Abstract: Convolution is fundamental in digital signal processing across many applications. Existing works enable N-point linear convolution via N-point right-angle circular convolution (RCC) based on ...
Abstract: Fast Fourier Transformation (FFT) has been widely recognized as an effective method for reducing the computational density of convolutional neural networks (CNNs). However, existing ...
Aging and Cardiovascular Discovery Center (C.G., M.C., V.M., C.B., D.J., C.T., Z.C., M.T., A.K.R., V.N.S.G., R.K.), Lewis Katz School of Medicine, Temple University ...
Aging and Cardiovascular Discovery Center, Lewis Katz School of Medicine, Temple University, Philadelphia, PA. (C.G., M.C., V.M., C.B., D.J., C.T., Z.C., M.T., A.K.R ...
The esp-nn optimized convolution functions are producing incorrect outputs, leading to a significant drop in model accuracy from 92% to below 70%. When using the standard ANSI C implementation, the ...
ABSTRACT: Based on complex variable theory, this study investigates the scattering of SH-waves by a circular inclusion in exponentially inhomogeneous media with nanoscale-dependent density and modulus ...
A windowed sinc function can implement a low-pass filter, and a two-dimensional convolutional filter can blur or sharpen images. In part 3 of this series, we introduced a low-pass filter based on the ...
Circular functions, primarily sine and cosine, are fundamental to understanding how waves—such as sound and electrical signals—are mathematically modeled and manipulated. These periodic functions have ...
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