Self Organisation and Modal Learning: Algorithms and Applications

Modal learning in neural computing [33] refers to the strategic combination of modes of adaptation and learning within a single artificial neural network structure. Modes, in this context, are learning methods that are transferable from one learning architecture to another, such as weight update equations. In modal learning two or more modes may proceed in parallel in different parts of the neural computing structure (layers and neurons), or they occupy the same part of the structure, and there is a mechanism for allowing the neural network to switch between modes.