Practical stability criteria for discrete fractional neural networks in product form design analysis

Abstract

In this paper, a neural network approach is suggested to the product design analysis. Namely, fractional-order neural network models are proposed as more flexible mechanism to study product form design. Since control and stability methods are fundamental in the construction and practical significance of a neural network model, appropriate controllers are designed and practical stability criteria are proposed for the fractional-order model under consideration. The stability and control analysis are based on the Lyapunov function method. Examples are elaborated to demonstrate the established results. The proposed modeling approach and the stability results are also applicable to numerous industrial design tasks.