Neural Network is the study of networks of adaptable nodes which though a process of learning from task examples, store experimental knowledge and make it available for use.

What are neural nets?
Neural Nets are artificial representation of the human brain which tries to similate how we learn or simply learning process. 


What is a Neuron ?




Biological Neuron 

Its important to understand what a biological neuron is as Neural Network is primarily designed on how a human brain does. things. 

A neuron or nerve cell is an electrically excitable cell that processes and transmits information by electrical and chemical signaling. Chemical signaling occurs via synapses, specialized connections with other cells. Neurons connect to each other to form networks. 

A number of specialized types of neurons exist: sensory neurons respond to touch, sound, light etc. 

A typical neuron is divided into three parts: the soma or cell body, dendrites, and axon. Dendrites are thin structures that arise from the cell body, often extending and branching multiple times, giving rise to a complex "dendritic tree".The axon leaves the soma at a swelling called the axon hillock, and can extend for great distances, giving rise to hundreds of branches.The axon carries nerve signals away from the soma (and also carries some types of information back to it). .The cell body of a neuron frequently gives rise to multiple dendrites, but never to more than one axon, although the axon may branch hundreds of times before it terminates. A typical synapse, then, is a contact between the axon of one neuron and a dendrite or soma of another. Synaptic signals may be excitatory or inhibitory. At the majority of synapses, signals are sent from the axon of one neuron to a dendrite of another. 

If the net excitation received by a neuron over a short period of time is large enough, the neuron generates a brief pulse called an action potential, which originates at the soma and propagates rapidly along the axon, activating synapses onto other neurons as it goes.Neuron Firing - Neurons only fire when input is bigger than some threshold. It should, however, be noted that firing doesn't get bigger as the stimulus increases, its an all or nothing arrangement. 

There are, however, many exceptions to these rules: neurons that lack dendrites, neurons that have no axon, synapses that connect an axon to another axon or a dendrite to another dendrite, etc

All neurons are electrically excitable.If the voltage changes by a large enough amount, an all-or-none electrochemical pulse called an action potential is generated, which travels rapidly along the cell's axon, and activates synaptic connections with other cells when it arrives.


The key to neural function is the synaptic signaling process, which is partly electrical and partly chemical. The electrical aspect depends on properties of the neuron's membrane.

Some ion channels are voltage gated, meaning that they can be switched between open and closed states by altering the voltage difference across the membrane. Others are chemically gated, meaning that they can be switched between open and closed states by interactions with chemicals that diffuse through the extracellular fluid. The interactions between ion channels and ion pumps produce a voltage difference across the membrane, typically a bit less than 1/10 of a volt at baseline. This voltage has two functions: first, it provides a power source for an assortment of voltage-dependent protein machinery that is embedded in the membrane; second, it provides a basis for electrical signal transmission between different parts of the membrane.

Neurons communicate by chemical and electrical synapses in a process known as synaptic transmission. The fundamental process that triggers synaptic transmission is the action potential, a propagating electrical signal that is generated by exploiting the electrically excitable membrane of the neuron. This is also known as a wave of depolarization.


Spikes (signals) arriving at an excitatory synapse tend to cause the receiving neuron to fire. Spikes (signals) arriving at an inhibitory synapse tend to inhibit the receiving neuron from firing.
The cell body and synapses essentially compute (by a complicated chemical/electrical process) the difference between the incoming excitatory and inhibitory inputs (spatial and temporal summation).
When this difference is large enough (compared to the neuron's threshold) then the neuron will fire.
Roughly speaking, the faster excitatory spikes arrive at its synapses the faster it will fire (similarly for inhibitory spikes).


Computer 


References
http://en.wikipedia.org/wiki/Neuron