Displaying similar documents to “Systolic architectures for fuzzy processing and their simulation.”

An architecture for making judgments using computing with words

Jerry Mendel (2002)

International Journal of Applied Mathematics and Computer Science

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Our thesis is that computing with words needs to account for the uncertainties associated with the meanings of words, and that these uncertainties require using type-2 fuzzy sets. Doing this leads to a proposed architecture for making it judgments by means of computing with words, i.e., to a perceptual computer-the Per-C. The Per-C includes an encoder, a type-2 rule-based fuzzy logic system, and a decoder. It lets all human-computer interactions be performed using words. In this paper,...

Automatic synthesis of fuzzy logic controllers.

Angel Barriga, Santiago Sánchez-Solano, Carlos Jesús Jiménez, D. Galán, D. R. López (1996)

Mathware and Soft Computing

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This paper describes a design environment for the hardware realizations of fuzzy controllers which includes a set of CAD tools to ease the description, verification and synthesis of this kind of systems. Special emphasis is focused on the use of a standard hardware description language (VHDL) and compatibility with other integrated circuits design tools.

Decomposition of the fuzzy inference system for implementation in the FPGA structure

Bernard Wyrwoł, Edward Hrynkiewicz (2013)

International Journal of Applied Mathematics and Computer Science

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The paper presents the design and implementation of a digital rule-relational fuzzy logic controller. Classical and decomposed logical structures of fuzzy systems are discussed. The second allows a decrease in the hardware cost of the fuzzy system and in the computing time of the final result (fuzzy or crisp), especially when referring to relational systems. The physical architecture consists of IP modules implemented in an FPGA structure. The modules can be inserted into or removed...

Interpretability of linguistic variables: a formal account

Ulrich Bodenhofer, Peter Bauer (2005)

Kybernetika

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This contribution is concerned with the interpretability of fuzzy rule-based systems. While this property is widely considered to be a crucial one in fuzzy rule-based modeling, a more detailed formal investigation of what “interpretability” actually means is not available. So far, interpretability has most often been associated with rather heuristic assumptions about shape and mutual overlapping of fuzzy membership functions. In this paper, we attempt to approach this problem from a...

Some ideas concerning fuzzy intelligent systems.

Senén Barro (1999)

Mathware and Soft Computing

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This article brings together some ideas on fuzzy intelligent systems. We start from fuzzy controllers, and we reflect on the role of fuzzy logic in other domains in which, in spite of optimistic forecasts, advances made are still less significant. By way of example, we make mention of certain fields in which it is foreseeable that there will be significant advances made using fuzzy logic. Finally, we emphasise certain problems and proposals that we consider to be of interest. ...

From computing with numbers to computing with words - From manipulation of measurements to manipulation of perceptions

Lotfi Zadeh (2002)

International Journal of Applied Mathematics and Computer Science

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Computing, in its usual sense, is centered on manipulation of numbers and symbols. In contrast, computing with words, or CW for short, is a methodology in which the objects of computation are words and propositions drawn from a natural language, e.g., small, large, far, heavy, not very likely, the price of gas is low and declining, Berkeley is near San Francisco, it is very unlikely that there will be a significant increase in the price of oil in the near future, etc. Computing with...

A methodology for developing knowledge-based systems.

Juan Luis Castro, José Jesús Castro-Sánchez, Antonio Espin, José Manuel Zurita (1998)

Mathware and Soft Computing

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This paper presents a methodology for developing fuzzy knowledge based systems (KBS), which permits a complete automatization. This methodology will be useful for approaching more complex problems that those in which machine learning from examples are successful.

On classification with missing data using rough-neuro-fuzzy systems

Robert K. Nowicki (2010)

International Journal of Applied Mathematics and Computer Science

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The paper presents a new approach to fuzzy classification in the case of missing data. Rough-fuzzy sets are incorporated into logical type neuro-fuzzy structures and a rough-neuro-fuzzy classifier is derived. Theorems which allow determining the structure of the rough-neuro-fuzzy classifier are given. Several experiments illustrating the performance of the roughneuro-fuzzy classifier working in the case of missing features are described.