Adaptive resonance is a term often used in the context of artificial neural networks, referring to the ability of these networks to adapt and learn from input data. There are several synonyms that can be used to describe this phenomenon, such as self-organizing, self-learning, and self-adapting. Other related terms include neural plasticity, dynamic learning, and continuous learning. Each of these terms emphasizes the dynamic nature of neural networks, which are able to adjust and improve their performance based on ongoing feedback. As researchers continue to explore the potential of these networks in a variety of applications, the language used to describe their capabilities will continue to evolve and expand.