Neural networks are computing systems designed to mimic both the structure and function of the human brain. Caltech ...

Fig. 1 shows the mapping of points from the training sample in the coordinates of the two main features – u1 and u2. The color of the point corresponds to the class (red – 0, aqua – 1). From the ...

Learn how Network in Network (NiN) architectures work and how to implement them using PyTorch. This tutorial covers the concept, benefits, and step-by-step coding examples to help you build better ...

In this report, the neural identification problem is outlined and the identifiability question for a general class of recurrent neural networks is addressed. As part of the intelligent flight control ...

This paper investigates the use of neural network combining methods to improve time series forecasting performance of the traditional single keep-the-best (KTB) model. The ensemble methods are applied ...

While power tools and libraries, such as Apache Spark and Intel’s Trusted Analytics Platform, make it possible to quickly design, implement, train, and test neural network applications, it is the ...

A group of researchers reports the construction of the first reservoir computing device built with a microelectromechanical system. The neural network exploits the nonlinear dynamics of a microscale ...