Übersicht			Auf mobile öffnen

Lieferstatus:	Auf Bestellung (Lieferzeit unbekannt)
Veröffentlichung:	Juli 2012
Genre:	Naturwissensch., Medizin, Technik
	Applied Dynamical Systems / Automated Pattern Recognition / B / complexity / Computational complexity / Cybernetics & systems theory / Cybernetics and systems theory / Digital and Analog Signal Processing / Digitale Signalverarbeitung (DSP) / engineering / Image processing / Kybernetik und Systemtheorie / Mathematik für Ingenieure / Mustererkennung / pattern recognition / Signal Processing / Signal, Image and Speech Processing / Speech processing systems mehr...
ISBN:	9783642307515
EAN-Code:	9783642307515
Verlag:	Springer EN
Einband:	Gebunden
Sprache:	English
Serie:	#04 - Springer Theses
Dimensionen:	H 235 mm / B 155 mm / D
Gewicht:	483 gr
Seiten:	186
Illustration:	XXII, 186 p.
Zus. Info:	EUDR exemption - product or manufacturing materials placed on the market prior to 31.12.2025.
Bewertung:	Titel bewerten / Meinung schreiben

Inhalt:

A natural evolution of statistical signal processing, in connection with the progressive increase in computational power, has been exploiting higher-order information. Thus, high-order spectral analysis and nonlinear adaptive filtering have received the attention of many researchers. One of the most successful techniques for non-linear processing of data with complex non-Gaussian distributions is the independent component analysis mixture modelling (ICAMM). This thesis defines a novel formalism for pattern recognition and classification based on ICAMM, which unifies a certain number of pattern recognition tasks allowing generalization. The versatile and powerful framework developed in this work can deal with data obtained from quite different areas, such as image processing, impact-echo testing, cultural heritage, hypnograms analysis, web-mining and might therefore be employed to solve many different real-world problems.