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[1992 Proceedings] IEEE International Conference on Fuzzy Systems最新文献

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The design and implementation of a massively-parallel fuzzy architecture 一种大规模并行模糊架构的设计与实现
[1992 Proceedings] IEEE International Conference on Fuzzy Systems Pub Date : 1992-03-08 DOI: 10.1109/FUZZY.1992.258700
N. Howard, R. Taylor, Nigel M. Allinson
{"title":"The design and implementation of a massively-parallel fuzzy architecture","authors":"N. Howard, R. Taylor, Nigel M. Allinson","doi":"10.1109/FUZZY.1992.258700","DOIUrl":"https://doi.org/10.1109/FUZZY.1992.258700","url":null,"abstract":"The York fuzzy automata machine (FAMe) is a massively parallel fuzzy cellular automata machine, capable of a wide range of computation. Rather than a fixed architecture, FAMe makes use of reconfigurable logic for implementing the most appropriate hardware for a given program. The authors describe the structure of the fuzzy automata machine and show how large complex fuzzy parallel systems may be constructed. A simple example of the use of FAMe involving fuzzy logic is given.<<ETX>>","PeriodicalId":222263,"journal":{"name":"[1992 Proceedings] IEEE International Conference on Fuzzy Systems","volume":"4659 1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1992-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125816306","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 16
Neural fuzzy architecture for adaptive control 自适应控制的神经模糊结构
[1992 Proceedings] IEEE International Conference on Fuzzy Systems Pub Date : 1992-03-08 DOI: 10.1109/FUZZY.1992.258715
L. Pavel, M. Chelaru
{"title":"Neural fuzzy architecture for adaptive control","authors":"L. Pavel, M. Chelaru","doi":"10.1109/FUZZY.1992.258715","DOIUrl":"https://doi.org/10.1109/FUZZY.1992.258715","url":null,"abstract":"The authors address the tracking control of linear and nonlinear systems with unknown dynamics. A self-tuning neural fuzzy adaptive control architecture, based on M. Sugeno's model for fuzzy systems (1985) and on the use of feedforward neural networks is proposed. The control loop is described. Then, the adaptive neural version of the Sugeno model for fuzzy inference systems, inserted in this loop, is presented. The algorithm was simulated and tested for discrete-time linear and nonlinear systems.<<ETX>>","PeriodicalId":222263,"journal":{"name":"[1992 Proceedings] IEEE International Conference on Fuzzy Systems","volume":"83 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1992-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122917449","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 13
Fuzzy controller design without domain experts 不需要领域专家的模糊控制器设计
[1992 Proceedings] IEEE International Conference on Fuzzy Systems Pub Date : 1992-03-08 DOI: 10.1109/FUZZY.1992.258631
J.-S.R. Jang
{"title":"Fuzzy controller design without domain experts","authors":"J.-S.R. Jang","doi":"10.1109/FUZZY.1992.258631","DOIUrl":"https://doi.org/10.1109/FUZZY.1992.258631","url":null,"abstract":"The control of nonlinear systems through a self-learning mechanism that can derive the membership functions of the rules used by a fuzzy controller is considered. Without resorting to domain experts, a fuzzy controller has to be constructed that can perform the control task of a regulator problem. The approach is based on the adaptive network, a flexible building block that can be used to implement fuzzy controllers as well as the plants under consideration. The learning rule of adaptive networks can force the plant state to approach a desired state on a time step by time step basis. The proposed approach was used to build a fuzzy controller for balancing an inverted pendulum system. It is shown that only four fuzzy if-then rules are necessary to perform the control task. The controller was quite tolerant to dealing with initial conditions that deviated significantly from the origin. The inverted pendulum system was used to test the proposed control scheme. The simulation results demonstrated its feasibility and robustness.<<ETX>>","PeriodicalId":222263,"journal":{"name":"[1992 Proceedings] IEEE International Conference on Fuzzy Systems","volume":"118 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1992-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123470033","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 110
A dynamic learning team model as a fuzzy perceptron 基于模糊感知器的动态学习团队模型
[1992 Proceedings] IEEE International Conference on Fuzzy Systems Pub Date : 1992-03-08 DOI: 10.1109/FUZZY.1992.258638
H. Nojiri
{"title":"A dynamic learning team model as a fuzzy perceptron","authors":"H. Nojiri","doi":"10.1109/FUZZY.1992.258638","DOIUrl":"https://doi.org/10.1109/FUZZY.1992.258638","url":null,"abstract":"The author develops an understanding of the formal relationship between perceptrons and dynamic team models. The various concepts of perceptrons and fuzzy sets are introduced to a framework for dynamic team decisions. Then a dynamic learning team model is proposed which uses the learning rules to adjust the informal human relations expressed by the concepts of fuzzy relations. A proposed dynamic learning team model contains a fuzzy perceptron as a special case.<<ETX>>","PeriodicalId":222263,"journal":{"name":"[1992 Proceedings] IEEE International Conference on Fuzzy Systems","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1992-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123610308","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
A survey on generalized measures 广义测度综述
[1992 Proceedings] IEEE International Conference on Fuzzy Systems Pub Date : 1992-03-08 DOI: 10.1109/FUZZY.1992.258773
E. Klement, S. Weber
{"title":"A survey on generalized measures","authors":"E. Klement, S. Weber","doi":"10.1109/FUZZY.1992.258773","DOIUrl":"https://doi.org/10.1109/FUZZY.1992.258773","url":null,"abstract":"The authors present a unified approach to several concepts on generalized measures with various domains and ranges, which are: sigma -additive measures; probability measures of fuzzy events; fuzzy probability measures; fuzzy-valued fuzzy measures; ( sigma -) perpendicular to -decomposable measures; measures of fuzzy sets; and perpendicular to '-decomposable measures, where perpendicular to ' is the extension of an Archimedean t-conorm on (0,M) to D/sub M/ via the extension principle. All these measures are handled in a unified way. The main emphasis is on integral representations of such measures if they are defined on a collection of fuzzy sets.<<ETX>>","PeriodicalId":222263,"journal":{"name":"[1992 Proceedings] IEEE International Conference on Fuzzy Systems","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1992-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133388273","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Fuzzy sets in image processing and recognition 模糊集在图像处理和识别中的应用
[1992 Proceedings] IEEE International Conference on Fuzzy Systems Pub Date : 1992-03-08 DOI: 10.1109/FUZZY.1992.258606
S. Pál
{"title":"Fuzzy sets in image processing and recognition","authors":"S. Pál","doi":"10.1109/FUZZY.1992.258606","DOIUrl":"https://doi.org/10.1109/FUZZY.1992.258606","url":null,"abstract":"The various aspects of image processing and analysis problems where the theory of fuzzy set has so far been applied are addressed along with their relevance and applications. The possibility of combining fuzzy set theory, neural network theory and genetic algorithms for improved performance is discussed. The applications include enhancement, edge detection, thinning, segmentation, object extraction, skeleton extraction, primitive extraction, information and ambiguity measures, curve fitting, and the use of neural learning. Some future research directions are outlined. A list of representative references is also provided.<<ETX>>","PeriodicalId":222263,"journal":{"name":"[1992 Proceedings] IEEE International Conference on Fuzzy Systems","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1992-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127809047","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 70
A design algorithm of membership functions for a fuzzy neuron using example-based learning 基于实例学习的模糊神经元隶属函数设计算法
[1992 Proceedings] IEEE International Conference on Fuzzy Systems Pub Date : 1992-03-08 DOI: 10.1109/FUZZY.1992.258599
T. Yamakawa, Masuo Furukawa
{"title":"A design algorithm of membership functions for a fuzzy neuron using example-based learning","authors":"T. Yamakawa, Masuo Furukawa","doi":"10.1109/FUZZY.1992.258599","DOIUrl":"https://doi.org/10.1109/FUZZY.1992.258599","url":null,"abstract":"The authors describe a design algorithm for extraction of membership functions of a fuzzy neuron based on example-based learning with optimization of cross-detecting lines. This algorithm facilitates design without the knowledge of experts. The algorithm was verified by recognition of hand-written characters. Using this algorithm, a fuzzy neuron can be designed very easily without knowledge about the features of the character, and optimum membership functions can be extracted.<<ETX>>","PeriodicalId":222263,"journal":{"name":"[1992 Proceedings] IEEE International Conference on Fuzzy Systems","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1992-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121455239","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 37
Fuzzy systems as universal approximators 模糊系统作为全称逼近器
[1992 Proceedings] IEEE International Conference on Fuzzy Systems Pub Date : 1992-03-08 DOI: 10.1109/FUZZY.1992.258720
B. Kosko
{"title":"Fuzzy systems as universal approximators","authors":"B. Kosko","doi":"10.1109/FUZZY.1992.258720","DOIUrl":"https://doi.org/10.1109/FUZZY.1992.258720","url":null,"abstract":"The author shows that an additive fuzzy system can approximate any continuous function on a compact domain to any degree of accuracy. Fuzzy systems are dense in the space of continuous functions. The fuzzy system approximates the function by covering its graph with fuzzy patches in the input-output state space. Each fuzzy rule defines a fuzzy patch and connects commonsense knowledge with state-space geometry. Neural or statistical clustering algorithms can approximate the unknown fuzzy patches and generate fuzzy systems from training data.<<ETX>>","PeriodicalId":222263,"journal":{"name":"[1992 Proceedings] IEEE International Conference on Fuzzy Systems","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1992-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128957407","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1686
Fuzzy hypercubes: a possibilistic inferencing paradigm 模糊超立方体:一种可能性推理范式
[1992 Proceedings] IEEE International Conference on Fuzzy Systems Pub Date : 1992-03-08 DOI: 10.1109/FUZZY.1992.258701
H. Kang, G. Vachtsevanos
{"title":"Fuzzy hypercubes: a possibilistic inferencing paradigm","authors":"H. Kang, G. Vachtsevanos","doi":"10.1109/FUZZY.1992.258701","DOIUrl":"https://doi.org/10.1109/FUZZY.1992.258701","url":null,"abstract":"A robust and reliable learning and reasoning mechanism is addressed based upon fuzzy set theory and fuzzy associative memories. The mechanism stores an initial knowledge base via approximate learning and utilizes this information for decision-making systems via fuzzy inferencing. This fuzzy computer architecture, a fuzzy hypercube, processes all the rules in one clock period in parallel. Fuzzy hypercubes can be applied to control of a class of complex and highly nonlinear systems which suffer from vagueness or uncertainty.<<ETX>>","PeriodicalId":222263,"journal":{"name":"[1992 Proceedings] IEEE International Conference on Fuzzy Systems","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1992-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116993864","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 7
Parameter formulae for fundamental operations of weakly non-interactive fuzzy numbers 弱非交互模糊数基本运算的参数公式
[1992 Proceedings] IEEE International Conference on Fuzzy Systems Pub Date : 1992-03-08 DOI: 10.1109/FUZZY.1992.258611
M. Kawaguchi, T. Da-te
{"title":"Parameter formulae for fundamental operations of weakly non-interactive fuzzy numbers","authors":"M. Kawaguchi, T. Da-te","doi":"10.1109/FUZZY.1992.258611","DOIUrl":"https://doi.org/10.1109/FUZZY.1992.258611","url":null,"abstract":"D. Dubois and H. Prade (1981) introduced the concept of weakly noninteractive fuzzy numbers whose operations are based on the extension principle corresponding to each t-norm in place of the minimum operator. Some properties of weakly noninteractive fuzzy numbers and their practical method of calculation are investigated. Three parameters indicating the mean value and the left/right spreads of the fuzzy number are considered. Various parameter formulas for arithmetic operations and power function operation of certain kinds of weakly noninteractive fuzzy numbers involving no-interactive fuzzy numbers are presented. The formulas are applicable to both cases of the L-R fuzzy number of Dubois and Prade (1978) and an improved version of the calculation method using the digital representation. An attempt is made to classify general t-norms into the three classes from the viewpoint of the parameter formulas. The results of numerical experiments are shown for the formulas and the calculation method using the digital representation.<<ETX>>","PeriodicalId":222263,"journal":{"name":"[1992 Proceedings] IEEE International Conference on Fuzzy Systems","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1992-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116301409","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 4
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