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Equation 9 · Part 4 · How Edge AI Electronics and Sensor Systems Actually Work

Offset from zero

r=S (q−Z),r = S\,(q - Z),
q−Zq-Z

What this part means

Count how many integer steps q lies above or below the zero-point. A positive result gives a positive model value; a negative result gives a negative one.

Its job in the formula

This part belongs to the expression shown above. Read it together with the other parts of the formula.

The passage around this formula

The arithmetic-shrinking lever is quantization. A widely used scheme maps a real-valued weight or activation r onto a low-bit integer q through an affine relationship r=S (q−Z)r = S\,(q - Z). with a scale S and a zero-point Z chosen so that ordinary 8-bit integers can represent the values a trained network actually produces. The 2018 paper that formalized this scheme for mobile and embedded inference showed that training the network with this quantization in the loop, rather than quantizing a finished floating-point model after the fact, preserves accuracy far better, and that integer-only arithmetic — no floating-point unit required anywhere in the inference path — can be implemented…

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Learn the underlying idea

The zero-point is the integer code chosen to mean the real value zero.

Open the illustrated zero-point z guide →

Sources cited in the surrounding passage

These citations provide research context; check each source for the exact claim it supports.

Further reading for this equation