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: For any linear and time-invariant system, its output is the linear convolution between the variable input sequence and the constant system impulse response. When the input is long and the ...
This project involves an MNIST dataset classification model using a linear & convolution approach. The model is designed to recognize handwritten digits with high accuracy. With 3 convolution and 1 ...
Repeated convolution and truncation of a truncated fat-tailed distribution, instead of Monte Carlo simulation, for pricing a discrete, simple barrier option is presented. The parameters for the ...
A desktop application built with Python to provide an intuitive, animated visualization of discrete and continuous time convolution and correlation. This tool is designed for students, educators, and ...
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 ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results