scispace - formally typeset
Journal ArticleDOI

VLSI Hardware Realization of Self-Learning Recursive Fuzzy Model for Dynamic Systems

M.F. Scheffer, +1 more
- 01 Jul 1993 - 
- Vol. 26, Iss: 2, pp 769-772
TLDR
A hardware realization of a self-learning fuzzy logic controller, based upon a unique probability theory approach to fuzzy identification and estimation, is presented, chosen because of an inherent filtering operation making it highly immune to noise.
About
This article is published in IFAC Proceedings Volumes.The article was published on 1993-07-01. It has received 7 citations till now. The article focuses on the topics: Fuzzy electronics & Fuzzy number.

read more

Citations
More filters
Journal ArticleDOI

Computational intelligence in management of ATM networks

TL;DR: The current state of ATM network management research employing artificial neural networks, fuzzy systems and design methods based on evolutionary computation as reported in the technical literature is summarized.
Proceedings ArticleDOI

Fuzzy adaptive traffic enforcement for ATM networks

TL;DR: This paper presents a fuzzy logic CAC (connection admission control) and traffic policing method intended for the modelling and management of ATM networks.
Proceedings ArticleDOI

Fuzzy modeling and prediction of network traffic fluctuations

TL;DR: A fuzzy logic self-learning model and adaptive predictor of traffic now is presented, and the results of an application of this predictor on real world telephone links, are shown, and are compared to applications of a math-model and a Kalman-filter predictor.

Fuzzy logic control techniques and structures for Asynchronous Transfer Mode (ATM) based multimedia networks

TL;DR: The research presented in this thesis aims to demonstrate that fuzzy logic is a useful tool for developing mechanisms for controlling traffic flows in ATM based multimedia networks to maintain quality of service (QoS) requirements and maximize resource utilization.
References
More filters
Journal ArticleDOI

Fuzzy Model Identification and Self-Learning for Dynamic Systems

TL;DR: The required computer capacity and time for implementing the proposed algorithms and related resulting models are-significantly reduced by introducing the concept of the "referential fuzzy sets."
Journal ArticleDOI

Probabilistic fuzzy model for dynamic systems

TL;DR: A model, based on a fuzzy relation obtained from fuzzy referential sets on the input and output spaces, for predicting the behaviour of nonlinear dynamic systems is presented.
Journal ArticleDOI

New fuzzy learning model with recursive estimation for dynamic systems

TL;DR: A systematic design technique for a discrete-time self-learning fuzzy model, based on fuzzy relational equations, is presented with some novel features, and is shown to be a fuzzy automaton.
Journal ArticleDOI

Empirical comparison of methods of fuzzy relational identification

TL;DR: In this paper, a number of methods have been proposed for the identification and self learning of relational fuzzy models and the results show that identified relational models can give as good results as rule-based models and can be made to be very tolerant of noise in the identification data.
Journal ArticleDOI

New approach to fuzzy learning in dynamic systems

TL;DR: A new fuzzy method is defined called priming, which is a process of inducing a specified dynamic behaviour in a fuzzy system model by means of an external function.
Related Papers (5)