Describe briefly the forms of noise to which a transistor is prone-Sol.docx

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Describe briefly the forms of noise to which a transistor is prone. Solution The major sources of noise in transistors are: BJTs ----- shot noise, flicker noise, burst noise MOSFETs ----- flicker noise, thermal noise in strong inversion, shot noise in weak inversion, burst noise . Thermal noise is generated by the random thermal motion of charge carriers . Flicker noise , also known as 1/ f noise, is a signal or process with a frequency spectrum that falls off steadily into the higher frequencies, with a pink spectrum. It occurs in almost all electronic devices, and results from a variety of effects, though always related to a direct current. . Shot noise occurs due to various reasons - random emission of carriers across a barrier, random tunneling of carriers, generation/recombination processes in bulk and depletion region, thermal fluctuations triggering a relaxation current through diffusion. . Burst noise (or random telegraph signal) is seen as random .

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The signal is the meaningful information that you’re actually trying to detect. The noise is the random, unwanted variation or fluctuation that interferes with the signal. To get a sense of this, imagine trying to tune into a radio station. Ok, you don’t use radio anymore, so imagine your dad can’t call you to get help setting up his Spotify, so is trying to tune into a radio station. He turns the dial but it’s just picking up white noise and, after a few frustrating minutes, he manages to pick up a signal and tune into a station. The same is true in statistics — there is something you’re trying to actually measure (say, how many Americans want to leave for Canada), but the data could be noisy (by including everyone who just makes a trip over the border to buy affordable medication). Noisy data are data from which it is hard to determine the true effect.Examples of signal vs noise If I speak German, for most people, there will be no signal, just noise, although Claus can detect the actual signal. How accurate are the polls in predicting the election? If the data are noisy (for example, because it’s a small sample size, has low external validity, or small effect size), the poll numbers won’t correlate well with a change in the chance of a different President. Does money make you happier? The signal (correlation between income and happiness) would be noisy because of confounders — you’d expect people who earn more to be happier because they are in positions of higher social status, they have better working conditions, being happier could cause people to be rich etc. Turns out there is some signal amongst the noise though.

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