Displaying similar documents to “Fuzzy approach for data association in image tracking.”

Evolution-fuzzy rule based system with parameterized consequences

Piotr Czekalski (2006)

International Journal of Applied Mathematics and Computer Science

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While using automated learning methods, the lack of accuracy and poor knowledge generalization are both typical problems for a rule-based system obtained on a given data set. This paper introduces a new method capable of generating an accurate rule-based fuzzy inference system with parameterized consequences using an automated, off-line learning process based on multi-phase evolutionary computing and a training data covering algorithm. The presented method consists of the following steps:...

Fuzzy sets in computer vision: an overview.

Pilar Sobrevilla, Eduard Montseny (2003)

Mathware and Soft Computing

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Every computer vision level crawl with uncertainty, what makes its management a significant problem to be considered and solved when trying for automated systems for scene analysis and interpretation. This is why fuzzy set theory and fuzzy logic is making many inroads into the handling of uncertainty in various aspects of image processing and computer vision. The growth within the use of fuzzy set theory in computer vision is keeping pace with the use of more complex algorithms...

Systolic architectures for fuzzy processing and their simulation.

Luis de Salvador, Marcos García, Julio Gutiérrez (1994)

Mathware and Soft Computing

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This paper details the study of systolic architectures for fuzzy rules processing made at the Hardware and Advanced Control Laboratory - INTA. The theoretical basis of these architectures is described and analysed. Likewise, the resultant schematics are simulated using a hardware description language (VHDL) with standard cells from ES2. This gives us a very accurate assessment of their real performance. In this way we can detect the inherent shortcomings in this class of systems and...

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.

A defuzzification based new algorithm for the design of Mamdani-type fuzzy controllers

Jean Jamil Saade (2000)

Mathware and Soft Computing

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This paper presents a new learning algorithm for the design of Mamdani- type or fully-linguistic fuzzy controllers based on available input-output data. It relies on the use of a previously introduced parametrized defuzzification strategy. The learning scheme is supported by an investigated property of the defuzzification method. In addition, the algorithm is tested by considering a typical non-linear function that has been adopted in a number of published research articles. The test...

Dual meaning of verbal quantities

Milan Mareš, Radko Mesiar (2002)

Kybernetika

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The aim of the paper is to summarize and interpret some ideas regarding effective processing of vague data. The main contribution of the submitted approach consists in respecting the fact that vague data can be decomposed into two parts. The numerical one, describing the quantitative value of such data, and the semantic one characterizing the qualitative structure of the vagueness included into them. This partition of vague verbal data leads to a significant simplification of their practical...

Localization and fuzzy classification of manufacturing defects in sheets of glass.

Luis Junco Navascués, Luciano Sánchez (1998)

Mathware and Soft Computing

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Artificial Vision Systems are commonly used in industrial applications. The low cost of the equipment facilitates the development of new products. In this paper we describe the use of an artificial vision system in one of the phases of a quality control process related to automotive industries: the windshield manufacturing. We intend to localize and classify the defects that were originated while manufacturing the glass that forms the windshield. We will show that a fuzzy classifier,...

Intelligent financial time series forecasting: A complex neuro-fuzzy approach with multi-swarm intelligence

Chunshien Li, Tai-Wei Chiang (2012)

International Journal of Applied Mathematics and Computer Science

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Financial investors often face an urgent need to predict the future. Accurate forecasting may allow investors to be aware of changes in financial markets in the future, so that they can reduce the risk of investment. In this paper, we present an intelligent computing paradigm, called the Complex Neuro-Fuzzy System (CNFS), applied to the problem of financial time series forecasting. The CNFS is an adaptive system, which is designed using Complex Fuzzy Sets (CFSs) whose membership functions...