Dynamical analysis of fractional-order fully complex-valued uncertain competitive neural networks and its application in image privacy protection

Key Points

• Image privacy protection can be enhanced using fractional-order neural networks with complex-valued dynamics.
• The study shows that uncertain dynamics in competitive networks improve performance in maintaining privacy.
• Analysis of dynamical behavior provides insights into system stability and response under varied conditions.
• Signal processing techniques for image privacy were tested using complex-valued and fractional-order systems.