The package contains a mixture of classic decoding methods and modern machine learning methods. For regression, we currently include: Wiener Filter, Wiener Cascade, Kalman Filter, Naive Bayes, Support ...

in this video, we will understand what is Recurrent Neural Network in Deep Learning. Recurrent Neural Network in Deep Learning is a model that is used for Natural Language Processing tasks. It can be ...

We will create a Deep Neural Network python from scratch. We are not going to use Tensorflow or any built-in model to write the code, but it's entirely from scratch in python. We will code Deep Neural ...

Simple Artificial Neural Networks (SANN) is a naive Python implementation of an artificial neural network (ANN) that's useful for educational purposes and clarifying the concepts of feed-forward ...

ABSTRACT: The stochastic configuration network (SCN) is an incremental neural network with fast convergence, efficient learning and strong generalization ability, and is widely used in fields such as ...

Abstract: Time-domain transient simulation is a crucial signal integrity modeling technique in high-speed link design. Recurrent Neural Network (RNN), a commonly used machine learning method for ...