Sensor Signal and Information Processing III

• Autore: Woo Wai Lok
• Pubblicazione: Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021
• Descrizione fisica: 1 online resource (394 p.)
• Soggetto topico: History of engineering and technology
• Soggetto non controllato: ADMM; Akaike information criterion; aluminum ingot; audio signal processing; Bayesian tracking; blind signal separation; brain CT image; brain-computer interface; complexity; compressed sensing; computational efficiency; computed tomography; cosine loss; CSI; cyclic spectrum; data reduction; decision tree-support vector machine; deep learning; dictionary learning; Difference of Gaussian; dual-function radar-communications; EEG; equivalent bias angles; fingerprinting; frequency-hopping code; gearbox fault; geometric calibration; high-order cumulant; human-robot interaction; image captioning; image reconstruction; image registration; inception-v3; indoor localization; information embedding; internet of things; Internet of Things (IoT); inverse problems; kalman filter; Laplacian scores; large deformation; linear array push-broom sensor; long short-term memory network; long- and short-period errors; LoRaWAN; low-dose CT; machine learning; mask gradient response; medical image registration; micro-vibration; modulation classification; motor imagery; multiple-input multiple-output (MIMO); mutual information (mi); n/a; neural network; noise filtering; non-rigid transformation; nonlinear autoregressive; nonlocal total variation; nonnegative matric factorization; permutation entropy (PE); pianists; proximal splitting; reaction wheel; registration accuracy; reverse dispersion entropy (RDE); reverse permutation entropy (RPE); row-action; sensor signal; sensors; signal denoising; signal detection; similarity measure; singular value decomposition; sleep stage; sound event classification; sparse recovery; sparse-view CT; spectroscopy; stable recovery; state space model; support vector machines; surface inspection; tensor principal component pursuit; tensor SVD; the multi-inputs convolutional neural networks; the single shot multibox detector networks; three-dimensional (3D) vision; time series analysis; waveform optimization; wavelet packet; weakly supervised; weighted-permutation entropy (W-PE); wind turbine
• Persona (resp. second.): GaoBin; WooWai Lok
• Sommario/riassunto: 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.
• Titolo autorizzato: Sensor Signal and Information Processing III
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 9910557693303321
• Lo trovi qui: Univ. Federico II