Springer, 2001. — 328 p.
Pattern recognition currently comprises a vast body of methods supporting the development of numerous applications in many different areas of activity. The generally recognized relevance of pattern recognition methods and techniques lies, for the most part, in the general trend or "intelligent" task emulation, which has definitely pervaded our daily life. Robot assisted manufacture, medical diagnostic systems, forecast of economic variables, exploration of Earth's resources, and analysis of satellite data are just a few examples of activity fields where this trend applies. The pervasiveness of pattern recognition has boosted the number of taskspecific methodologies and enriched the number of links with other disciplines. As counterbalance to this dispersive tendency there have been, more recently, new theoretical developments that are bridging together many of the classical pattern recognition methods and presenting a new perspective of their links and inner workings.
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