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I'm having trouble finding study material or subject.

Theme: Emphasize the processing of signals generated by the sensor at the expense of sensitivity / selectivity.

I can find material related to sensors, but I couldn't find an explanation about 'processing the signals generated by the sensor at the expense of sensitivity / selectivity.'

Could someone explain or indicate a material (book)?

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    \$\begingroup\$ Where does your 'Theme' come from? If a book, link to it. If a tutor, ask them. \$\endgroup\$
    – Neil_UK
    Commented Sep 27, 2020 at 20:31

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I suggest you read the AppNotes from Analog Devices Incorporated. As a kid, I learned much useful analog/signal_processing ideas and maths and building ideas from their freely available publications.

The Analog Dialogue was one which I received monthly. So google that, and start reading, and perhaps BUILDING real circuits.

Use an old loudspeaker, from anold transistor radio, as your microphone. You might reverse_wire the tiny transformer, to stepup the voltage to be a useful level.

You can touch the wires to your earbuds, and hear your fingernail scratching across the loudspeaker's paper cone.

Get starting learning.

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To be concrete about discerning important output signals from sensors ----- theories exist on Matched_Filtering, to optimally extract signals from noise or to optimally discriminate between TWO choices of possible signals.

Just consider the integral, over a complete period, of [ sin(x) * cosine(x)]

The integral is ZERO, when integrated over N * period_duration.

Such signals (sin, cosing) are deemed orthogonal.

Many other "signals" have been defined, to achieve orthogonality.

Some of these "signals" look like noise (randomness) yet to the crafted receiver of such signals, able to implement correlators, a strong and robust datalink exists.

Peter Mallory did much work in this area.

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  • \$\begingroup\$ Actually, my question was a little vague, because it is an example of a generic sensor that most sensors have this behavior. I will explain what I have understood so far with research. When we are talking about sensitivity, small changes (or changes) occur, give an electrical signal for example. this can be through graphs and using mathematical people with the relationship between the output and the input used graph using the derivative. \$\endgroup\$
    – LUFER
    Commented Sep 28, 2020 at 2:49
  • \$\begingroup\$ See, selectivity means to be selective in the type of signal you want to detect (read). example if I am using an ideal sensor (that is, it does not exist in the real world), it can separate two different quantities in its reading. \$\endgroup\$
    – LUFER
    Commented Sep 28, 2020 at 2:50
  • \$\begingroup\$ If we take an example, we have a temperature and gases to measure in the same place, if we have a sensor that is ideal, the sensor can read a single quantity, without interference from the other quantity. The real sensor (truth) can read, but with a small or large margin of reading error because of the other quantity. My question: when we process the signals generated by the sensor at the expense of sensitivity / selectivity.Precisely when we have processing the signals generated by the sensor to the detriment ... this does not achieve this relationship. (that understanding). \$\endgroup\$
    – LUFER
    Commented Sep 28, 2020 at 2:50

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