l Laboratories, the research arm of the Bell Telephone Company in the middle of the 20th century. At the time a number of communication technologies were known and used: among them were telegraph (Morse, 1844), telephone (Bell, 1876), wireless telegraph (Marconi, 1894), amplitude modulation (AM) radio (Fessenden, 1906), 233355 frequency modulation (FM) radio (Armstrong, 1936), analogue voice to digital conversion and pulse-code modulation (PCM) (Reeves, 1937), voice spectrum analysis and synthesis coding (Vocoder) (Dudley, 1937), and spread spectrum (Antheil and Lamarr, 1942). These technologies all impacted on how information in a discrete form may be transmitted. Morse code had already demonstrated that it is more efficient to use unequal code lengths to represent a letter of the alphabet as a function of its frequency of occurrence. Telephony and AM radio used a bandwidth proportional to that of the baseband signal, showing the minimum required capacity for analogue transmission. FM and spread spectrum techniques had shown that the quality/reliability of reception was a function of utilised bandwidth and therefore there existed a trade-off between frequency resource utilisation and reception quality. (The reason FM quality of sound is better is because a 3-10 times wider bandwidth compared with AM is used for the transmission of the same sounds.) Representation of voice from its analogue form to digital heralded an alternative of information transmission and 'voice coding' technologies demonstrated that the utilised bandwidth may be reduced if quality impairment can be tolerated. This led to two questions which were addressed by Shannon's paper: (1) What is the minimum number of discrete symbols (such as Morse code's dots and dashes) that are required to faithfully represent information output from a source? (2) How much discrete information may be transmitted on a band-limited channel in the presence of noise? Shannon mathematically answers these two questions using a new field of science known as 'informatio