Temporally-asymmetric Hebbian learning is a class of algorithms motivated by data from recent neurophysiology experiments. While traditional Hebbian learning rules use mean firin...
A variety of modern technologies such as networks, Internet, and electronic services demand private and secure communications for a great number of everyday transactions. Security ...
Cellular Neural Networks are widely used with real-time image processing's applications. Such systems can be efficiently realized using macro enriched fieldprogrammable gate-...
Reconfigurable hardware has become a well-accepted option for implementing digital signal processing (DSP). Traditional devices such as field-programmable gate arrays offer good fi...
Linear projection equations arise in many optimization problems and have important applications in science and engineering. In this paper, we present a recurrent neural network fo...