LEADER 00794nam0-2200277 --450 001 9910862297303321 005 20240617142730.0 100 $a20240617d1911----kmuy0itay5050 ba 101 0 $afre 102 $aFR 105 $aa 001yy 200 1 $aMicrobes et toxines$fEtienne Burnet$gavec une introduction de Elie Metchnikoff 210 $aParis$cFlammarion$d1911 215 $aXI, 349, 8 p.$cill.$d19 cm 225 1 $aBibliothèque de philosophie scientifique 610 0 $aMicrobi 610 0 $aTossine 676 $a616.02$v23$zita 700 1$aBurnet,$bÉtienne$01741287 801 0$aIT$bUNINA$gREICAT$2UNIMARC 901 $aBK 912 $a9910862297303321 952 $aA MIC 2141$b8964/2024$fFAGBC 959 $aFAGBC 996 $aMicrobes et toxines$94167293 997 $aUNINA LEADER 04266nam 22006375 450 001 9910299901603321 005 20200706010332.0 010 $a3-319-61373-1 024 7 $a10.1007/978-3-319-61373-4 035 $a(CKB)4340000000062783 035 $a(DE-He213)978-3-319-61373-4 035 $a(MiAaPQ)EBC4915508 035 $a(PPN)203671767 035 $a(EXLCZ)994340000000062783 100 $a20170714d2018 u| 0 101 0 $aeng 135 $aurnn#008mamaa 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aAdapted Compressed Sensing for Effective Hardware Implementations $eA Design Flow for Signal-Level Optimization of Compressed Sensing Stages /$fby Mauro Mangia, Fabio Pareschi, Valerio Cambareri, Riccardo Rovatti, Gianluca Setti 205 $a1st ed. 2018. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2018. 215 $a1 online resource (XIV, 319 p. 180 illus., 142 illus. in color.) 311 $a3-319-61372-3 320 $aIncludes bibliographical references at the end of each chapters. 327 $aChapter 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. 330 $aThis 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. 606 $aElectronic circuits 606 $aSignal processing 606 $aImage processing 606 $aSpeech processing systems 606 $aElectronics 606 $aMicroelectronics 606 $aCircuits and Systems$3https://scigraph.springernature.com/ontologies/product-market-codes/T24068 606 $aSignal, Image and Speech Processing$3https://scigraph.springernature.com/ontologies/product-market-codes/T24051 606 $aElectronics and Microelectronics, Instrumentation$3https://scigraph.springernature.com/ontologies/product-market-codes/T24027 615 0$aElectronic circuits. 615 0$aSignal processing. 615 0$aImage processing. 615 0$aSpeech processing systems. 615 0$aElectronics. 615 0$aMicroelectronics. 615 14$aCircuits and Systems. 615 24$aSignal, Image and Speech Processing. 615 24$aElectronics and Microelectronics, Instrumentation. 676 $a621.3815 700 $aMangia$b Mauro$4aut$4http://id.loc.gov/vocabulary/relators/aut$01062650 702 $aPareschi$b Fabio$4aut$4http://id.loc.gov/vocabulary/relators/aut 702 $aCambareri$b Valerio$4aut$4http://id.loc.gov/vocabulary/relators/aut 702 $aRovatti$b Riccardo$4aut$4http://id.loc.gov/vocabulary/relators/aut 702 $aSetti$b Gianluca$4aut$4http://id.loc.gov/vocabulary/relators/aut 906 $aBOOK 912 $a9910299901603321 996 $aAdapted Compressed Sensing for Effective Hardware Implementations$92527395 997 $aUNINA LEADER 01550nam0 22003851i 450 001 VAN00016349 005 20251031021355.975 010 $a88-386-0700-1 100 $a20040520d1994 |0itac50 ba 101 $aita 102 $aIT 105 $a|||| ||||| 181 $ai$b e 182 $an 183 $anc 200 1 $aStatistica per discipline biomediche$fStanton A. 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