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Kokke, C.A. (author), Coutino, Mario (author), Anitori, Laura (author), Heusdens, R. (author), Leus, G.J.T. (author)
Sensor selection is a useful method to help reduce data throughput, as well as computational, power, and hardware requirements, while still maintaining acceptable performance. Although minimizing the Cramér-Rao bound has been adopted previously for sparse sensing, it did not consider multiple targets and unknown source models. In this work, we...
conference paper 2023
document
Kokke, C.A. (author), Coutino, Mario (author), Heusdens, R. (author), Leus, G.J.T. (author)
Sensor selection is a useful method to help reduce computational, hardware, and power requirements while maintaining acceptable performance. Although minimizing the Cramér-Rao bound has been adopted previously for sparse sensing, it did not consider multiple targets and unknown target directions. We propose to tackle the sensor selection problem...
conference paper 2023
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Pribić, Radmila (author), Leus, G.J.T. (author)
A stochastic approach to resolution based on information distances computed from the geometry of data models which is characterized by the Fisher information is explored. Stochastic resolution includes probability of resolution and signal-to-noise ratio (SNR). The probability of resolution is assessed from a hypothesis test by exploiting...
conference paper 2018