Infrared (IR) spectral imaging sensing is a powerful visual technique for industrial material
recognition in robot vision systems. However, the imaging sensing data have issues of …

Blind filtering is an emerging topic in various domains to recover an excitation from
responses measured by sensors. In the existing literature, the minimum entropy …

Fourier transform infrared (FTIR) imaging spectrometers are often corrupted by the problems
of band overlap and random noise during the infrared spectrum acquisition process. Such …

In the fields of industry research, infrared spectrometers are widely used in diverse
applications. However, the spectrum often suffers from band overlap and random noise due …

An FTIR spectrometer often suffers from common problems of band overlap and Poisson
noises. In this paper, we show that the issue of infrared (IR) spectrum degradation can be …

Cyber-Manufacturing combines industrial big data with intelligent analysis to find and
understand the intangible problems in decision-making, which requires a systematic method …

Blind filtering is one of the most important techniques for bearing fault diagnosis. Among
these techniques, the Box-Cox sparse measures (BCSM) filter shows its effectiveness for …

In this paper, we proposed a novel resolution enhancement model for the unknown
instrument function and infrared spectral signal estimation. The Gabor transform can be …

Infrared spectral data often exhibit band overlap and random noise when it is applied to
recognize the unknown chemical materials. To address these issues, a novel regularization …

With the development of spectral detection and photoelectric imaging, multiband spectrum is
always degraded by the random noise and band overlap during the acquisition of spectrum …