Language:
English
繁體中文
Help
Login
Back
Switch To:
Labeled
|
MARC Mode
|
ISBD
Adapted Compressed Sensing for Effec...
~
Setti, Gianluca.
Adapted Compressed Sensing for Effective Hardware Implementations = A Design Flow for Signal-Level Optimization of Compressed Sensing Stages /
Record Type:
Language materials, printed : Monograph/item
Title/Author:
Adapted Compressed Sensing for Effective Hardware Implementations/ by Mauro Mangia, Fabio Pareschi, Valerio Cambareri, Riccardo Rovatti, Gianluca Setti.
Reminder of title:
A Design Flow for Signal-Level Optimization of Compressed Sensing Stages /
Author:
Mangia, Mauro.
other author:
Pareschi, Fabio.
Description:
XIV, 319 p. 180 illus., 142 illus. in color.online resource. :
Contained By:
Springer Nature eBook
Subject:
Electronic circuits. -
Online resource:
https://doi.org/10.1007/978-3-319-61373-4
ISBN:
9783319613734
Adapted Compressed Sensing for Effective Hardware Implementations = A Design Flow for Signal-Level Optimization of Compressed Sensing Stages /
Mangia, Mauro.
Adapted Compressed Sensing for Effective Hardware Implementations
A Design Flow for Signal-Level Optimization of Compressed Sensing Stages /[electronic resource] :by Mauro Mangia, Fabio Pareschi, Valerio Cambareri, Riccardo Rovatti, Gianluca Setti. - 1st ed. 2018. - XIV, 319 p. 180 illus., 142 illus. in color.online resource.
Chapter 1. Introduction to Compressed Sensing: Fundamentals and Guarantees -- Chapter 2.How (Well) Compressed Sensing Works in Practice -- Chapter 3. From Universal to Adapted Acquisition: Rake that Signal! -- Chapter 4.The Rakeness Problem with Implementation and Complexity Constraints -- Chapter 5.Generating Raking Matrices: a Fascinating Second-Order Problem -- Chapter 6.Architectures for Compressed Sensing -- Chapter 7.Analog-to-information Conversion -- Chapter 8.Low-complexity Biosignal Compression using Compressed Sensing -- Chapter 9.Security at the analog-to-information interface using Compressed Sensing.
This book describes algorithmic methods and hardware implementations that aim to help realize the promise of Compressed Sensing (CS), namely the ability to reconstruct high-dimensional signals from a properly chosen low-dimensional “portrait”. The authors describe a design flow and some low-resource physical realizations of sensing systems based on CS. They highlight the pros and cons of several design choices from a pragmatic point of view, and show how a lightweight and mild but effective form of adaptation to the target signals can be the key to consistent resource saving. The basic principle of the devised design flow can be applied to almost any CS-based sensing system, including analog-to-information converters, and has been proven to fit an extremely diverse set of applications. Many practical aspects required to put a CS-based sensing system to work are also addressed, including saturation, quantization, and leakage phenomena.
ISBN: 9783319613734
Standard No.: 10.1007/978-3-319-61373-4doiSubjects--Topical Terms:
563332
Electronic circuits.
LC Class. No.: TK7888.4
Dewey Class. No.: 621.3815
Adapted Compressed Sensing for Effective Hardware Implementations = A Design Flow for Signal-Level Optimization of Compressed Sensing Stages /
LDR
:03065nam a22003975i 4500
001
999343
003
DE-He213
005
20200706010332.0
007
cr nn 008mamaa
008
201225s2018 gw | s |||| 0|eng d
020
$a
9783319613734
$9
978-3-319-61373-4
024
7
$a
10.1007/978-3-319-61373-4
$2
doi
035
$a
978-3-319-61373-4
050
4
$a
TK7888.4
072
7
$a
TJFC
$2
bicssc
072
7
$a
TEC008010
$2
bisacsh
072
7
$a
TJFC
$2
thema
082
0 4
$a
621.3815
$2
23
100
1
$a
Mangia, Mauro.
$e
author.
$4
aut
$4
http://id.loc.gov/vocabulary/relators/aut
$3
1290938
245
1 0
$a
Adapted Compressed Sensing for Effective Hardware Implementations
$h
[electronic resource] :
$b
A Design Flow for Signal-Level Optimization of Compressed Sensing Stages /
$c
by Mauro Mangia, Fabio Pareschi, Valerio Cambareri, Riccardo Rovatti, Gianluca Setti.
250
$a
1st ed. 2018.
264
1
$a
Cham :
$b
Springer International Publishing :
$b
Imprint: Springer,
$c
2018.
300
$a
XIV, 319 p. 180 illus., 142 illus. in color.
$b
online resource.
336
$a
text
$b
txt
$2
rdacontent
337
$a
computer
$b
c
$2
rdamedia
338
$a
online resource
$b
cr
$2
rdacarrier
347
$a
text file
$b
PDF
$2
rda
505
0
$a
Chapter 1. Introduction to Compressed Sensing: Fundamentals and Guarantees -- Chapter 2.How (Well) Compressed Sensing Works in Practice -- Chapter 3. From Universal to Adapted Acquisition: Rake that Signal! -- Chapter 4.The Rakeness Problem with Implementation and Complexity Constraints -- Chapter 5.Generating Raking Matrices: a Fascinating Second-Order Problem -- Chapter 6.Architectures for Compressed Sensing -- Chapter 7.Analog-to-information Conversion -- Chapter 8.Low-complexity Biosignal Compression using Compressed Sensing -- Chapter 9.Security at the analog-to-information interface using Compressed Sensing.
520
$a
This book describes algorithmic methods and hardware implementations that aim to help realize the promise of Compressed Sensing (CS), namely the ability to reconstruct high-dimensional signals from a properly chosen low-dimensional “portrait”. The authors describe a design flow and some low-resource physical realizations of sensing systems based on CS. They highlight the pros and cons of several design choices from a pragmatic point of view, and show how a lightweight and mild but effective form of adaptation to the target signals can be the key to consistent resource saving. The basic principle of the devised design flow can be applied to almost any CS-based sensing system, including analog-to-information converters, and has been proven to fit an extremely diverse set of applications. Many practical aspects required to put a CS-based sensing system to work are also addressed, including saturation, quantization, and leakage phenomena.
650
0
$a
Electronic circuits.
$3
563332
650
0
$a
Signal processing.
$3
561459
650
0
$a
Image processing.
$3
557495
650
0
$a
Speech processing systems.
$3
564428
650
0
$a
Electronics.
$3
596389
650
0
$a
Microelectronics.
$3
554956
650
1 4
$a
Circuits and Systems.
$3
670901
650
2 4
$a
Signal, Image and Speech Processing.
$3
670837
650
2 4
$a
Electronics and Microelectronics, Instrumentation.
$3
670219
700
1
$a
Pareschi, Fabio.
$e
author.
$4
aut
$4
http://id.loc.gov/vocabulary/relators/aut
$3
1290939
700
1
$a
Cambareri, Valerio.
$e
author.
$4
aut
$4
http://id.loc.gov/vocabulary/relators/aut
$3
1290940
700
1
$a
Rovatti, Riccardo.
$e
author.
$4
aut
$4
http://id.loc.gov/vocabulary/relators/aut
$3
1290941
700
1
$a
Setti, Gianluca.
$e
author.
$4
aut
$4
http://id.loc.gov/vocabulary/relators/aut
$3
1290942
710
2
$a
SpringerLink (Online service)
$3
593884
773
0
$t
Springer Nature eBook
776
0 8
$i
Printed edition:
$z
9783319613727
776
0 8
$i
Printed edition:
$z
9783319613741
776
0 8
$i
Printed edition:
$z
9783319870656
856
4 0
$u
https://doi.org/10.1007/978-3-319-61373-4
912
$a
ZDB-2-ENG
912
$a
ZDB-2-SXE
950
$a
Engineering (SpringerNature-11647)
950
$a
Engineering (R0) (SpringerNature-43712)
based on 0 review(s)
Multimedia
Reviews
Add a review
and share your thoughts with other readers
Export
pickup library
Processing
...
Change password
Login