TY - BOOK ID - 136187963 TI - Sensor Signal and Information Processing III AU - Woo, Wai Lok AU - Gao, Bin PY - 2021 PB - Basel, Switzerland MDPI - Multidisciplinary Digital Publishing Institute DB - UniCat KW - geometric calibration KW - long- and short-period errors KW - equivalent bias angles KW - sparse recovery KW - linear array push-broom sensor KW - deep learning KW - signal detection KW - modulation classification KW - the single shot multibox detector networks KW - the multi-inputs convolutional neural networks KW - medical image registration KW - similarity measure KW - non-rigid transformation KW - computational efficiency KW - registration accuracy KW - signal denoising KW - singular value decomposition KW - Akaike information criterion KW - reaction wheel KW - micro-vibration KW - permutation entropy (PE) KW - weighted-permutation entropy (W-PE) KW - reverse permutation entropy (RPE) KW - reverse dispersion entropy (RDE) KW - time series analysis KW - complexity KW - sensor signal KW - tensor principal component pursuit KW - stable recovery KW - tensor SVD KW - ADMM KW - kalman filter KW - nonlinear autoregressive KW - neural network KW - noise filtering KW - multiple-input multiple-output (MIMO) KW - frequency-hopping code KW - dual-function radar-communications KW - information embedding KW - mutual information (mi) KW - waveform optimization KW - spectroscopy KW - compressed sensing KW - inverse problems KW - dictionary learning KW - image registration KW - large deformation KW - weakly supervised KW - high-order cumulant KW - cyclic spectrum KW - decision treeāsupport vector machine KW - wind turbine KW - gearbox fault KW - cosine loss KW - long short-term memory network KW - indoor localization KW - CSI KW - fingerprinting KW - Bayesian tracking KW - image reconstruction KW - computed tomography KW - nonlocal total variation KW - sparse-view CT KW - low-dose CT KW - proximal splitting KW - row-action KW - brain CT image KW - audio signal processing KW - sound event classification KW - nonnegative matric factorization KW - blind signal separation KW - support vector machines KW - brain-computer interface KW - motor imagery KW - machine learning KW - internet of things KW - pianists KW - surface inspection KW - aluminum ingot KW - mask gradient response KW - Difference of Gaussian KW - inception-v3 KW - EEG KW - sleep stage KW - wavelet packet KW - state space model KW - image captioning KW - three-dimensional (3D) vision KW - human-robot interaction KW - Laplacian scores KW - data reduction KW - sensors KW - Internet of Things (IoT) KW - LoRaWAN KW - n/a KW - decision tree-support vector machine UR - https://www.unicat.be/uniCat?func=search&query=sysid:136187963 AB - 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. ER -