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003 OCoLC;

005 20210521102427.0;

008 040116s2004 maua b 001 0 eng ;

010 a| 2004042589;

015 a| GBA4602432| bnb;

016 7 a| 0129723332| Uk;

019 a| 56640029;

020 a| 0262693151q| (pbk. ;q| alk. paper);

020 a| 9780262693158q| (pbk. ;q| alk. paper);

029 1 a| AU@b| 000025288964;

029 1 a| DEBBGb| BV019530333;

029 1 a| HR0b| 0262693151;

029 1 a| IG#b| 9780262693158;

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035 a| (Sirsi) o54356741;

035 a| (OCoLC)54356741z| (OCoLC)56640029;

042 a| pcc;

049 a| EREE;

050 00 a| QA76.87b| .S78 2004;

082 00 a| 006.3/22| 22;

084 a| CM 25002| rvk;

084 a| CM 41002| rvk;

084 a| ST 3302| rvk;

100 1 a| Stone, James V.,c| Dr.=| ^A1060210;

245 10 a| Independent component analysis :b| a tutorial introduction /c| James V. Stone.;

300 a| xviii, 193 pages :b| illustrations ;c| 23 cm;

336 a| textb| txt2| rdacontent;

337 a| unmediatedb| n2| rdamedia;

338 a| volumeb| nc2| rdacarrier;

500 a| "A Bradford book.";

504 a| Includes bibliographical references (pages 183-190) and index.;

505 00 g| I.t| Independent component analysis and blind source separation --g| 1.t| Overview of independent component analysis --g| 2.t| Strategies for blind source separation --g| II.t| The geometry of mixtures --g| 3.t| Mixing and unmixing --g| 4.t| Unmixing using the inner product --g| 5.t| Independence and probability density functions --g| III.t| Methods for blind source separation --g| 6.t| Projection pursuit --g| 7.t| Independent component analysis --g| 8.t| Complexity pursuit --g| 9.t| Gradient ascent --g| 10.t| Principal component analysis and factor analysis --g| IV.t| Applications --g| 11.t| Applications of ICA --g| V.t| Appendices --g| A.t| A vector matrix tutorial --g| B.t| Projection pursuit gradient ascent --g| C.t| Projection pursuit : stepwise separation of sources.;

520 1 a| "In Independent Component Analysis, Jim Stone presents the essentials of ICA and related techniques (projection pursuit and complexity pursuit) in a tutorial style, using intuitive examples described in simple geometric terms. The treatment fills the need for a basic primer on ICA that can be used by readers of varying levels of mathematical sophistication, including engineers, cognitive scientists, and neuroscientists who need to know the essentials of this evolving method.";

520 8 a| "Topics covered include the geometry of mixing and unmixing; methods for blind source separation; and applications of ICA, including voice mixtures, EEG, fMRI, and fetal heart monitoring. The appendixes provide a vector matrix tutorial, plus basic demonstration computer code that allows the reader to see how each mathematical method described in the text translates into working Matlab computer code."--Jacket.;

650 0 a| Neural networks (Computer science)=| ^A263002;

650 0 a| Independent component analysis.=| ^A1422746;

650 7 a| Independent component analysis.2| fast0| (OCoLC)fst01764575;

650 7 a| Neural networks (Computer science)2| fast0| (OCoLC)fst01036260;

650 17 a| Multivariate analyse.2| gtt;

949 a| QA76.87 .S78 2004h| joyner48i| 30372017459956o| jjlm;

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999 a| QA76.87 .S78 2004w| LCc| 1i| 30372017459956d| 12/8/2023e| 6/10/2023l| JGESm| JOYNERn| 8r| Ys| Yt| JGESBKu| 5/21/2021x| BOOKz| JSTACKSo| .STAFF. jjlm;

Independent component analysis : a tutorial introduction / James V. Stone.

Author/creator	Stone, James V.
Format	Book
Publication Info	Cambridge, Mass. : MIT Press, ©2004.
Description	xviii, 193 pages : illustrations ; 23 cm
Subjects	Neural networks (Computer science) Independent component analysis.

Contents	I. Independent component analysis and blind source separation -- 1. Overview of independent component analysis -- 2. Strategies for blind source separation -- II. The geometry of mixtures -- 3. Mixing and unmixing -- 4. Unmixing using the inner product -- 5. Independence and probability density functions -- III. Methods for blind source separation -- 6. Projection pursuit -- 7. Independent component analysis -- 8. Complexity pursuit -- 9. Gradient ascent -- 10. Principal component analysis and factor analysis -- IV. Applications -- 11. Applications of ICA -- V. Appendices -- A. A vector matrix tutorial -- B. Projection pursuit gradient ascent -- C. Projection pursuit : stepwise separation of sources.
Review	"In Independent Component Analysis, Jim Stone presents the essentials of ICA and related techniques (projection pursuit and complexity pursuit) in a tutorial style, using intuitive examples described in simple geometric terms. The treatment fills the need for a basic primer on ICA that can be used by readers of varying levels of mathematical sophistication, including engineers, cognitive scientists, and neuroscientists who need to know the essentials of this evolving method."
Summary	"Topics covered include the geometry of mixing and unmixing; methods for blind source separation; and applications of ICA, including voice mixtures, EEG, fMRI, and fetal heart monitoring. The appendixes provide a vector matrix tutorial, plus basic demonstration computer code that allows the reader to see how each mathematical method described in the text translates into working Matlab computer code."--Jacket.
General note	"A Bradford book."
Bibliography note	Includes bibliographical references (pages 183-190) and index.
LCCN	2004042589
ISBN	0262693151 (pbk. ; alk. paper)
ISBN	9780262693158 (pbk. ; alk. paper)

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Independent component analysis : a tutorial introduction / James V. Stone.

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