We consider a notion of morphism of neural networks and develop its properties. We show how, given any definite logic program P, the least fixed point of the immediate consequenc...
Despite the well-known performances and the theoretical power of neural networks, learning and generalizing are sometimes very difficult. In this article, we investigate how short ...
Abstract The Little-Hopfield neural network programmed with Horn clauses is studied. We argue that the energy landscape of the system, corresponding to the inconsistency function f...
Saratha Sathasivam, Wan Ahmad Tajuddin Wan Abdulla...
The objective in any pattern recognition problem is to capture the characteristics common to each class from feature vectors of the training data. While Gaussian mixture models ap...
This paper presents our Recurrent Control Neural Network (RCNN), which is a model-based approach for a data-efficient modelling and control of reinforcement learning problems in di...