Distorted Acquisition of Dynamic Events Sensed by Frequency-Scanning Fiber-Optic Interrogators and a Mitigation Strategy.

Fiber-optic dynamic interrogators, which use periodic frequency scanning, actually sample a time-varying measurand on a time grid. Commonly, however, the sampled values are reported on a time grid, synchronized with the periodic scanning. It is the novel and noteworthy message of this paper that this artificial assignment may give rise to significant distortions in the recovered signal.

Gaussian bandwidth selection for manifold learning and classification.

Kernel methods play a critical role in many machine learning algorithms. They are useful in manifold learning, classification, clustering and other data analysis tasks. Setting the kernel's scale parameter, also referred to as the kernel's bandwidth, highly affects the performance of the task in hand.

On the question of whether lubricants fluidize in stick-slip friction.

Intermittent sliding (stick-slip motion) between solids is commonplace (e.g., squeaking hinges), even in the presence of lubricants, and is believed to occur by shear-induced fluidization of the lubricant film (slip), followed by its resolidification (stick).

An estimation method for improved extraction of the decay curve signal from CPMG-like measurements with a unilateral scanner.

Unilateral NMR devices are valuable tools used to study non-invasively arbitrarily-sized objects. They have been utilized in various applications, including non-destructive testing and well logging. However, measurements with such scanners are characterized by a low sensitivity, which is mainly the result of the low and inhomogeneous magnetic field B0.

An estimation method of MR signal parameters for improved image reconstruction in unilateral scanner.

Unilateral NMR devices are used in various applications including non-destructive testing and well logging, but are not used routinely for imaging. This is mainly due to the inhomogeneous magnetic field (B0) in these scanners. This inhomogeneity results in low sensitivity and further forces the use of the slow single point imaging scan scheme.

A hybrid technique for blind separation of non-gaussian and time-correlated sources using a multicomponent approach.

Blind inversion of a linear and instantaneous mixture of source signals is a problem often encountered in many signal processing applications. Efficient fastICA (EFICA) offers an asymptotically optimal solution to this problem when all of the sources obey a generalized Gaussian distribution, at most one of them is Gaussian, and each is independent and identically distributed (i.i.

Blind separation of superimposed shifted images using parameterized joint diagonalization.

We consider the blind separation of source images from linear mixtures thereof, involving different relative spatial shifts of the sources in each mixture. Such mixtures can be caused, e.g.