Fixed-Point Made Easy for FPGA Programming - MATLAB & Simulink
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    Fixed-Point Made Easy for FPGA Programming

    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

    Published: 11 May 2020