Artificial Neural Networks : Comparative Study

Neural networks and conventional computers: A comparative distinction

Conventional computers employ specific algorithms to solve particular problems whereas neural networks learn by experience and example and cannot be programmed or fed with any particular algorithm to perform a specific task.

Due to inherent self-learning nature of neural networks, their activities can be sometimes unpredictable and unexpected, whereas on the contrary, the activities of conventional computers is totally predictable due to their cognitive approach of problem solving.

Human Neurons versus Artificial Neurons

An artificial neuron is a multi input and single output device having two operation modes- the training mode and the using mode.

The neuron is trained to fire (or not), for particular input patterns, in the training mode.

In the using mode, when a taught input pattern is detected at the input, its associated output becomes the current output. If the input pattern does not belong in the taught list of input patterns, the firing rule is used to determine whether to fire or not.