Fixed-Point Made Easy for FPGA Programming

Material used in the "Fixed-Point Made Easy for FPGA Programming" webinar.
383 Downloads
Updated 21 Oct 2020

View License

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.

Topics include:

Fixed-point theory
Fixed-point number system
Mathematical range
Quantization error in the time and frequency domains
Common functions
Arithmetic: square root, reciprocal, log2
Trigonometry: cosine, sine, atan2
Signal processing: FIR, FFT
FPGA considerations
Targeting Xilinx and Intel devices
Maintaining precision
Using native floating point for full-precision calculations
Example: communications packet detection
Matched filter
Peak detection
FPGA optimizations

Cite As

MathWorks Fixed Point Team (2024). 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 .

MATLAB Release Compatibility
Created with R2017b
Compatible with R2017b and later releases
Platform Compatibility
Windows macOS Linux

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!
Version Published Release Notes
2.0.0.0

Updated the material used in the webinar.

1.0.0.0

Added copyright notices.