國立高雄大學圖資館 |

語系: 繁體中文

說明(常見問題)

圖資館首頁

登入

回首頁

切換: 標籤 | MARC模式 | ISBD

Compressed sensing and its applicati...

(1998 :)

Compressed sensing and its applicationsthird International MATHEON Conference 2017 /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Compressed sensing and its applicationsedited by Holger Boche ... [et al.].
其他題名:	third International MATHEON Conference 2017 /
其他作者:	Boche, Holger.
團體作者:
出版者:	Cham :Springer International Publishing :2019.
面頁冊數:	xvii, 295 p. :ill., digital ;24 cm.
Contained By:	Springer Nature eBook
標題:	Compressed sensing (Telecommunication)
電子資源:	https://doi.org/10.1007/978-3-319-73074-5
ISBN:	9783319730745$q(electronic bk.)

Compressed sensing and its applicationsthird International MATHEON Conference 2017 /
Compressed sensing and its applicationsthird International MATHEON Conference 2017 /[electronic resource] :edited by Holger Boche ... [et al.]. - Cham :Springer International Publishing :2019. - xvii, 295 p. :ill., digital ;24 cm. - Applied and numerical harmonic analysis,2296-5009. - Applied and numerical harmonic analysis..

An Introduction to Compressed Sensing -- Quantized Compressed Sensing: a Survey -- On reconstructing functions from binary measurements -- Classification scheme for binary data with extensions -- Generalization Error in Deep Learning -- Deep learning for trivial inverse problems -- Oracle inequalities for local and global empirical risk minimizers -- Median-Truncated Gradient Descent: A Robust and Scalable Nonconvex Approach for Signal Estimation -- Reconstruction Methods in THz Single-pixel Imaging.

The chapters in this volume highlight the state-of-the-art of compressed sensing and are based on talks given at the third international MATHEON conference on the same topic, held from December 4-8, 2017 at the Technical University in Berlin. In addition to methods in compressed sensing, chapters provide insights into cutting edge applications of deep learning in data science, highlighting the overlapping ideas and methods that connect the fields of compressed sensing and deep learning. Specific topics covered include: Quantized compressed sensing Classification Machine learning Oracle inequalities Non-convex optimization Image reconstruction Statistical learning theory This volume will be a valuable resource for graduate students and researchers in the areas of mathematics, computer science, and engineering, as well as other applied scientists exploring potential applications of compressed sensing.

ISBN: 9783319730745$q(electronic bk.)

Standard No.: 10.1007/978-3-319-73074-5doiSubjects--Topical Terms:

769143
Compressed sensing (Telecommunication)

LC Class. No.: TK5102.9 / .I57 2017

Dewey Class. No.: 621.3822

Compressed sensing and its applicationsthird International MATHEON Conference 2017 /
LDR:02522nmm a2200337 a 4500 001 587206
003 DE-He213
005 20200704164535.0
006 m d
007 cr nn 008maaau
008 210326s2019 sz s 0 eng d
020 $a 9783319730745$q(electronic bk.)
020 $a 9783319730738$q(paper)
024 7 $a 10.1007/978-3-319-73074-5 $2 doi
035 $a 978-3-319-73074-5
040 $a GP $c GP
041 0 $a eng
050 4 $a TK5102.9 $b .I57 2017
072 7 $a PBW $2 bicssc
072 7 $a MAT003000 $2 bisacsh
072 7 $a PBW $2 thema
082 0 4 $a 621.3822 $2 23
090 $a TK5102.9 $b .I61 2017
111 2 $n (3rd : $d 1998 : $c Amsterdam, Netherlands) $3 194767
245 1 0 $a Compressed sensing and its applications $h [electronic resource] : $b third International MATHEON Conference 2017 / $c edited by Holger Boche ... [et al.].
260 $a Cham : $b Springer International Publishing : $b Imprint: Birkhauser, $c 2019.
300 $a xvii, 295 p. : $b ill., digital ; $c 24 cm.
490 1 $a Applied and numerical harmonic analysis, $x 2296-5009
505 0 $a An Introduction to Compressed Sensing -- Quantized Compressed Sensing: a Survey -- On reconstructing functions from binary measurements -- Classification scheme for binary data with extensions -- Generalization Error in Deep Learning -- Deep learning for trivial inverse problems -- Oracle inequalities for local and global empirical risk minimizers -- Median-Truncated Gradient Descent: A Robust and Scalable Nonconvex Approach for Signal Estimation -- Reconstruction Methods in THz Single-pixel Imaging.
520 $a The chapters in this volume highlight the state-of-the-art of compressed sensing and are based on talks given at the third international MATHEON conference on the same topic, held from December 4-8, 2017 at the Technical University in Berlin. In addition to methods in compressed sensing, chapters provide insights into cutting edge applications of deep learning in data science, highlighting the overlapping ideas and methods that connect the fields of compressed sensing and deep learning. Specific topics covered include: Quantized compressed sensing Classification Machine learning Oracle inequalities Non-convex optimization Image reconstruction Statistical learning theory This volume will be a valuable resource for graduate students and researchers in the areas of mathematics, computer science, and engineering, as well as other applied scientists exploring potential applications of compressed sensing.
650 0 $a Compressed sensing (Telecommunication) $3 769143
650 0 $a Signal processing $x Mathematics $v Congresses. $3 515700
650 1 4 $a Information and Communication, Circuits. $3 276027
650 2 4 $a Fourier Analysis. $3 273776
650 2 4 $a Mathematical Applications in Computer Science. $3 530811
650 2 4 $a Machine Learning. $3 833608
650 2 4 $a Signal, Image and Speech Processing. $3 273768
700 1 $a Boche, Holger. $3 280052
710 2 $a SpringerLink (Online service) $3 273601
773 0 $t Springer Nature eBook
830 0 $a Applied and numerical harmonic analysis. $3 558836
856 4 0 $u https://doi.org/10.1007/978-3-319-73074-5
950 $a Mathematics and Statistics (SpringerNature-11649)