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Titolo:
Signal processing and pattern recognition with soft computing
Autore:
Suzuki, Y; Itakura, KI; Saga, S; Maeda, J;
Indirizzi:
Muroran Inst Technol, Dept Comp Sci & Syst Engn, Muroran, Hokkaido 05008585, Japan Muroran Inst Technol Muroran Hokkaido Japan 05008585 aido 05008585, Japan
Titolo Testata:
PROCEEDINGS OF THE IEEE
fascicolo: 9, volume: 89, anno: 2001,
pagine: 1297 - 1317
SICI:
0018-9219(200109)89:9<1297:SPAPRW>2.0.ZU;2-P
Fonte:
ISI
Lingua:
ENG
Soggetto:
IMAGE SEGMENTATION TECHNIQUES; NEURAL NETWORKS; GENETIC ALGORITHM; QRS DETECTION; FRACTAL DIMENSION; ECG ANALYSIS; FUZZY-SETS; CLASSIFICATION; CLASSIFIERS; FEATURES;
Keywords:
ART2; Cps detection; electrocardiogram; evolutionary computing; fractal dimension; freehand drawing; fuzzy logic; fuzzy systems; geostructure; human interface; image segmentation; MART; natural images; neural networks; region-growing algorithm; soft computing; visualization;
Tipo documento:
Review
Natura:
Periodico
Settore Disciplinare:
Engineering, Computing & Technology
Citazioni:
105
Recensione:
Indirizzi per estratti:
Indirizzo: Suzuki, Y Muroran Inst Technol, Dept Comp Sci & Syst Engn, Muroran, Hokkaido 05008585, Japan Muroran Inst Technol Muroran Hokkaido Japan 05008585 585, Japan
Citazione:
Y. Suzuki et al., "Signal processing and pattern recognition with soft computing", P IEEE, 89(9), 2001, pp. 1297-1317

Abstract

Signal processing and pattern recognition (SPPR) are one of the most attractive areas in applications of soft computing (SC). In this paper, we describe the overall role of SC in SPPR with specific applications to biomedicalengineering, geoscience for mining and civil engineering, human interface,and image processing. Detection of characteristic points in an electrocardiogram (ECG) to implement an advanced ECG analyzer is presented, which is carried out using both conventional SPPR techniques and self-organizing neural networks. Next, successful technologies for monitoring a geostructure bysupervised and self-organizing neural networks are described. Identification of a freehand drawing by a combination of fuzzy logic and neural networks is also described. Moreover application of fuzzy logic to image segmentation is presented. Finally, innovation of SPPR using SC technologies is discussed.

ASDD Area Sistemi Dipartimentali e Documentali, Università di Bologna, Catalogo delle riviste ed altri periodici
Documento generato il 04/07/20 alle ore 11:42:14