The Neural Network

Traditionally when we speak of neural network it refers to network or circuit of biological neurons. But in this modern age it refers to artificial neural networks (ANN),also called simulating neural networks (SNN) ,which is made of artificial neurons or nodes. These nodes are highly interconnected working together to solve specific problem by mimicking somehow like brain neural network. Of course brain neural network are much more complex than artificial neural networks. Neural network is used in artificial intelligence and cognitive modeling.

Thanks to neural network that it is now possible to recognize speech, analysis of image, and production of autonomous robots which can learn by own, no need to over burden a robot with huge software till its nervous break down occurs.

Neural network take a different approach to deal with problem where as conventional computer make use of algorithmic approach i.e. a sequence of instructions to solve a problem. We can say that neural network are non linear statistical data modeling or decision making tool. Neural network learn by example like our brain does. They are not been programmed to do a definite work.

Neural networks are built in by simulating the way that signals or impulses are carried by neurons in our nervous system or brain. As much is unknown about how the brain processes information the neural network model are only gross idealizations of real networks of brain.

So it's really important to understand completely the mechanism of nerve conduction. In recent year much of investigation in done in studying about neuromodulators such as dopamine, acetylcholine, and serotonin on behavior and learning. Biophysics model such as BCM theory has proved important to decipher the mechanism of neuron plasticity i.e. ability to change the strength of connection between two neurons.