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 ...

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 moving-average filter can address white noise in the time domain but performs poorly in the frequency domain. In part 1 of this series, we defined convolution, denoted by the * symbol, and looked at ...

Convolution is used in a variety of signal-processing applications, including time-domain-waveform filtering. In a recent series on the inverse fast Fourier transform (FFT), we concluded with a ...

Scientists have created a novel probabilistic model for 5-minutes ahead PV power forecasting. The method combines a convolutional neural network with bidirectional long short-term memory, attention ...

This project involves implementing the forward pass of an 18-layer Convolutional Neural Network (CNN) in MATLAB for object detection. The goal is to classify 32x32x3 images into one of ten categories, ...

The world of artificial intelligence (AI) is rapidly evolving, and AI is increasingly enabling applications that were previously unattainable or very difficult to implement. A subsequent article, ...