000 03290nam a22004695i 4500
001 978-3-642-24139-0
003 DE-He213
005 20140220083303.0
007 cr nn 008mamaa
008 111024s2012 gw | s |||| 0|eng d
020 _a9783642241390
_9978-3-642-24139-0
024 7 _a10.1007/978-3-642-24139-0
_2doi
050 4 _aQ342
072 7 _aUYQ
_2bicssc
072 7 _aCOM004000
_2bisacsh
082 0 4 _a006.3
_223
100 1 _aMelin, Patricia.
_eauthor.
245 1 0 _aModular Neural Networks and Type-2 Fuzzy Systems for Pattern Recognition
_h[electronic resource] /
_cby Patricia Melin.
264 1 _aBerlin, Heidelberg :
_bSpringer Berlin Heidelberg,
_c2012.
300 _aX, 214 p.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aStudies in Computational Intelligence,
_x1860-949X ;
_v389
505 0 _aPart I: Basic Concepts and Theory -- Part II Modular Neural Networks in Pattern Recognition -- Part III Optimization of Modular Neural Networks for Pattern Recognition.
520 _aThis book describes hybrid intelligent systems using type-2 fuzzy logic and modular neural networks for pattern recognition applications. Hybrid intelligent systems combine several intelligent computing paradigms, including fuzzy logic, neural networks, and bio-inspired optimization algorithms, which can be used to produce powerful pattern recognition systems. Type-2 fuzzy logic is an extension of traditional type-1 fuzzy logic that enables managing higher levels of uncertainty in complex real world problems, which are of particular importance in the area of pattern recognition. The book is organized in three main parts, each containing a group of chapters built around a similar subject. The first part consists of chapters with the main theme of theory and design algorithms, which are basically chapters that propose new models and concepts, which are the basis for achieving intelligent pattern recognition. The second part contains chapters with the main theme of using type-2 fuzzy models and modular neural networks with the aim of designing intelligent systems for complex pattern recognition problems, including iris, ear, face and voice recognition. The third part contains chapters with the theme of evolutionary optimization of type-2 fuzzy systems and modular neural networks in the area of intelligent pattern recognition, which includes the application of genetic algorithms for obtaining optimal type-2 fuzzy integration systems and ideal neural network architectures for solving problems in this area.
650 0 _aEngineering.
650 0 _aArtificial intelligence.
650 0 _aOptical pattern recognition.
650 1 4 _aEngineering.
650 2 4 _aComputational Intelligence.
650 2 4 _aArtificial Intelligence (incl. Robotics).
650 2 4 _aPattern Recognition.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9783642241383
830 0 _aStudies in Computational Intelligence,
_x1860-949X ;
_v389
856 4 0 _uhttp://dx.doi.org/10.1007/978-3-642-24139-0
912 _aZDB-2-ENG
999 _c102262
_d102262