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In today’s world the amount of sampled data is increasing as more efficient and faster analog to digital converters (ADC) are becoming available. There is a need to implement Digital Signal Processing (DSP) solutions in hardware to accommodate the current processing rates of this data. Field Programmable Gate Array (FPGA) platforms offer enormous resources suitable for such implementation. In the mean time, they allow the hardware solutions to be prototyped, implemented, and tested with ease. However, in academia, there still exists a gap between developing systems using the traditional skills gained in DSP courses and implementing them on FPGAs. At Boise State University, the author had developed and taught a new graduate level course titled “Hardware Implementation of Digital Signal Processing” as part of the Masters and Ph.D. program in Electrical and Computer Engineering to close this gap. This paper discusses the topics chosen, course outline, practical exercises and the tools used in teaching this course. It also presents an assessment of the effectiveness of the developed course organization, practical exercises, and the teaching methodology. It also describes how traditional DSP concepts are blended into the implantation on FPGAs.

Work in Progress - Teaching Hardware Implementation of Digital Signal Processing Algorithms on FPGAs