Researchers have developed a compact, low-cost convolutional spectrometer that delivers lab-grade precision for applications ...

Abstract: Subsampled blind deconvolution is the recovery of two unknown signals from samples of their convolution. To overcome the ill-posedness of this problem, solutions based on priors tailored to ...

Abstract: Data-driven process monitoring has benefited from the development and application of kernel transformations, especially when various types of nonlinearity exist in the data. However, when ...