Abstract: Recently, Differential Dynamic Programming (DDP) and other similar algorithms have become the solvers of choice when performing non-linear Model Predictive Control (nMPC) with modern robotic ...

Department of Engineering Technology, Savannah State University, Savannah, GA, USA. Our analysis reveals that most claimed applications of Grover’s algorithm fall into one of several categories: Those ...

Abstract: Determination of source-destination connectivity in networks has long been a fundamental problem, where most existing works are based on deterministic graphs that overlook the inherent ...

Learn how to acquire and process textual data and visualize the key findings Obtain deeper insight into the most commonly used algorithms and techniques and understand their tradeoffs Implement models ...

The rise of artificial intelligence (AI) deep learning algorithms is helping to accelerate brain-computer interfaces (BCIs). Published in this month’s Nature Neuroscience is new research that shows ...

Machine learning and deep learning have been widely embraced, and even more widely misunderstood. In this article, I’ll step back and explain both machine learning and deep learning in basic terms, ...

Simulated annealing (SA) attracts more attention among classical heuristic algorithms because many combinatorial optimization problems can be easily recast as the ground state search problem of the ...

What is this book about? Scala is a highly scalable integration of object-oriented nature and functional programming concepts that make it easy to build scalable and complex big data applications.

Machine learning is a branch of artificial intelligence that includes methods, or algorithms, for automatically creating models from data. Unlike a system that performs a task by following explicit ...

A quantum computer is a machine designed to use quantum mechanics to do things which cannot be done by any machine based only on the laws of classical physics. Eventual applications of quantum ...