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

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A neural expert system using fuzzy teaching input 基于模糊教学输入的神经专家系统
[1992 Proceedings] IEEE International Conference on Fuzzy Systems Pub Date : 1992-03-08 DOI: 10.1109/FUZZY.1992.258661
Y. Hayashi
{"title":"A neural expert system using fuzzy teaching input","authors":"Y. Hayashi","doi":"10.1109/FUZZY.1992.258661","DOIUrl":"https://doi.org/10.1109/FUZZY.1992.258661","url":null,"abstract":"The author previously (1990, 1991) proposed a fuzzy neural expert system and provided a method to extract automatically fuzzy IF-THEN rules from a trained neural network. The previous work is extended and a neural expert system is proposed using fuzzy teaching input. The neural expert system can perform generalization of the information derived from training data with fuzzy teaching input and embodiment of knowledge in the form of a fuzzy neural network, where the fuzzy teaching input is subjectively given by domain experts: and extraction of fuzzy IF-THEN rules with linguistic relative importance of each proposition in an antecedent (IF-part) from a trained neural network. A method is proposed to extract automatically fuzzy IF-THEN rules from the trained neural network generated by training data with fuzzy teaching input.<<ETX>>","PeriodicalId":222263,"journal":{"name":"[1992 Proceedings] IEEE International Conference on Fuzzy Systems","volume":"661 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":"133130357","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: 26
Perceptual grouping based on fuzzy sets 基于模糊集的感知分组
[1992 Proceedings] IEEE International Conference on Fuzzy Systems Pub Date : 1992-03-08 DOI: 10.1109/FUZZY.1992.258737
Hang-Bong Kangt, E. Walker
{"title":"Perceptual grouping based on fuzzy sets","authors":"Hang-Bong Kangt, E. Walker","doi":"10.1109/FUZZY.1992.258737","DOIUrl":"https://doi.org/10.1109/FUZZY.1992.258737","url":null,"abstract":"The authors propose a new approach based on fuzzy sets for detecting relations among points, line segments, and elliptic arc segments. Appropriate constraints defining the relations are extracted. A suitable fuzzy membership function is assigned to each constraint. Then the constraints are combined by fuzzy set operations to describe meaningful relations. According to these meaningful relations, a perceptual grouping is executed. Grouping methods are described on the basis of collinear and coelliptic relations. A measure of the significance of grouping for high-level vision processing is discussed. A prototype system for perceptual grouping from image data was implemented using a frame-based knowledge representation scheme, and experimental results for real image data are presented.<<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":"133809510","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
An approach to stability analysis of second order fuzzy systems 二阶模糊系统的稳定性分析方法
[1992 Proceedings] IEEE International Conference on Fuzzy Systems Pub Date : 1992-03-08 DOI: 10.1109/FUZZY.1992.258713
S. Kawamoto, K. Tada, A. Ishigame, T. Taniguchi
{"title":"An approach to stability analysis of second order fuzzy systems","authors":"S. Kawamoto, K. Tada, A. Ishigame, T. Taniguchi","doi":"10.1109/FUZZY.1992.258713","DOIUrl":"https://doi.org/10.1109/FUZZY.1992.258713","url":null,"abstract":"The stability of fuzzy systems can be discussed by the theorem of K. Tanaka and M. Sugeno (1990). However, it is difficult to find the common positive definite matrix P which is introduced in the theorem, and satisfies, for example, two Lyapunov inequalities A/sub 1//sup T/PA/sub 1/-P<0 and A/sub 2//sup T/PA/sub 2/-P<0. The authors present a new simple approach for finding the whole region where a 2*2 real matrix P exists. As an example, two spring-mass physical systems with damping are treated, and the region of P is obtained. Also, three examples considered by Tanaka and Sugeno are discussed. It is emphasized that illustrating the P-region calculated by the approach aids the design of a fuzzy controller.<<ETX>>","PeriodicalId":222263,"journal":{"name":"[1992 Proceedings] IEEE International Conference on Fuzzy Systems","volume":"13 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":"133919574","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: 133
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
Fuzzy control of robots 机器人的模糊控制
[1992 Proceedings] IEEE International Conference on Fuzzy Systems Pub Date : 1992-03-08 DOI: 10.1109/FUZZY.1992.258694
J. Zhou, P. Coiffet
{"title":"Fuzzy control of robots","authors":"J. Zhou, P. Coiffet","doi":"10.1109/FUZZY.1992.258694","DOIUrl":"https://doi.org/10.1109/FUZZY.1992.258694","url":null,"abstract":"The authors deal with the application aspect of fuzzy sets theory in the robot control, domain, namely the servoing, the kinematic control and the dynamic control. The principles of the fuzzy controllers are presented. The simulation results showed that fuzzy control can also be applied to the basic robot control, and it facilitates the engineering implementations.<<ETX>>","PeriodicalId":222263,"journal":{"name":"[1992 Proceedings] IEEE International Conference on Fuzzy Systems","volume":"23 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":"131357392","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: 61
Fuzzy cluster analysis for multi-antecedent rule base restructuring based on S-implication 基于s -蕴涵的多先行规则库重构模糊聚类分析
[1992 Proceedings] IEEE International Conference on Fuzzy Systems Pub Date : 1992-03-08 DOI: 10.1109/FUZZY.1992.258783
I. Turksen, S. Jiang
{"title":"Fuzzy cluster analysis for multi-antecedent rule base restructuring based on S-implication","authors":"I. Turksen, S. Jiang","doi":"10.1109/FUZZY.1992.258783","DOIUrl":"https://doi.org/10.1109/FUZZY.1992.258783","url":null,"abstract":"A new fuzzy cluster analysis approach is proposed for a restructuring of multi-antecedent rule bases where rules are based on S-implication. The algorithms can be applied with a compositional tolerance relation or with an analogical tolerance relation. The adoption of a specific algorithm therefore corresponds to the inference mode to be executed on the knowledge base. It is shown that the analogical tolerance relation is highly efficient in rule base restructuring and rule firing under a proposed search schema. Finally, further studies are discussed.<<ETX>>","PeriodicalId":222263,"journal":{"name":"[1992 Proceedings] IEEE International Conference on Fuzzy Systems","volume":"25 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":"125299403","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: 1
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