00921nam a2200229 i 4500991002176589707536070223s2006 it b 000 0 ita db13487371-39ule_instDip.to Filologia Class. e Scienze Filosoficheita230Nardi, Enzo207748Ateismo e desiderio di Dio nell'opera di Henri De Lubac /Enzo Nardi Lucca :Edizioni modernografica,c2006479 p. ;24 cmContiene riferimenti bibliograficiLubac, Henri :dePensiero teologico.b1348737123-02-0723-02-07991002176589707536LE007 230 NAR 01.0212007000115701le007pE40.00-l- 00000.i1437733023-02-07Ateismo e desiderio di Dio nell'opera di Henri De Lubac1096276UNISALENTOle00723-02-07ma -itait 0005904nam 2201501z- 450 991055769330332120210501(CKB)5400000000044598(oapen)https://directory.doabooks.org/handle/20.500.12854/68367(oapen)doab68367(EXLCZ)99540000000004459820202105d2021 |y 0engurmn|---annantxtrdacontentcrdamediacrrdacarrierSensor Signal and Information Processing IIIBasel, SwitzerlandMDPI - Multidisciplinary Digital Publishing Institute20211 online resource (394 p.)3-0365-0012-X 3-0365-0013-8 In the current age of information explosion, newly invented technological sensors and software are now tightly integrated with our everyday lives. Many sensor processing algorithms have incorporated some forms of computational intelligence as part of their core framework in problem-solving. These algorithms have the capacity to generalize and discover knowledge for themselves and to learn new information whenever unseen data are captured. The primary aim of sensor processing is to develop techniques to interpret, understand, and act on information contained in the data. The interest of this book is in developing intelligent signal processing in order to pave the way for smart sensors. This involves the mathematical advancement of nonlinear signal processing theory and its applications that extend far beyond traditional techniques. It bridges the boundary between theory and application, developing novel theoretically inspired methodologies targeting both longstanding and emergent signal processing applications. The topics range from phishing detection to integration of terrestrial laser scanning, and from fault diagnosis to bio-inspired filtering. The book will appeal to established practitioners, along with researchers and students in the emerging field of smart sensor signal processing.History of engineering and technologybicsscADMMAkaike information criterionaluminum ingotaudio signal processingBayesian trackingblind signal separationbrain CT imagebrain-computer interfacecomplexitycompressed sensingcomputational efficiencycomputed tomographycosine lossCSIcyclic spectrumdata reductiondecision tree-support vector machinedeep learningdictionary learningDifference of Gaussiandual-function radar-communicationsEEGequivalent bias anglesfingerprintingfrequency-hopping codegearbox faultgeometric calibrationhigh-order cumulanthuman-robot interactionimage captioningimage reconstructionimage registrationinception-v3indoor localizationinformation embeddinginternet of thingsInternet of Things (IoT)inverse problemskalman filterLaplacian scoreslarge deformationlinear array push-broom sensorlong short-term memory networklong- and short-period errorsLoRaWANlow-dose CTmachine learningmask gradient responsemedical image registrationmicro-vibrationmodulation classificationmotor imagerymultiple-input multiple-output (MIMO)mutual information (mi)n/aneural networknoise filteringnon-rigid transformationnonlinear autoregressivenonlocal total variationnonnegative matric factorizationpermutation entropy (PE)pianistsproximal splittingreaction wheelregistration accuracyreverse dispersion entropy (RDE)reverse permutation entropy (RPE)row-actionsensor signalsensorssignal denoisingsignal detectionsimilarity measuresingular value decompositionsleep stagesound event classificationsparse recoverysparse-view CTspectroscopystable recoverystate space modelsupport vector machinessurface inspectiontensor principal component pursuittensor SVDthe multi-inputs convolutional neural networksthe single shot multibox detector networksthree-dimensional (3D) visiontime series analysiswaveform optimizationwavelet packetweakly supervisedweighted-permutation entropy (W-PE)wind turbineHistory of engineering and technologyWoo Wai Lokedt1327837Gao BinedtWoo Wai LokothGao BinothBOOK9910557693303321Sensor Signal and Information Processing III3038162UNINA