000			02120nam a22002777a 4500
005			20250625154716.0
008			250625b |||||||| |||| 00| 0 eng d
020			_a9783111339191
040			_aCSL _cCSL
041			_2eng _aeng
084			_aD651:915 Q8;R4 _qCSL
100			_a Beyerer, Jürgen _eauthor. _9814585
245			_aPattern Recognition _b: Introduction, Features, Classifiers and Principles
250			_a2nd ed.
260			_aBoston : _bDe Gruyter, _c2024.
300			_axxv, 327p. _b: ill. _c; 24 cm.
500			_aIncludes bibliography glossary and index.
520			_aThe book offers a thorough introduction to Pattern Recognition aimed at master and advanced bachelor students of engineering and the natural sciences. Besides classification - the heart of Pattern Recognition - special emphasis is put on features: their typology, their properties and their systematic construction. Additionally, general principles that govern Pattern Recognition are illustrated and explained in a comprehensible way. Rather than presenting a complete overview over the rapidly evolving field, the book clarifies the concepts so that the reader can easily understand the underlying ideas and the rationale behind the methods. For this purpose, the mathematical treatment of Pattern Recognition is pushed so far that the mechanisms of action become clear and visible, but not farther. Therefore, not all derivations are driven into the last mathematical detail, as a mathematician would expect it. Ideas of proofs are presented instead of complete proofs. From the authors’ point of view, this concept allows to teach the essential ideas of Pattern Recognition with sufficient depth within a relatively lean book.
650			_aBayesian. _9814586
650			_aParameter Estimation. _9814587
650			_aGeneral Considerations. _9814588
650			_aStatistical pattern. _9814589
700			_a Hagmanns , Raphael _eco-author. _9814590
700			_a Stadler, Daniel _eco- author. _9814591
942			_2CC _cTEXL _hD651:915 Q8;R4 _n0
999			_c1432944 _d1432944