Modern information theory was first published in 1948 by Claude Elmwood Shannon [1431,1432]. (His papers have been reprinted by the IEEE Press [1433].) For a good mathematical treatment of the topic, consult [593]. In this section, I will just sketch some important ideas.

Information theory defines the **amount of information** in a message as the minimum number of bits needed to encode all possible meanings of that message, assuming all messages are equally likely. For example, the day-of-the-week field in a database contains no more than 3 bits of information, because the information can be encoded with 3 bits:

000 = Sunday 001 = Monday 010 = Tuesday 011 = Wednesday 100 = Thursday 101 = Friday 110 = Saturday 111 is unused

If this information were represented by corresponding ASCII character strings, it would take up more memory space but would not contain any more information. Similarly, the “sex” field of a database contains only 1 bit of information, even though it might be stored as one of two 6-byte ASCII strings: “MALE” or “FEMALE.”

Formally, the amount of information in a message *M* is measured by the **entropy** of a message, denoted by H(*M*). The entropy of a message indicating sex is 1 bit; the entropy of a message indicating the day of the week is slightly less than 3 bits. In general, the entropy of a message measured in bits is log_{2} *n*, in which *n* is the number of possible meanings. This assumes ...

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