A In April 2002 an event took place which demonstrated one of the many applications of information theory. A2002 年 4 月发生的事件向我们展示了众多信息理论实践中的一项。 The space probe, Voyager I, launched in 1977, had sent back spectacular images of Jupiter and Saturn and then soared out of the Solar System on a one-way mission to the stars. 1977 年发射的“旅行者 1 号”太空探测器向我们发送回了木星和土星精美绝伦的图像，然后就离开了太阳系去完成关于其他星球的单程任务。 After 25 years of exposure to the freezing temperatures of deep space, the probe was beginning to show its age. 在外太空的冰冷温度中停留了 25 年的探测器已经逐渐显示出衰老的迹象。 Sensors and circuits were on the brink of failing and NASA experts realised that they had to do something or lose contact with their probe forever. 传感器和电路都濒临崩溃的边缘，美国宇航局 (NASA) 的专家们意识到他们必须采取行动，否则将和他们的探测器永远失去联系。 The solution was to get a message to Voyager I to instruct it to use spares to change the failing parts. 解决办法就是向“旅行者 1 号”发送信息，指示它用备件替换失效的部件。 With the probe 12 billion kilometres from Earth, this was not an easy task. 探测器距离地球 120 亿公里，这绝不是一项简单的任务。 By means of a radio dish belonging to NASA's Deep Space Network, the message was sent out into the depths of space. 通过 NASA 外太空网络的无线设备，信息被发送了出去。 Even travelling at the speed of light, it took over 11 hours to reach its target, far beyond the orbit of Pluto. 即使是以光速运行，这条信息依旧用了 11 个小时到达远在冥王星轨道之外的目的地。 Yet, incredibly, the little probe managed to hear the faint call from its home planet, and successfully made the switchover. 然而，不可思议的是，这个小小的探测器设法听到了来自地球的微弱呼唤，并成功地完成了交接。

B It was the longest-distance repair job in history, and a triumph for the NASA engineers. B 这是历史上最长距离的维修工作，也是 NASA 工程师的胜利。 But it also highlighted the astonishing power of the techniques developed by American communications engineer Claude Shannon, who had died just a year earlier. 然而，它也突出了美国通信工程师 Claude Shannon 发明的技术的惊人力量，不幸的是，这位工程师在一年前已经去世了。 Born in 1916 in Petoskey, Michigan, Shannon showed an early talent for maths and for building gadgets, and made breakthroughs in the foundations of computer technology when still a student. Shannon 生于 1916 年，出生地是密歇根州的皮托斯基，他很早就表现出了对于数学和建造机件的天分，并且在他还只是名学生的时候就取得了计算机科技基础的突破。 While at Bell Laboratories, Shannon developed information theory, but shunned the resulting acclaim. 在贝尔实验室工作的时候，Shannon 发明了信息理论，但却回避了由它带来的种种赞誉。 In the 1940s, he single-handedly created an entire science of communication which has since inveigled its way into a host of applications, from DVDs to satellite communications to bar codes - any area, in short, where data has to be conveyed rapidly yet accurately. 在 20 世纪 40 年代，他独自创造了整个信息科学，这门科学不久就在许多领域得到了应用，从 DVD 到卫星通信再到条形码——简单地说，在任何需要快速并准确传递数据的领域。

C This all seems light years away from the down-to-earth uses Shannon originally had for his work, which began when he was a 22-year-old graduate engineering student at the prestigious Massachusetts Institute of Technology in 1939. C这似乎和 Shannon 最初的想法相去甚远，早在 1939 年，当他还是一名麻省理工学院工程专业 22 岁的研究生的时候，他就已经有了这种想法。 He set out with an apparently simple aim: to pin down the precise meaning of the concept of 'information’. 他最初的目的简单明了：获得“信息”的精准含义。 The most basic form of information, Shannon argued, is whether something is true or false - which can be captured in the binary unit, or 'bit', of the form 1 or 0. Shannon 认为信息的最基本形式就是它是否准确——体现在二进制单位比特的形式 1 或 0 中。 Having identified this fundamental unit, Shannon set about defining otherwise vague ideas about information and how to transmit it from place to place. 在确定了这个最基本的单位后，Shannon 就开始去定义相对模糊的信息想法及如何传送。 In the process he discovered something surprising: it is always possible to guarantee information will get through random interference – ‘noise’, - intact. 在此过程中，他有一个惊人的发现：信息总是有可能精准地穿过随机的干扰，也就是噪音的干扰。

D Noise usually means unwanted sounds which interfere with genuine information. D 噪音通常意味着干扰真正信息的多余声音。 Information theory generalises this idea via theorems that capture the effects of noise with mathematical precision. 信息理论把这一想法归纳成为一个通过数学精密度来获得噪音效果的定理。 In particular, Shannon showed that noise sets a limit on the rate at which information can pass along communication channels while remaining error-free. 特别是 Shannon 表示噪音为信息沿着通信渠道无错误传递速率设定了一个极限。 This rate depends on the relative strengths of the signal and noise travelling down the communication channel, and on its capacity (its ‘bandwidth’). 这一速率取决于沿着通信渠道运送的信号和噪音的相对强度及其容量（即带宽）。 The resulting limit, given in units of bits per second, is the absolute maximum rate of error-free communication given signal strength and noise level. 结果的极限，以每秒比特为单位，就是考虑到信号强度和噪音水平后无错误通信的最大速率。 The trick, Shannon showed, is to find ways of packaging up – ‘coding’, - information to cope with the ravages of noise, while staying within the information-carrying capacity -'bandwidth* - of the communication system being used. 这个技术就是去寻找写代码的方式，去处理噪音的干扰，却要保持在通信系统的信息容量（带宽）范围内。

E Over the years scientists have devised many such coding methods, and they have proved crucial in many technological feats. E 在过去的这些年中，科学家们已经发明了许多此类译码方法，这些方法在许多科技壮举中都起到了至关重要的作用。 The Voyager spacecraft transmitted data using codes which added one extra bit for every single bit of information; the result was an error rate of just one bit in 10,000 - and stunningly clear pictures of the planets. “旅行者”宇宙飞船使用代码传递数据，给每个信息的单一比特多增加一个比特；它的错误率仅为每一万个中一个比特，因此能够为我们带来精美清晰的星球图片。 Other codes have become part of everyday life - such as the Universal Product Code, or bar code, which uses a simple error-detecting system that ensures supermarket check-out lasers can read the price even on, say, a crumpled bag of crisps. 其他代码已经成为我们日常生活中的一部分，例如通用产品代码或条形码，就是使用了简单的错误探测体系来确保超市的镭射扫描器能够读出商品价格，即便是在一个破碎的薯片袋子上。 As recently as 1993, engineers made a major breakthrough by discovering so-called turbo codes - which come very close to Shannon's ultimate limit for the maximum rate that data can be transmitted reliably, and now play a key role in the mobile videophone revolution. 1993 年，工程师们取得了重大突破，发现了涡轮编码，这和 Shannon 为数据有效传递的最大速率计算的最终极值非常接近，并且目前在可视电话革命中起到了重要作用。

F Shannon also laid the foundations of more efficient ways of storing information, by stripping out superfluous (‘ redundant’) bits from data which contributed little real information. F通过从有效信息很少的数据中去除多余的比特的方法，Shannon 也为发现信息储存更有效办法奠定了基础。 As mobile phone text messages like ‘I CN C U’ show, it is often possible to leave out a lot of data without losing much meaning. 正如手机短信“I CN C U”一样，省略掉一些信息却不必流失其意义是可能的。 As with error correction, however, there’s a limit beyond which messages become too ambiguous. 而对于错误纠正而言，信息太过模糊也是有极限的。 Shannon showed how to calculate this limit, opening the way to the design of compression methods that cram maximum information into the minimum space. Shannon 展示了如何去计算这个极值，为把最大值信息储存进最小空间的压缩方法的设计开辟了道路。