The use of dynamic synapse neural networks for speech processing tasks
Sageev George · University of Southern California Digital Library · 2015
Automated signal processing systems have become increasingly popular in the modern world. One challenge to developing such systems is the user's inability or lack of desire to provide large sample sets for model development or classification tasks. In such situations, a complete statistical description of signals to be classified is not possible. Nevertheless, life on earth (in particular neural systems) seems capable of temporal signal classification even when given only a small number of sample signals. -- In this thesis, I explore this seemingly incongruent situation.