Abstract: Inverse scattering problems (ISPs) often suffer from severe ill-posedness and nonlinearity. In this article, a parameter identification method that determines the necessary conditions of ...

Abstract: Superresolution (SR) methods become essential when an undersampled low-resolution (LR) image is unable to provide accurate target detection. The estimation of an HR image from a single LR ...

Abstract: Point cloud processing is fundamental to applications such as autonomous driving, robotic navigation, and 3D reconstruction. Sampling is a crucial process in point cloud processing, but ...

Abstract: Neural implicit fields, such as the neural signed distance field (SDF) of a shape, have emerged as a powerful representation for many applications, e.g., encoding a 3D shape and performing ...

Abstract: We propose an end-to-end attribute compression method for dense point clouds. The proposed method combines a frequency sampling module, an adaptive scale feature extraction module with ...

Abstract: Given that the sampling and arrangement of the array need a reasonable standard to guide in high-precision magnetocardiography (MCG) imaging, the sampling range required for robust ...

ABSTRACT: In many real-time resource-constrained embedded systems, highly-predictable system behavior is a key design requirement. The “time-triggered co-operative” (TTC) scheduling algorithm provides ...

Abstract: Sampling theory in fractional Fourier Transform (FrFT) domain has been studied extensively in the last decades. This interest stems from the ability of the FrFT to generalize the traditional ...

Abstract: For periodic and nonperiodic band-limited signals, the sampling of both the signal and the signal derivative enables the number of sampling points to be reduced and the sampling step between ...

Abstract: Low sampling frequency challenges the exact identification of continuous-time (CT) dynamical systems from sampled data, even when their models are identifiable. A necessary and sufficient ...