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ParCeL-1: a parallel language based on autonomous agents for connectionist and AI applications ParCeL-1:一种基于连接器和人工智能应用程序的自主代理的并行语言
1st International Symposium on Neuro-Fuzzy Systems, AT '96. Conference Report Pub Date : 1996-08-29 DOI: 10.1109/ISNFS.1996.603822
S. Vialle, Y. Lallement, T. Cornu
{"title":"ParCeL-1: a parallel language based on autonomous agents for connectionist and AI applications","authors":"S. Vialle, Y. Lallement, T. Cornu","doi":"10.1109/ISNFS.1996.603822","DOIUrl":"https://doi.org/10.1109/ISNFS.1996.603822","url":null,"abstract":"We present a new language called ParCeL-1, dedicated to connectionist and explicitly parallel AI programming. ParCeL-1 is a language based on agents, similar to actor languages. Its agents are autonomous and follow a computational model in which the communications are non-blocking and the communication scheme is explicit. ParCeL-1 has a parallel implementation and runs on several multiprocessor architectures. We give an example of connectionist programming (the Kohonen map) and show several performance results on a transputer based multiprocessor architecture and on the Cray T3D parallel computer.","PeriodicalId":187481,"journal":{"name":"1st International Symposium on Neuro-Fuzzy Systems, AT '96. Conference Report","volume":"2015 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1996-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121605932","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
An accelerator card for fuzzy learning 一个用于模糊学习的加速卡
1st International Symposium on Neuro-Fuzzy Systems, AT '96. Conference Report Pub Date : 1996-08-29 DOI: 10.1109/ISNFS.1996.603819
M. Russo, G. V. Russo, C. Petta, N. Randaazo
{"title":"An accelerator card for fuzzy learning","authors":"M. Russo, G. V. Russo, C. Petta, N. Randaazo","doi":"10.1109/ISNFS.1996.603819","DOIUrl":"https://doi.org/10.1109/ISNFS.1996.603819","url":null,"abstract":"In this paper we present a fuzzy multiprocessor card which is capable of significantly increasing the performance, in terms of time, of a generic fuzzy inference learning algorithm based on techniques that do not use the derivative of the function to be learned, such as genetic algorithms.","PeriodicalId":187481,"journal":{"name":"1st International Symposium on Neuro-Fuzzy Systems, AT '96. Conference Report","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1996-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131179286","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
VLSI complexity of threshold gate COMPARISON VLSI阈值门复杂度比较
1st International Symposium on Neuro-Fuzzy Systems, AT '96. Conference Report Pub Date : 1996-08-29 DOI: 10.1109/ISNFS.1996.603834
Valeriu Beiu
{"title":"VLSI complexity of threshold gate COMPARISON","authors":"Valeriu Beiu","doi":"10.1109/ISNFS.1996.603834","DOIUrl":"https://doi.org/10.1109/ISNFS.1996.603834","url":null,"abstract":"The paper overviews recent developments concerning optimal (from the point of view of size and depth) implementations of the Boolean function COMPARISON using feedforward neural networks made of threshold gates. We detail a class of solutions which covers another particular solution, and spans from constant to logarithmic depths. These circuit complexity results are supplemented by fresh VLSI complexity results having applications to hardware implementations of neural networks and to VLSI-friendly learning algorithms. In order to estimate the area (A) and the delay (T), as well as the classical AT/sup 2/, we use the following 'cost functions': (i) the connectivity (i.e., sum of fan-ins) and the number-of-bits for representing the weights and thresholds are used to approximate the area; while (ii) the fan-ins and the length of the wires are used for closer estimates of the delay. Such approximations allow us to compare the different solutions-which present very interesting fan-in dependent depth-size and area-delay tradeoffs-with respect to AT/sup 2/.","PeriodicalId":187481,"journal":{"name":"1st International Symposium on Neuro-Fuzzy Systems, AT '96. Conference Report","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1996-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114773102","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: 3
A genetic approach to fuzzy learning 模糊学习的遗传方法
1st International Symposium on Neuro-Fuzzy Systems, AT '96. Conference Report Pub Date : 1996-08-29 DOI: 10.1109/ISNFS.1996.603814
M. Russo
{"title":"A genetic approach to fuzzy learning","authors":"M. Russo","doi":"10.1109/ISNFS.1996.603814","DOIUrl":"https://doi.org/10.1109/ISNFS.1996.603814","url":null,"abstract":"The approach proposed allows supervised approximation of multi-input/multi-output (MIMO) systems. Typically a small number of fuzzy rules are produced. The learning capacity is considerable, as is shown by the numerous applications developed. The paper gives a significant example of how the fuzzy models developed are generally better than those to be found in recent literature concerning both the approximation capability and simplicity.","PeriodicalId":187481,"journal":{"name":"1st International Symposium on Neuro-Fuzzy Systems, AT '96. Conference Report","volume":"244 ","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1996-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133455802","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: 14
Comparison between classical and fuzzy-controller for electrohydraulic axes 电液轴经典控制器与模糊控制器的比较
1st International Symposium on Neuro-Fuzzy Systems, AT '96. Conference Report Pub Date : 1996-08-29 DOI: 10.1109/ISNFS.1996.603833
F. Ionescu, F. Haszier
{"title":"Comparison between classical and fuzzy-controller for electrohydraulic axes","authors":"F. Ionescu, F. Haszier","doi":"10.1109/ISNFS.1996.603833","DOIUrl":"https://doi.org/10.1109/ISNFS.1996.603833","url":null,"abstract":"Electro-hydro-pneumatic systems for the position, speed or force control are to day even more employed as actuation means for robots, machine tools, aerospace and other engines both because of their high dynamics and specific transmitted power. Due especially to the low price and the last achievements of the field of modern and robust control it became possible to answer the new requirements on higher dynamics and stability and to replace even the traditional electromechanical means. Our paper presents some comparative results of simulations of a electrohydraulic axis both with P, PID and fuzzy-logic controllers as preliminary steps towards their implementation on the HYPAS-simulation software as well as for some actual applications in the field of machine tools. Simulations are achieved both with the MATLAB/SIMULINKand HYPAS-simulation program. Experimentally investigations were realised on an actual three-axis Cartesian robot.","PeriodicalId":187481,"journal":{"name":"1st International Symposium on Neuro-Fuzzy Systems, AT '96. Conference Report","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1996-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124836994","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
Adapted gradient algorithm for algebraic fuzzy neural networks 代数模糊神经网络的自适应梯度算法
1st International Symposium on Neuro-Fuzzy Systems, AT '96. Conference Report Pub Date : 1996-08-29 DOI: 10.1109/ISNFS.1996.603837
H. Teodorescu, D. Arotaritei, E. González, A. Mendana
{"title":"Adapted gradient algorithm for algebraic fuzzy neural networks","authors":"H. Teodorescu, D. Arotaritei, E. González, A. Mendana","doi":"10.1109/ISNFS.1996.603837","DOIUrl":"https://doi.org/10.1109/ISNFS.1996.603837","url":null,"abstract":"A learning algorithm based on a gradient technique is introduced for the algebraic fuzzy neural network with fuzzy weights. The fuzzy weights can be triangular fuzzy numbers (usually nonsymmetric), or trapezoidal fuzzy numbers. The network is able to map a vector of triangular (trapezoidal) fuzzy numbers into any other vector of triangular (trapezoidal) fuzzy numbers.","PeriodicalId":187481,"journal":{"name":"1st International Symposium on Neuro-Fuzzy Systems, AT '96. Conference Report","volume":"81 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1996-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117209399","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 neuro-fuzzy systems for control applications 一种用于控制的神经模糊系统
1st International Symposium on Neuro-Fuzzy Systems, AT '96. Conference Report Pub Date : 1996-08-29 DOI: 10.1109/ISNFS.1996.603829
F. Berardi, M. Chiaberge, E. Miranda, L. Reyneri
{"title":"A neuro-fuzzy systems for control applications","authors":"F. Berardi, M. Chiaberge, E. Miranda, L. Reyneri","doi":"10.1109/ISNFS.1996.603829","DOIUrl":"https://doi.org/10.1109/ISNFS.1996.603829","url":null,"abstract":"This paper describes DANIELA a neuro-fuzzy system for control applications. The system is based on a custom neural device that can implement either multilayer perceptrons, radial basis functions or fuzzy paradigms. The system implements intelligent control algorithms mixing neuro-fuzzy paradigms with finite state automata and is used to control a walking hexapod.","PeriodicalId":187481,"journal":{"name":"1st International Symposium on Neuro-Fuzzy Systems, AT '96. Conference Report","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1996-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121659734","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
Adaptive neuro-fuzzy controller for navigation of mobile robot 移动机器人导航的自适应神经模糊控制器
1st International Symposium on Neuro-Fuzzy Systems, AT '96. Conference Report Pub Date : 1996-08-29 DOI: 10.1109/ISNFS.1996.603828
J. Godjevac, N. Steele
{"title":"Adaptive neuro-fuzzy controller for navigation of mobile robot","authors":"J. Godjevac, N. Steele","doi":"10.1109/ISNFS.1996.603828","DOIUrl":"https://doi.org/10.1109/ISNFS.1996.603828","url":null,"abstract":"Fuzzy systems are able to treat uncertain and imprecise information; they make use of knowledge in the form of linguistic rules. Their drawbacks are caused mainly by the difficulty of defining accurate membership functions and lack of a systematic procedure for the transformation of expert knowledge into the rule base. Neural networks have the ability to learn but with some neural networks, knowledge representation and extraction are difficult. First, we consider a rule based fuzzy controller and a learning procedure based on the stochastic approximation method. The radial basis function neural network is then considered and it is shown that a modified form of this network is identical with the fuzzy controller which may thus be considered as a neuro-fuzzy controller. Numerical examples are presented to demonstrate the validity of the approach and it is shown that such an adaptive neuro-fuzzy system is successful in the control of a mobile robot.","PeriodicalId":187481,"journal":{"name":"1st International Symposium on Neuro-Fuzzy Systems, AT '96. Conference Report","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1996-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131928121","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: 6
Feedforward neural filter with learning in features space. Preliminary results 特征空间学习的前馈神经滤波器。初步结果
1st International Symposium on Neuro-Fuzzy Systems, AT '96. Conference Report Pub Date : 1996-08-29 DOI: 10.1109/ISNFS.1996.603815
H. Teodorescu, C. Bonciu
{"title":"Feedforward neural filter with learning in features space. Preliminary results","authors":"H. Teodorescu, C. Bonciu","doi":"10.1109/ISNFS.1996.603815","DOIUrl":"https://doi.org/10.1109/ISNFS.1996.603815","url":null,"abstract":"An adaptive filtering technique using a multilayer perceptron neural network designed as a transversal filter, based on the information extracted from the second order statistics of the signal, is presented. The statistics are extracted with a principal component analysis (PCA) hierarchical network. The training procedure uses an error signal computed as the difference between the desired and actual largest eigenvalues. Some advantages of the proposed method are illustrated by preliminary experiments on electrocardiographic (ECG) signal filtering.","PeriodicalId":187481,"journal":{"name":"1st International Symposium on Neuro-Fuzzy Systems, AT '96. Conference Report","volume":"82 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1996-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121524943","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
The VLSI design of a digital fuzzification circuit for a 4 input CMOS fuzzy processor running at a rate of 320 ns 为运行速度为320ns的四输入CMOS模糊处理器设计了数字模糊化电路
1st International Symposium on Neuro-Fuzzy Systems, AT '96. Conference Report Pub Date : 1996-08-29 DOI: 10.1109/ISNFS.1996.603817
A. Gabrielli, E. Gandolfi, M. Masetti
{"title":"The VLSI design of a digital fuzzification circuit for a 4 input CMOS fuzzy processor running at a rate of 320 ns","authors":"A. Gabrielli, E. Gandolfi, M. Masetti","doi":"10.1109/ISNFS.1996.603817","DOIUrl":"https://doi.org/10.1109/ISNFS.1996.603817","url":null,"abstract":"The paper first summarizes the architecture of a VLSI fuzzy processor that can be fabricated in 0.7 /spl mu/m digital CMOS technology. This processor is able to process a four 7-bit input data set every 320 ns. This rate increases up to 100 ns if only two inputs are processed. The innovative feature of this design is the independence of the processing rate from the fuzzy system. The fuzzy chip architecture is pipelined and each step takes 20 ns. We describe in this paper the fuzzification process: in our solution the membership functions (MFs) have a triangular shape, therefore there is a memory where the related points necessary to define the shape are stored. In one pipeline step the MF shape is generated and in the following step the grade of truth /spl alpha/ is computed. In this paper we describe in details the circuit.","PeriodicalId":187481,"journal":{"name":"1st International Symposium on Neuro-Fuzzy Systems, AT '96. Conference Report","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1996-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132151622","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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