05863nam 2201477z- 450 991055769330332120231214133107.0(CKB)5400000000044598(oapen)https://directory.doabooks.org/handle/20.500.12854/68367(EXLCZ)99540000000004459820202105d2021 |y 0engurmn|---annantxtrdacontentcrdamediacrrdacarrierSensor Signal and Information Processing IIIBasel, SwitzerlandMDPI - Multidisciplinary Digital Publishing Institute20211 electronic 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 & technologybicsscgeometric calibrationlong- and short-period errorsequivalent bias anglessparse recoverylinear array push-broom sensordeep learningsignal detectionmodulation classificationthe single shot multibox detector networksthe multi-inputs convolutional neural networksmedical image registrationsimilarity measurenon-rigid transformationcomputational efficiencyregistration accuracysignal denoisingsingular value decompositionAkaike information criterionreaction wheelmicro-vibrationpermutation entropy (PE)weighted-permutation entropy (W-PE)reverse permutation entropy (RPE)reverse dispersion entropy (RDE)time series analysiscomplexitysensor signaltensor principal component pursuitstable recoverytensor SVDADMMkalman filternonlinear autoregressiveneural networknoise filteringmultiple-input multiple-output (MIMO)frequency-hopping codedual-function radar-communicationsinformation embeddingmutual information (mi)waveform optimizationspectroscopycompressed sensinginverse problemsdictionary learningimage registrationlarge deformationweakly supervisedhigh-order cumulantcyclic spectrumdecision tree-support vector machinewind turbinegearbox faultcosine losslong short-term memory networkindoor localizationCSIfingerprintingBayesian trackingimage reconstructioncomputed tomographynonlocal total variationsparse-view CTlow-dose CTproximal splittingrow-actionbrain CT imageaudio signal processingsound event classificationnonnegative matric factorizationblind signal separationsupport vector machinesbrain-computer interfacemotor imagerymachine learninginternet of thingspianistssurface inspectionaluminum ingotmask gradient responseDifference of Gaussianinception-v3EEGsleep stagewavelet packetstate space modelimage captioningthree-dimensional (3D) visionhuman-robot interactionLaplacian scoresdata reductionsensorsInternet of Things (IoT)LoRaWANHistory of engineering & technologyWoo Wai Lokedt1327837Gao BinedtWoo Wai LokothGao BinothBOOK9910557693303321Sensor Signal and Information Processing III3038162UNINA