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Ridgelet has multi-resolution properties in direction besides scale and position. This paper proposes a geometrical multi-resolution network (GMN) based on ridgelet frame by taking ridgelet as the activation function in the hidden layer. For ridgelet is efficient in describing line, hyperplane, and other non-point like structures in high dimension, the network is capable of catching essential features...
In this work, a novel method is proposed to optimize the array geometry for DOA estimation. The method is based on minimization of fine error variances with the constraint that the gross error probability is below a certain threshold. For this purpose, a metric function that reflects the gross and fine error characteristics of the array is proposed. Theoretical analyses show that the minimization...
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