LEADER 01943nam 2200613 450 001 9910819098103321 005 20180731044138.0 010 $a1-4704-0460-5 035 $a(CKB)3360000000465040 035 $a(EBL)3114207 035 $a(SSID)ssj0000889103 035 $a(PQKBManifestationID)11478606 035 $a(PQKBTitleCode)TC0000889103 035 $a(PQKBWorkID)10866183 035 $a(PQKB)11786847 035 $a(MiAaPQ)EBC3114207 035 $a(RPAM)14226148 035 $a(PPN)195417445 035 $a(EXLCZ)993360000000465040 100 $a20060111h20062006 uy| 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aOn boundary interpolation for matrix valued Schur functions /$fVladimir Bolotnikov, Harry Dym 210 1$aProvidence, Rhode Island :$cAmerican Mathematical Society,$d[2006] 210 4$dİ2006 215 $a1 online resource (122 p.) 225 1 $aMemoirs of the American Mathematical Society,$x0065-9266 ;$vnumber 856 300 $a"Volume 181, number 856 (end of volume)." 311 $a0-8218-4047-9 320 $aIncludes bibliographical references. 327 $a""Bibliography"" 410 0$aMemoirs of the American Mathematical Society ;$vno. 856. 606 $aSchur functions 606 $aInterpolataion spaces 606 $aMoment problems (Mathematics) 606 $aLyapunov functions 615 0$aSchur functions. 615 0$aInterpolataion spaces. 615 0$aMoment problems (Mathematics) 615 0$aLyapunov functions. 676 $a510 s 676 $a515/.73 700 $aBolotnikov$b Vladimir$f1962-$01632498 702 $aDym$b H$g(Harry),$f1938- 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910819098103321 996 $aOn boundary interpolation for matrix valued Schur functions$93971676 997 $aUNINA LEADER 04360nam 2200913z- 450 001 9910557554603321 005 20220111 035 $a(CKB)5400000000044060 035 $a(oapen)https://directory.doabooks.org/handle/20.500.12854/76670 035 $a(oapen)doab76670 035 $a(EXLCZ)995400000000044060 100 $a20202201d2021 |y 0 101 0 $aeng 135 $aurmn|---annan 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 00$aSensors for Vital Signs Monitoring 210 $aBasel, Switzerland$cMDPI - Multidisciplinary Digital Publishing Institute$d2021 215 $a1 online resource (141 p.) 311 08$a3-0365-1766-9 311 08$a3-0365-1765-0 330 $aSensor technology for monitoring vital signs is an important topic for various service applications, such as entertainment and personalization platforms and Internet of Things (IoT) systems, as well as traditional medical purposes, such as disease indication judgments and predictions. Vital signs for monitoring include respiration and heart rates, body temperature, blood pressure, oxygen saturation, electrocardiogram, blood glucose concentration, brain waves, etc. Gait and walking length can also be regarded as vital signs because they can indirectly indicate human activity and status. Sensing technologies include contact sensors such as electrocardiogram (ECG), electroencephalogram (EEG), photoplethysmogram (PPG), non-contact sensors such as ballistocardiography (BCG), and invasive/non-invasive sensors for diagnoses of variations in blood characteristics or body fluids. Radar, vision, and infrared sensors can also be useful technologies for detecting vital signs from the movement of humans or organs. Signal processing, extraction, and analysis techniques are important in industrial applications along with hardware implementation techniques. Battery management and wireless power transmission technologies, the design and optimization of low-power circuits, and systems for continuous monitoring and data collection/transmission should also be considered with sensor technologies. In addition, machine-learning-based diagnostic technology can be used for extracting meaningful information from continuous monitoring data. 606 $aEnergy industries & utilities$2bicssc 606 $aTechnology: general issues$2bicssc 610 $a3D+t modeling 610 $a4D CT 610 $aabsolute distance measurement 610 $acage deformation 610 $acardiopulmonary resuscitation (CPR) 610 $acarotid blood flow (CBF) 610 $acerebral circulation 610 $acompensatory reserve 610 $acone-beam computed tomography 610 $acontinuous-wave radar 610 $acoronary artery 610 $across-correlation 610 $aCW radar 610 $adecomposition level 610 $adenoising 610 $adoppler cardiogram 610 $aelectroencephalogram (EEG) 610 $aenvelope detection 610 $afrequency discrimination 610 $afrequency-shift keying radar 610 $aheartbeat accuracy improvement 610 $aheartbeat detection 610 $ahemodynamic data 610 $alow-contrast object 610 $amedical monitoring 610 $amodulation transfer function 610 $amother wavelet function 610 $anoise power spectrum 610 $anon-rigid registration 610 $aoptimal filter 610 $apassenger detection 610 $aphysiology 610 $aradar feature vector 610 $aradar machine learning 610 $aradar signal processing 610 $asignal decomposition 610 $asignal-to-noise-ratio 610 $aultra-high resolution 610 $avital signs 610 $avital-signs monitoring 610 $awavelet transform 610 $awearable sensors 615 7$aEnergy industries & utilities 615 7$aTechnology: general issues 700 $aYang$b Jong-Ryul$4edt$01295515 702 $aHyun$b Eugin$4edt 702 $aKim$b Sun Kwon$4edt 702 $aYang$b Jong-Ryul$4oth 702 $aHyun$b Eugin$4oth 702 $aKim$b Sun Kwon$4oth 906 $aBOOK 912 $a9910557554603321 996 $aSensors for Vital Signs Monitoring$93025902 997 $aUNINA