- 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).
Source: Watteam Home – Watteam
Design a wearable fitness monitor that measure pulse rate and oxygen saturation level of blood.
Design some kind of sensing network using the TI sensor tag – available in bluetooth and wifi.
I2S is a popular digital interface for audio, but is not supported on many microcontrollers. Design an interface from I2S to SPI (or I2C) that uses the smallest possible processor to do the work. Build a PCB/develop software….
The Makey Makey is essential a generalized input device – a touch keyboard that can be used in many different ways.
The Arduino is a cheap electronics board that allows you to make your own electronics without a ton of coding experience. We love the Arduino, but like any electronics project, coming up with ideas for what to build is tough. Whether you’re just looking for inspiration or just need a place to start, let’s take a look at ten of the coolest Arduino projects.
Source: Top 10 Kickass Arduino Projects
Note: even some of the ones marked Easy may not be so easy – also some require expensive extras.
Source: Arduino Playground – Ideas
Use this method to make an animation (web-based?) that calculate pi. The Pi Machine – NYTimes.com.
Some MSP430’s have a very low power mode that lets you implement a finite state machine to do some simple processing without waking the processor up. See “SCAN IF” in MSP430FG4618 family data sheet (http://www.ti.com/lit/ug/slau056l/slau056l.pdf). We have some of these processors, so you could try it out.
- Fuzzy logic for control.
- Neural nets for control.
- Implement controller with programmable logic
- Optimal control.
- DSP processors, and their use in control systems.
- Control of non-linear systems.
- Adaptive control.
- Efficient computer implementation of discrete controllers
- Examine a specific system and design and implement a controller.
- Derive Mason’s gain formula.
- Derive the Routh-Hurwitz criterion.
- Derive relationships for observability and/or controllability.
- Derive Ackerman’s formula
- Control a “Satellite” system
- Control a gantry crane or inverted pendulum.
- Resurrect and control a ball-and-beam experiment
Explore some of the more advanced features of MatLab or SolidWork in some creative way.
Build a virtual model of a 3-D world and use MatLab to “fly” through it.
Try to control a SolidWorks model from MATLAB. I’ve never done this so some initial research will be necessary to make sure it is feasible.
Try to model fluid flow in SolidWorks. I’ve never done this, so some initial research will be necessary to see if it is feasible.
Make some other robots with servos…
Attach a joystick (or use a wii nunchuck) to control the x,y position of your robot.
A description of the PID algorithme w/o a lot of math.
A ram pump uses gravity and inertia to pump water from a lower reservoir to a higher one. Build a demonstration model.
Use SolidWorks (or Matlab) to generate a 3D Koch’s snowflake (link)
Animate the formation of a Koch’s snowflake, in MATLAB with smaller triangles gradually emerging out of the larger ones.
The robot your built is more accurate at some locations than others. Do a sensitivity analysis (this involves some derivatives) to quantify this sensitivity function.