Signal Processing

(The Magic and Power of Recursive Equations)

 

ME 510/610 Course Outline:             Course_Outline

 

Lecture Video Access:                        Lecture Video Access

 

Bus Seat Data:                                    Seat_Data.zip

HW6_signal.txt:                                 HW6_signal.txt

 

Assignment_Week_7:                        Assignment_Week_7

Assignment_Week_7_files.zip:         Assignment_Week_7_files.zip

Assignment_Week_9_files.zip:         Assignment_Week_9_files.zip

 

ME 510/610  Assignments

 

  1. Assignments

 

 

ME 453/553 Handouts

 

  1. Handout 01 - Examples of Simple Recursive Equations Representing Very Complicated Behavior
  2. Handout 02 - Introduction
  3. Handout 03 - Convolution
  4. Handout 04 - Discrete Fourier Transform
  5. Handout 05 - DFT Development
  6. Handout 06 - Example of what constitutes a complete cycle for a DFT
  7. Handout 07 - Example Illustrating and Comparing the Various ways the DFT can be Calculated
  8. Handout 08 - Calculation of the Frequency Response using the DFT and the Impulse Response
  9. Handout 09 - Zero Padding
  10. Handout 10 - Harmonics
  11. Handout 11 - Paper - Vibration Transmissibility Characteristics of a Newly Designed Bus Drivers Seat
  12. Handout 12 - Report - Determination of the Dynamic Characteristics of a Newly Designed Drivers Seat
  13. Handout 13 - Periodogram_and_Welchs_Method
  14. Handout 14 - Spectrum and spectral density estimation by the Discrete Fourier transform (DFT) including a comprehensive list of window functions and some new flat-top windows
  15. Handout 15 - How to use the FFT and Matlab’s pwelch function for signal and noise simulations and measurements
  16. Handout 16 - The Use of Fast Fourier Transform for the Estimation of Power Spectra -  A Method Based on Time Averaging Over Short Modified Periodograms
  17. Handout 17 - Introduction to Digital Filters
  18. Handout 18 - Moving Average Filters
  19. Handout 19 - Windowed Sinc Filters
  20. Handout 20 - Windowed-Sinc Filter Implimentation
  21. Handout 21 - Custom Filters
  22. Handout 22 - Recursive Filters
  23. Handout 23 - Chebyshev filters
  24. Handout 24 - Filter_Comparison
  25. Handout 25 - Matlab-Filter Functions
  26. Handout 26 - FIR Digital Filters
  27. Handout 29 - Kalman Filter Introduction
  28. Handout 30 - An introduction to scalar Kalman filters
  29. Handout 31 - Applications of the Kalman Filter
  30. Handout 32 - Kalman Filter Example
  31. Handout 33 - Estimating Simple Models from Real Laboratory Process Data