产生误差的平均速度是每秒4米。
他们已经制造出能够在受控的工厂环境中识别出几分之一毫米误差的机器人。
They have built robots that can recognize the error of a machine panel by a fraction of a millimeter in a controlled factory environment.
误差的一个来源是折射,即光束通过不同温度和压力的空气层时发生的弯曲现象。
One source of error is refraction, the bending of light beams as they pass through air layers of different temperature and pressure.
Successive approximation, Newton-Raphson was one nice example, but there's a whole class of things that get closer and closer, reducing your errors as you go along.
逐渐逼近,牛顿迭代是一个很好的例子,随着你不断的时行下去,你会不断的离结果越来越近,逐渐地减少误差。
So how do we go about measuring these things and what sorts of errors are in them, and how accurate are they?
那么我们该如何去评估,其中产生怎样的误差,它们又准确到什么程度
What do you think the error is going to be by failing to recognize that at the end of 6 times 10 to the 23rd I have over-counted some energy?
你们可能会发现,这将会有误差,在6乘以10的23次方的末端,我多余地引入了一些能量?
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