Abstract: The offset linear canonical transform (OLCT) plays an important role in many fields of optics and signal processing. In this paper, we address the problem of signal filtering and ...

Our research proves a conjecture from string theory asserting the vanishing of a specific convolution sum arising in the 4-graviton scattering amplitude in 10-dimensional type IIB string theory. The ...

Linear algebra is essential for understanding core data science concepts like machine learning, neural networks, and data transformations. Different books cater to various needs. Some focus on ...

ABSTRACT: The development of new technologies in smart cities is often hailed as it becomes a necessity to solve many problems like energy consumption and transportation. Wireless networks are part of ...

In seismic exploration, dense and evenly spatial sampled seismic traces are crucial for successful implementation of most seismic data processing and interpretation algorithms. Recently, numerous ...

Abstract: We illustrate some recent results on exact solutions to discrete-time l 1-norm minimization problems with convolution constraints. A fixed-point property for this class of problems is ...

CoAtNets combines convolutional and attention models to enhance performance in deep learning tasks. This hybrid model has demonstrated state-of-the-art results in image classification, particularly on ...

Currently, only 4-D input tensors (batched image-like tensors) are supported. unfoldNd implements the operation for 3d and 5d inputs and shows good performance. Like torch.nn.Fold, but supports 3d, 4d ...