• Implement the FFT on a DSP processor and display result.
  • Study adaptive filters and implement one.
  • Program the DSP processor to implement a DTMF coder and/or decoder.
  • Study wavelets, and demonstrate their use
  • Explore computer vision techniques based on DSP principles
  • How can DSP algorithms be implemented on Gate Arrays. http//www.mathworks.com/digest_xilinx_training
  • Implement a filter in Verilog
  • Describe, in some depth, architectural features of our DSP processor designed particularly for DSP work, and write some code to demonstrate.
  • Write a very efficient (assembly language) FIR filter for a DSP
  • Code up a prime factor FFT (Matlab or C)
  • Report on the advantages of Delta-Sigma (oversampling) D/A and A/D convertors
  • Create a filter design package that generates source code for the DSP (ie, given a specified frequency response, the package generates a program that will implement that filter)
  • Design a system that performs either µ-law or A-law companding, then test it.
  • Construct a system that produces band-limited white noise. This would be very useful for the department for a wide variety of purposes.
  • Perform data compression using Linear Predictive Coding, Huffman Coding, or some other compression algorithm.
  • Show how quantization affects pole location in various realizations of IIR filters.
  • Explore how quantization affect the performance of FIR filters.
  • Description (and implementation?) of Parks-McClellan algorithm for filter design.
  • Research/Implement Linear Predictive Coding
  • Research Speech Analysis (tools and techniques used).
  • Implement an IIR filter on a fixed point DSP processor and investigate scaling of coefficients.
  • How can approximately linear phase IIR filters be designed.
  • Detect the location of a sound by employing multiple microphones (or use multiple speakers to “steer” sound).

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