Order Total (1 Item Items):
Shipping Destination:
Salazar Addisson (28 results)
Skip to main search results
Search filters
Product Type
- All Product Types
- Books (28)
- Magazines & Periodicals (No further results match this refinement)
- Comics (No further results match this refinement)
- Sheet Music (No further results match this refinement)
- Art, Prints & Posters (No further results match this refinement)
- Photographs (No further results match this refinement)
- Maps (No further results match this refinement)
- Manuscripts & Paper Collectibles (No further results match this refinement)
Condition Learn more
- New (23)
- As New, Fine or Near Fine (5)
- Very Good or Good (No further results match this refinement)
- Fair or Poor (No further results match this refinement)
- As Described (No further results match this refinement)
Binding
Collectible Attributes
- First Edition (No further results match this refinement)
- Signed (No further results match this refinement)
- Dust Jacket (No further results match this refinement)
- Seller-Supplied Images (12)
- Not Print on Demand (16)
Language (1)
Price
- Any Price
- Under £ 20 (No further results match this refinement)
- £ 20 to £ 35 (No further results match this refinement)
- Over £ 35
Free Shipping
- Free Shipping to U.S.A. (No further results match this refinement)
Seller Location
Seller Rating
-
On Statistical Pattern Recognition in Independent Component Analysis Mixture Modelling (Springer Theses, 4)
Seller: Ria Christie Collections, Uxbridge, United Kingdom
Seller rating 5 out of 5 stars
£ 96.88
£ 11.98 shipping
Ships from United Kingdom to U.S.A.Quantity: Over 20 available
Add to basketCondition: New. In.
-
On Statistical Pattern Recognition in Independent Component Analysis Mixture Modelling (Springer Theses, 4)
Seller: Ria Christie Collections, Uxbridge, United Kingdom
Seller rating 5 out of 5 stars
£ 96.88
£ 11.98 shipping
Ships from United Kingdom to U.S.A.Quantity: Over 20 available
Add to basketCondition: New. In.
-
-
-
On Statistical Pattern Recognition in Independent Component Analysis Mixture Modelling
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
Seller rating 5 out of 5 stars
Condition: New.
-
Condition: New. pp. 208.
-
Condition: New. pp. 208.
-
Hardcover. Condition: Brand New. 2013 edition. 207 pages. 9.65x0.71x6.46 inches. In Stock.
-
Taschenbuch. Condition: Neu. On Statistical Pattern Recognition in Independent Component Analysis Mixture Modelling | Addisson Salazar | Taschenbuch | Springer Theses | xxii | Englisch | 2014 | Springer | EAN 9783642428753 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
-
On Statistical Pattern Recognition in Independent Component Analysis Mixture Modelling
Language: English
Published by Springer Berlin Heidelberg, 2014
ISBN 10: 3642428754 ISBN 13: 9783642428753
Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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.
-
On Statistical Pattern Recognition in Independent Component Analysis Mixture Modelling
Language: English
Published by Springer Berlin Heidelberg, 2012
ISBN 10: 3642307515 ISBN 13: 9783642307515
Buch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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.
-
On Statistical Pattern Recognition in Independent Component Analysis Mixture Modelling
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
Seller rating 5 out of 5 stars
£ 162.99
£ 15 shipping
Ships from United Kingdom to U.S.A.Quantity: Over 20 available
Add to basketCondition: As New. Unread book in perfect condition.
-
Hardcover. Condition: Like New. LIKE NEW. SHIPS FROM MULTIPLE LOCATIONS. book.
-
Condition: As New. Unread book in perfect condition.
-
Paperback. Condition: Like New. LIKE NEW. SHIPS FROM MULTIPLE LOCATIONS. book.
-
Independent Component Analysis (Ica)
Language: English
Published by NOVA SCIENCE PUBLISHERS INC (11/2018), 2018
ISBN 10: 1536139947 ISBN 13: 9781536139945
Condition: Used: Like New. LIVRE A L?ETAT DE NEUF. EXPEDIE SOUS 3 JOURS OUVRES. NUMERO DE SUIVI COMMUNIQUE AVANT ENVOI, EMBALLAGE RENFORCE. EAN:9781536139945.
-
Condition: new. Questo è un articolo print on demand.
-
Condition: new. Questo è un articolo print on demand.
-
On Statistical Pattern Recognition in Independent Component Analysis Mixture Modelling
Language: English
Published by Springer Berlin Heidelberg Aug 2014, 2014
ISBN 10: 3642428754 ISBN 13: 9783642428753
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
Seller rating 5 out of 5 stars
Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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. 208 pp. Englisch.
-
On Statistical Pattern Recognition in Independent Component Analysis Mixture Modelling
Language: English
Published by Springer Berlin Heidelberg Jul 2012, 2012
ISBN 10: 3642307515 ISBN 13: 9783642307515
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
Seller rating 5 out of 5 stars
Buch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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. 208 pp. Englisch.
-
On Statistical Pattern Recognition in Independent Component Analysis Mixture Modelling
Language: English
Published by Springer Berlin Heidelberg, 2014
ISBN 10: 3642428754 ISBN 13: 9783642428753
Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Nominated as an outstanding PhD theses by the Polytechnic University of ValenciaPresent an excellent state-of-the-art literature review of the main applied theoretical foundations of statistical pattern recognition Gives new insights into.
-
On Statistical Pattern Recognition in Independent Component Analysis Mixture Modelling
Language: English
Published by Springer Berlin Heidelberg, 2012
ISBN 10: 3642307515 ISBN 13: 9783642307515
Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Nominated as an outstanding PhD theses by the Polytechnic University of ValenciaPresent an excellent state-of-the-art literature review of the main applied theoretical foundations of statistical pattern recognition Gives new insights into.
-
Condition: New. Print on Demand pp. 208 73 Figures, 49:B&W 6.14 x 9.21 in or 234 x 156 mm (Royal 8vo) Perfect Bound on White w/Gloss Lam.
-
Condition: New. Print on Demand pp. 208 73 Figures, 52:B&W 6.14 x 9.21in or 234 x 156mm (Royal 8vo) Case Laminate on White w/Gloss Lam.
-
Condition: New. PRINT ON DEMAND pp. 208.
-
Condition: New. PRINT ON DEMAND pp. 208.
-
On Statistical Pattern Recognition in Independent Component Analysis Mixture Modelling
Language: English
Published by Springer, Springer Jul 2012, 2012
ISBN 10: 3642307515 ISBN 13: 9783642307515
Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germany
Seller rating 5 out of 5 stars
Buch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -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.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 208 pp. Englisch.
-
On Statistical Pattern Recognition in Independent Component Analysis Mixture Modelling
Language: English
Published by Springer, Springer Aug 2014, 2014
ISBN 10: 3642428754 ISBN 13: 9783642428753
Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germany
Seller rating 5 out of 5 stars
Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -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.Springer-Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 208 pp. Englisch.
