1. A multi-criteria event detection system comprising: a plurality of sensors, wherein each said sensor is capable of detecting a signature characteristic of a presence of an event and providing an output indicating the same; a processor for receiving each of said outputs of said plurality of sensors, said processor including a probabilistic neural network for processing said outputs, and wherein said probabilistic neural network comprises a nonlinear, non-parametric pattern recognition algorithm that operates by defining a probability density function for a plurality of data sets that are each based on a training set data and an optimized kernel width parameter, and wherein said plurality of data sets includes: a baseline, non-event, first data set; a second, event data set; and a third, nuisance data set; wherein said algorithm provides a decisional output indicative of the presence of the event based on recognizing and discriminating between said data sets and whether said outputs suffice to substantially indicate the presence of the event as opposed to the non-event or a nuisance situation.