Lightweight HI source finding for next generation radio surveys
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We introduce an integrated framework for detecting brain activity from fMRI data, which is based on a spatial discrete wavelet transform. Unlike the standard wavelet-based approach for fMRI analysis, we apply the suitable statistical test procedure in the ...
Extremely high data rates expected in next-generation radio interferometers necessitate a fast and robust way to process measurements in a big data context. Dimensionality reduction can alleviate computational load needed to process these data, in terms of ...
In this paper, we present our spreadsheet framework, which uses a spreadsheet-like interface for exploring biomedical datasets. The principles and advantages of this class of visualization systems are illustrated, and a case study for the analysis of hip j ...
Research on artificial neural networks (ANNs) has been carried out for more than five decades. A renewed interest appeared in the 80's with the finding of powerful models like J. Hopfield's recurrent networks, T. Kohonen's self-organizing feature maps, and ...
The representation of load dynamic characteristics remains an area of great uncertainty and it becomes a limiting factor of power systems dynamic performance analysis. A major difficulty, both for component-based and measurement-based methods, is the lack ...
A fundamental statistical problem is to indicate which of two hypotheses is better supported by the data. Statistics designed for this purpose are called weight of evidence. In this paper we study the problem of robust weights of evidence, optimal in their ...