In this study, we focus on investigating a nonsmooth convex optimization problem involving the l 1-norm under a non-negative constraint, with the goal of developing an inverse-problem solver for image ...

Deep neural networks (DNNs), which power modern artificial intelligence (AI) models, are machine learning systems that learn hidden patterns from various types of data, be it images, audio or text, to ...

Your browser does not support the audio element. The backpropagation algorithm is the cornerstone of modern artificial intelligence. Its significance goes far beyond ...

Abstract: To improve the estimation accuracy of the state of charge (SOC) in power batteries for electric vehicles, this study proposes a novel modeling and online SOC estimation method using Back ...

ABSTRACT: This paper proposes a unique approach to load forecasting using a fast convergent artificial neural network (ANN) and is driven by the critical need for power system planning. The Mazoon ...

Build your own backpropagation algorithm from scratch using Python — perfect for hands-on learners! Parkinson’s Isn’t Just Bad Luck. Scientists Reveal It’s Largely Preventable—and the Culprit Is All ...

Abstract: Neural Networks are indispensable tools in adaptive signal processing. Multi-layer perceptron (MLP) neural network is one of the most widely used neural network architecture. The performance ...

This file explores the working of various Gradient Descent Algorithms to reach a solution. Algorithms used are: Batch Gradient Descent, Mini Batch Gradient Descent, and Stochastic Gradient Descent ...