Information Theory The Big Idea Reading Passage
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Information Theory The Big Idea Reading Passage
Paragraph A
In April 2002, an event was conducted to demonstrate the application of information theory. In 1977, the space probe Voyager I was launched. It had returned images of Jupiter and Saturn and then came out of the solar system on a one-way mission to the star. 5 years later, it started to be exposed to freezing temperatures and showed its age. NASA experts thought that they had to do something with their probe forever and that sensors and circuits were on the edge of failing condition. As a result, it was to get information to Voyager I to guide it in using the spares to change the failing parts. This was not an easy task because it was 12 billion kilometres away from Earth. The radio dish belonged to the NASA deep space network. The information was sent into the depths of space. It took over 1 hour to reach its target even though it was travelling at the speed of light, which is far beyond the orbit of Pluto.
Paragraph B
In history, it was the longest process of repair and a triumph for NASA engineers. But shows an American Communications engineer, Claude Shannon, who died just a year ago, and it highlights the astonishing power. Shannon was born in 1916 in Petoskey, Michigan, and he showed his talent for maths and building gadgets. When still a student, he made breakthroughs in the foundation of computer technology at Bell Laboratories; he developed data theory but shunned the results as acclaim. In 1940, he created a full science of communication, which was infused with DVDs from satellite communication to bar codes-in short, where data has to be conveyed correctly.
Paragraph C
In 1939, at the famous Massachusetts Institute of Technology, Shannon, when he was 22 years old, held his graduate engineering student; it all seemed light years away from the responsibility for his work. Shannon set out with an apparently simple aim: the correct meaning of the concept of data. The most fundamental form of information, whether it is true or false, is in the form of a binary unit like 1 or 0. Confusion is used to transmit information from place to place. Shannon has discovered something surprising in the process: it is always possible that data will get through random interference- ‘unwanted sound.’
Paragraph D
Unwanted sound, which is also called noise, interferes with genuine information. Effects of noise in information theory generalised this idea via theorem capture with the help of mathematical precision. Shannon has shown that, especially when the noise sets a limit rate, the information is passed along communication channels error-free. It depends on the strength of the wave and unwanted sound travelling down the communication channel, as well as on its dimensions. As a result, the limit is given per second by units of bit, and the maximum rate of error-free communication is given wave and unwanted sound levels. Shannon used a trick to find out how to pack up coding information to cope with the ruin of unwanted sounds. The communication system is used when it stays within the capability of information-carrying capacity.
Paragraph E
Scientists have devised many methods, like coding methods, over the years. They also proved that those methods played an important role in many technologies. The voyager spacecraft transmitted data using codes that added one additional bit for each and every single bit of information. As a result, there was an error rate of just one bit in 10000, and it had stunningly clear pictures of the planets. Other codes have become part of day-to-day life, such as the universal product code or barcode; it is a simple error-detecting system that ensures supermarket checkout lasers can easily read the price even if it is a crumpled bag of crisps. Recently, engineers made a major breakthrough by discovering code called turbo codes in the year 1993- it is very close to Shannon's ultimate limit of the maximum rate at which data can be transmitted reliably, and now it is playing a major role in the mobile video phone revolution.
Paragraph F
Shannon also laid the basis for more fruitful ways of storing information, such as getting rid of excess (‘ redundant’) bits from data that give little real information. ‘I CN C U’ like shown in mobile phone text messages, it can be more possible to leave out the data without losing correct meaning. Like correcting mistakes, even messages have become too obscure. Shannon has shown how to calculate the limit and he also shown how to minimise methods that cram the maximum into the minimum space.
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