The transmission line experiences the highest number of faults in a power system due to its high exposure and the high number of coincidences that might occur along it. This study presents an approach ...
Kernel functions are vital ingredients of several machine learning (ML) algorithms but often incur substantial memory and computational costs. We introduce an approach to kernel approximation in ML ...
This paper covers the concept of Fourier series and its application for a periodic signal. A periodic signal is a signal that repeats its pattern over time at regular intervals. The idea inspiring is ...
Abstract: Orthogonal time frequency space (OTFS) modulation has recently been identified as a suitable waveform for joint radar and communication systems. Focusing on the effect of data modulation on ...
The popularity of existing spatial transcriptomics technologies is limited by resolution, sensitivity, or speed. We utilize hybrid block codes for error-correctable barcode decomposition, enabling ...
Department of Physics, University of California, Santa Barbara, Santa Barbara, California 93106, United States Institute for Terahertz Science and Technology, University of California, Santa Barbara, ...
We discuss structure-preserving model order reduction for port-Hamiltonian systems based on a nonlinear approximation ansatz which is linear with respect to a part of the state variables of the ...
Achieving high classification performance is challenging due to non-stationarity and low signal-to-noise ratio (low SNR) characteristics of EEG signals. Spatial filtering is commonly used to improve ...
Why do humans share information with others? Large-scale sharing is one of the most prominent social phenomena of the 21st century, with roots in the oldest forms of communication. We argue that ...
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