ABSTRACT
Neural networks with real-valued parameters have been widely studied and successfully applied to numerous problems. However, many types of data exhibit multidimensional or oscillatory structures that are not optimally represented in the real domain. In such cases, number systems extending the reals, such as complex numbers and quaternions, offer a more natural framework for data representation and processing.
