Time redundancy for error detecting neural networks

Concurrent error detection at an architectural level is often a basic requirement to achieve fault tolerance in neural networks for mission-critical applications. Time redundancy allows for concurrent error detection with low circuit complexity. In this paper, the use of alternating logic and complemented logic are analyzed as low-cost approaches to concurrent error detection. Different architectural approaches for the neural network design are considered to march the implementation constraints.