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Amplitude and frequency are the two primary features of one-dimensional signals, and thus both are widely utilized to analysis data in numerous fields. While amplitude can be examined directly, frequency requires more elaborate approaches, except in the si ...
Independent component analysis (ICA) is a suitable method for decomposing functional magnetic resonance imaging (fMRI) activity into spatially independent patterns. Practice has revealed that low-pass filtering prior to ICA may improve ICA results by reduc ...
We propose a new, general, method for spatial filtering by beam-forming. The desired filter, specified analytically on an n-dimensional sphere, is extended to n+1-dimensional Euclidean space. A continuous beamforming function is then obtained by the n+1-di ...
A low power sub-sampling multi-channel 2.4-GHz receiver front-end is presented. Bulk Acoustic Wave (BAW) resonators which intrinsically exhibit high quality factor (Q) are exploited in the frequency synthesis to provide low phase noise signal with low powe ...
We present the characterization of dyed doped/modified Epocore resist (Microresist Technology, Germany) with three commercially-available dyes (Proquimac Color, Spain). After being doped with lilac, red and yellow dyes in a 1:2500 ratio (dye:Epocore, w:w), ...
It is generally accepted that filtering microRNA (miRNA) target predictions by conservation or by accessibility can reduce the false discovery rate. However, these two strategies are usually not exploited in a combined and flexible manner. Here, we introdu ...
In this study, two reconfigurable bandpass filters are presented. The first filter is able to switch between WiFi and universal mobile telecommunications (UMTS) transmit band standards. Centre frequency, bandwidth and power specifications are precisely met ...
This paper presents a new approach to measuring similarity over massive time-series data. Our approach is built on two principles: one is to parallelize the large amount computation using a scalable cloud serving system, called TimeCloud. The another is to ...
We propose an approach for the estimation of sparse filters from a convolutive mixture of sources, exploiting the time-domain sparsity of the mixing filters and the sparsity of the sources in the time-frequency (TF) domain. The proposed approach is based o ...
We consider the problem of estimating multiple filters from convolutive mixtures of several unknown sources. We propose to exploit both the time-frequency (TF) sparsity of the sources and the sparsity of the mixing filters. Our framework consists of: a) a ...