Claude Shannon

The capacity of a noisy channel is the maximum rate at which information can be transmitted over it with arbitrarily small error probability.

It is not necessary to understand the meaning of the message in order to define its information content.

The significant aspect is not the individual message as such, but the statistical characteristics of the ensemble of messages.

The amount of information is measured by the number of binary digits necessary to specify the message.

Redundancy is the fraction of the message which is determined by the rules of the language or by statistical probabilities.

Noise is any unwanted addition to the signal.

The entropy of a discrete set of probabilities is a measure of the average uncertainty of the outcome.

The channel capacity C is given by C = W log2(1 + P/N).

The problem of communication is essentially that of reproducing at one point either exactly or approximately a message selected at another point.

The amount of information is a logarithmic measure of the number of available choices.

Information theory is not about meaning, but about the statistical properties of symbols.

The theory is largely a statistical theory, and it is not concerned with the meaning of messages.

A message is a sequence of symbols.

The redundancy of a language is a measure of the extent to which it is predictable.

The true measure of information is the reduction of uncertainty.

The capacity of a channel is the maximum rate at which information can be transmitted over it with arbitrarily small error.

Information is a measure of the unexpectedness of a message.

The more probable the message, the less information it conveys.

A communication system consists of five parts: an information source, a transmitter, a channel, a receiver, and a destination.

The purpose of the transmitter is to encode the message into a signal suitable for transmission over the channel.