Inspired strongly from the visual system, the Multi-layer Perceptron is a device capable of performing a classification task, learning from set of input-output associations often called training set. The presence of many layers of interconnected artificial neurons allows for a sequential processing of the raw data in input, and for the representation of arbitrarily complex non-linear functions of it. The parameters of the device are usually referred to as synaptic weights: these are able to capture complex structures (features) in the inputs, which, after the training is complete, can be used to obtain a correct classification when an unseen pattern is presented. This mechanism is likely very similar to the learning process taking place in the brain.
Nessun commento:
Posta un commento