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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

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