Equation 2 · Edge AI Electronics and Sensor Systems in Practice: Quantization, Power Budgets, and Sensor Front Ends
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the real-valued number. Read the equation part by part below; each part has a contextual explanation and a link to its mathematical background.
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where r is the real-valued number, q is the stored integer, S > 0 is a scale factor, and Z is an integer zero-point chosen so that real zero maps exactly onto a representable integer — a detail that matters because operations like zero-padding and ReLU depend on zero being represented without rounding error. Jacob and colleagues showed that with this scheme, matrix multiplications and convolutions can be carried out using only integer arithmetic, with the more expensive floating-point rescaling deferred to a single fixed-point multiply per output, and reported close to a fourfold reduction in memory footprint against 32-bit floats with accuracy close to the unquantized model on standard…
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where r is the real-valued number, q is the stored integer, S > 0 is a scale factor, and Z is an integer zero-point chosen so that real zero maps exactly onto a representable integer — a detail that matters because operations like zero-padding and ReLU depend on zero being represented without rounding error. Jacob and colleagues showed that with this scheme, matrix multiplications and convolutions can be carried out using only integer arithmetic, with the more expensive floating-point rescaling deferred to a single fixed-point multiply per output, and reported close to a fourfold reduction in memory footprint against 32-bit floats with accuracy close to the unquantized model on standard image classification and detection benchmarks [ 1 ] .
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