• 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).