One of the biggest challenges in FPGA programming is the process of quantizing mathematical operations to fixed-point for more efficient implementation.
This session teaches the fundamentals of the fixed-point number system and fixed-point arithmetic, along with considerations for targeting popular FPGA devices. These concepts are then reinforced through practical demonstrations, capped by walking through the process of quantizing a signal processing design.
Fixed-point number system
Quantization error in the time and frequency domains
Arithmetic: square root, reciprocal, log2
Trigonometry: cosine, sine, atan2
Signal processing: FIR, FFT
Targeting Xilinx and Intel devices
Using native floating point for full-precision calculations
Example: communications packet detection
MathWorks Fixed Point Team (2021). Fixed-Point Made Easy for FPGA Programming (https://www.mathworks.com/matlabcentral/fileexchange/64495-fixed-point-made-easy-for-fpga-programming), MATLAB Central File Exchange. Retrieved .
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