Isodipole textures are pairs of texture ensembles whose autocorrelations, and hence power spectra, are equal. Examples of readily discriminable isodipole textures are well known. Such discriminations appear to require feature extraction, since the isodipole condition eliminates ensemble differences in spatial frequency content. We studied the effects of phase decorrelation on VEP indices of dis...

Many cerebellar models use a form of synaptic plasticity that implements decorrelation learning. Parallel fibers carrying signals positively correlated with climbing-fiber input have their synapses weakened (long-term depression), whereas those carrying signals negatively correlated with climbing input have their synapses strengthened (long-term potentiation). Learning therefore ceases when all...

In this contribution we study azimuthal angle decorrelation in inclusive dijet cross sections taking into account the next–to–leading (NLO) corrections to the BFKL kernel while keeping the jet vertices at leading order. We show how the angular decorrelation for jets with a wide relative separation in rapidity largely decreases when the NLO corrections are included.

The interferometric synthetic aperture radiometer (InSARad) is a microwave imaging instrument with the large field of view and high spatial resolution by synthetic aperture technique. However, its performance is limited to the decorrelation effects. A space variant degradation image restoration method based on coordinate transform to alleviate the decorrelation effects is presented, and its val...

Machine learning systems, especially the methods based on deep learning, enjoy great success in modern computer vision tasks under ideal experimental settings. Generally, these classic are built i.i.d. assumption, supposing training and test data drawn from same distribution independently identically. However, aforementioned assumption is, general, unavailable real-world scenarios, as a result,...

We propose a contemporaneous bilinear transformation for p × q matrix time series to alleviate the difficulties in modeling and forecasting when and/or are large. The resulting transformed assumes block structure consisting of several small matrices, those uncorrelated across all times. Hence, an overall parsimonious model is achieved by each separately without loss information on linear dynami...

The design of an optimum front-end module for an automatic speech recognition system is still a great effort of many research teams all over the world. Prepared paper wants to contribute partly to these discussions. It is especially aimed at feature decorrelation techniques based on Maximum Linear Likelihood Transform (MLLT) applied at a different level of matrix clustering. Also the comparison...

In multi-antenna system, the correlations between the receiver antennas degrades the systems performance. In this paper, we propose a spatial decorrelation receiving technique in frequency-selective SIMO channels. A spatial-to-modal matrix is placed after the SIMO channel output to remove the correlations between the receiver antennas caused by the limited antenna separations. Simulation result...