Abstract: A fast linear convolution algorithm based on the Discrete Hirschman Transform (DHT) has been developed recently. It performs better than the traditional convolution based on the Discrete ...

Abstract: Data-driven process monitoring has benefited from the development and application of kernel transformations, especially when various types of nonlinearity exist in the data. However, when ...

This is a preview. Log in through your library . Abstract The semi-discrete convolution with the box spline is an important tool in approximation theory. We give a formula for the difference between ...

Light-weight convolutional neural networks (CNNs) suffer performance degradation as their low computational budgets constrain both the depth (number of convolution layers) and width (number of ...

Let μn be a sequence of discrete measures on the unit circle T = ℝ/ℤ with μn (0) = 0, and μn ((-δ,δ)) → 1, as n → ∞. We prove that the sequence of convolution operators (f ⁕ μn)(x) is strong sweeping ...