawa Prefectural Industrial Technology Center (Japan)••University of Tokushima (Japan)

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1. Fuzzy Optimal Control Revisited: Toward a New Generation of FuzzyControl? (Invited) 429

Janusz KacprzykPolish Academy of Sciences, (Poland)

2 . Application of Fuzzy Control to a Batch Culture (Invited) 433Tsunenobu FukudaKaneka Corporation (Japan)

3 . Forecast Learning Fuzzy Control of an Autonomous Mobile Robot 437Mikio Maeda, Manabu Shimakawa and Shuta MurakamiKyushu Institute of Technology (Japan)

4 . Minimization of Rule-Chips in Fuzzy Control and Fuzzy InferenceSystems 441

H.N.TeodorescuPolytechnic Institute of Iasi (Romania)

1 . A Movement Control Method and a Learning Method for Multi-CoupledCar-like Robots 445

Kazuhiro Yasui and Hidenori ItohNagoya Institute of Technology (Japan)

2 . An Adaptive Fuzzy Current Controller with Neural Network for Field-Oriented Controlled Induction Machine 449

Kyu-Chan Lee, Seong-Sik Min, Jhong-Whan Song and Kyu-Bock ChoHyosung Industries Co., Ltd (Korea)

3 . Cooperative Mobile Robots using Fuzzy Algorithm 453Hyuntae Kim, Heungsik Noh, Seungwoo Kim and Mignon ParkYonsei University (Korea)

4. Fuzzy PU-based Active Vibration Modes Compensation 457H.N.Teodorescu*, I.Bogdan* and F.Grigoras*^• Center for Fuzzy Systems & AI (Romania)••Institute for Information Science (Romania)

G - 4 FUI2Y LOCaG© CONTROL PART IV

1 . Stability Analysis of a Fuzzy Control System of a SuperconductingActuator 461

Tadashi Kitamura and Mochimitsu KomoriKyushu Institute of Technology (Japan)

2 . An Automatic Start-up and Shut-down Control of a Drum-type Boiler usingFuzzy Logic 465

Zeungnam Bien+, Dong-Hwan Hwang+, Jae Hyuk Lee+,Hyung-Keun Ryu^, Hanoh Lee^^, Sung-Kwang Hur+^+ andIk-Soo Park****• Korea Advanced Institute of Science and Technology (Korea)•• Korea Telecom (Korea)

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• • • Goldstar Industorial Systems (Korea)••••Korea Electric Power Corporation (Korea)

3 . A Fuzzy Automatic-combustion-control-system of Refuse IncinerationPlant 469

Makoto Fujiyoshi and Toshiyuki ShirakiHitachi Zosen Corp. (Japan)

4 . A Fuzzy Dynamic Learning Controller for Chemical Process Control 473Jeong Jun Song and Sunwon ParkKorea Advanced Institute of Science and Technology (Korea)

C-5 SYSTEM IDENTIFICATIONS BY NEURAL NETWORKSOrganizer : Takeshi Yamakawa

Kyushu Institute of Technology (Japan)

1. A Neo Fuzzy Neuron and Its Applications to System Identification andPrediction of the System Behavior 477

Takeshi Yamakawa, Eiji Uchino, Tsutomu Miki and Hiroaki KusanagiKyushu Instituye of Technology (Japan)

2. Neuro-Fuzzy Identification Model of Nonlinear Dynamic Systems 485Minho Lee, Soo-Young Lee and Cheol Hoon ParkKorea Advanced Institute of Science and Technology (Korea)

3 . Space-Time Structure Dynamics of Neural Networks 489Licheng Jiao and Zheng BaoXidian University (P.R.China)

4 . On the Dynamics and Potentialities of a Discrete-time Binary Neural Networkwith Time Delay 493

Simone Gardella, Toru Kumagai, Ryoichi Hashimoto and Mitsuo WadaIndustrial Products Reseach Institute, MITI (Japan)

1 . Custom Analog VLSI Neural Chips with On-chip Digital Learning forPattern/Character Recognition (Invited) 501

Yiwen Wang* and Fathi M. A. Salam*** University of Minnesota (U.S.A.)**Michigan State University (U.S.A.)

2. A Simple Nonlinear Synapse Circuit for Artificial Neural Networks(Invited) 505

Myung-Ryul ChoiKorea Electronics Technology Institute (Korea)

3 . MOS Charge-mode Circuits for Analog VLSI Neural Systems 509Okihiko Ishizuka, Zheng Tang, Jing Liang and Hiroki MatsumotoMiyazaki University (Japan)

4. An Input Driven Multi-layer Perceptron Neural Network and CMOS VLSIImplementation 513

Ho Sun Chung, Kyung Hoon Lee, Soo Yong Lee and Kwon II BaeKyungpook Nation University, Taegu (Korea)

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HARDWARE l8iPLEyiEN=

ELS

1 . Modular Analog Hardware Neural Networks with On Chip Hebbian Learningand Analog Weight Storage (Invited) 517

B. Linares-Barranco^, E. Sanchez-Sinencio++, A. Rodriguez-Vazquez^ andJ. L. Huertas*,* Centro Nacional de Microelectr6nica(Spain)**Texas A&M university (U.S.A.)

2 . Fuzzy Processors using Neural Phenomena in CMOS Digital LSI (Invited)..521Katsufusa Shono, Cong-Kha Pham and Shinichi OokiSophia University (Japan)

3 . On Realization of Large Neural Networks 527Wieslaw Sienko and Andrzej LukszaMaritime Merchant Academy (Poland)

4 . Analog Integrated Cochlear Model for Speech Analysis (Invited) 531Weimin Liu and Moise H.Goldstein, Jr. and Andreas G.AndreouThe Johns Hopkins University(U.S.A)

C-8 FU22Y HARDWARES AND FU22Y LO<QIG COMPUTERS

1 . Serial Architecture for Fuzzy Controllers: Hardware Implementation usingAnalog/Digital VLSI Techniques 535

Jose L.Huertas Diaz, Santiago Sanchez-Solano, Angel Barriga-Barros andIluminada Baturone CastilloCentro Nacional de Microelectronica (Spain)

2 . Digital Fuzzy Processor FP-5000 539Kazuhisa Shimizu, Masaharu Osumi and Fumikazu ImaeOMRON Corporation (Japan)

3 . WARP: Weight Associative Rule Processor An Innovative Fuzzy LogicController 543

Andrea Pagni, Rinaldo Poluzzi and Gianguido RizzottoSGS-Thomson Microelectronics (Italy)

4 . Architectures for Rule-Chips Number Minimizing in Fuzzy InferenceSystems 547

H.N.Teodorescu* and T.Yamakawa*** Polytechnic Institutte of Iasi (Romania)••Kyushu Institute of Technology (Japan)

1 . Implementation of Neural Network Adder (Invited) 551Mititada Morisue, Kenichiro Sakai and Hideki FujinagaSaitama University (Japan)

2 . Generation of Chaotic Signals using Current Mode Techniques 555A. Rodriguez-Vazquez, M. Delgado-Restituto, S. Espejo and J. L. HuertasCentro Nacional de Microelectr6nica (Spain)

3 . Boltzmann Machine Scheme Learning in an Analog Chaos Neuro-Computer

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559Masayoshi Inoue and Akihiro NagayoshiKagoshima Univversity (Japan)

4 . A Chaotic Chip for Analyzing Nonlinear Discrete Dynamical NetworkSystems (Invited) 563

Takeshi Yamakawa, Tsutomu Miki and Eiji UchinoKyushu Institute of Technology (Japan)

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1. Basic Tools for Fuzzy Control : Triangular Norms and Conorms (Invited)..567Erich Peter Klement and Peter BauerJohannes Kepler Universitat (Austria)

2 . Mathematical Foundations of Fuzzy Logic (Invited) 571Esko TurunenLappeenranta University of Technology (Finland)

3 . Linguistically Oriented Fuzzy Logic Controller(Invited) 575

Vildm NovakCzechoslovak Academy of Sciences (Czechoslovakia)

4 . Complements, t-norms, and s-norms in Toll Sets 579Sadaaki MiyamotoUniversity of Tokushima (Japan)

D-2 FUZZIFICATIQN AND UNCERTAINTY MEASURE

1. Average Total Uncertainty : A New Measure and its Properties (Invited)....583Nikhil R. Pal, James C. Bezdek and Rohan HemasinhaUniversity of West Florida (U.S.A.)

2 . Information Based Reasoning in Fuzzy and Dempster-Shafer Theories(Invited) 587

Arthur RamerUniversity of New South Wales (Australia)

3 . Multi-Valued Logic of Uncertainty Derived from Epistemic Modality 593Tetsuya Murai%, Masaki Miyakoshi** and Masaru Shimbo^* Sapporo Medical College (Japan)••Hokkaido University (Japan)

4. Fuzzifications of Complete Lattices and Applications 597Arturo A. L. SangalliChamplain Regional College (Canada)

D-3 FUZZY MEASURES AND APPLICATIONS (INVITDED)Organizer : Michel Grabisch

Thomson-Sintra ASM (France)

1. Application of Fuzzy Measure, Fuzzy Integral and Neural Network to theSystem Which Estimate Taste by Using Industrial Analysis 601

Masanori Matsuda* and Takaharu Kameoka^• Satake Corporation (Japan)•*Mie University (Japan)

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