News for
3-24-2017

After class on Wednesday I realized that the Chapter 3 Jupyter notebook has very good dicussions of how to work the last two problems of the midterm using Python. I would also say that Sympy (Symbolic Python) has some very nice features which I may get around to adding to a midterm hints notebook. In the mean time though, look at the Chapter 3 notebook, just reposted with the notebook upgraded to Jupyter.

Take-home midterm exam posted. The Web server is slow to respond and is being investigated.

Set #5 and hints for Set #5 posted.

Solutions for Set 2 and 3 posted.

Next Week 3/15 - Moving from today to next Wednesday focus on just a few things: (1) Wrap up Set 1p, (2) All take a look at Problem 4, Set 4, to better understand the general Gaussian problem, (3) As time permits move onto Set #5, especially problems 1 and 2. The midterm will be up and I will take some time to go over these problems.

As the semester passes by continue to think about data science and machine learning, as these are very contemporary topics across many disciplines.

Fall 2017

A request has been made to offer the phase-locked loops course, ECE 5675 or perhaps wireless networking. This course, like 5615, can be a self-study course/independent study type course using the available lecture videos and course notes. Ask me for info. Other such courses are under consideration as well.

Office Hours

M 2:15 to 3:00 PM and after 4:20 PM as needed,
W 2:15 to 3:00 PM and after 4:20 PM as needed,
or by appointment.
Office EN 292,
Phone 255-3500, mwickert@uccs.edu.

Learning Python

Python Basics (beta) a tutorial written in IPython Notebook

Link to Anaconda. This is the scientific Python I recommend.

An IDE I recommend is Pycharm Community Edition.

NumPy2MATLAB and IPython reference card.

The future of Jupyter Notebook is JupyterLab.

Obtaining Mathematica

EAS RATS and LATS Servers

Mathematica is available across the campus due to the CU system wide site license. This system-site license also means that students may install their own copy on home computers as well. Some links of interest regarding the CU site license for Mathematica are: download and installation and support information.

Catalog Course Description

Concepts of signal processing using random signals; random vectors, random processes, signal modeling, Levinson recursion, Wiener filtering, spectrum estimation, and detection theory.
Prerequisite: ECE 4650/5650 or equivalent and ECE 3610 or equivalent.
Offered: Alternate Spring Semesters

Course Materials - Course Notes, m-Code

Course Syllabus as of 04:42 PM on Tuesday, January 03, 2017.

PDF file of Intro Lecture as of 07:01 AM on Wednesday, January 18, 2017.

Lecture Notes

  • PDF file of Chapter 2 as of 07:48 PM on Tuesday, January 17, 2017. Jupyter notebook as of 10:13 AM on Friday, March 24, 2017. Jupyter notebook pdf as of 03:24 PM on Wednesday, January 28, 2015.
  • PDF file of Chapter 3 as of 06:44 AM on Wednesday, January 18, 2017. Jupyter notebook as of 10:14 AM on Friday, March 24, 2017. Jupyter notebook pdf as of 08:56 PM on Wednesday, April 08, 2015.
  • PDF file of Chapter 4 as of 06:45 AM on Wednesday, January 18, 2017.
  • PDF file of Chapter 5 as of 02:47 PM on Tuesday, January 17, 2017.
  • PDF file of Chapter 6 as of 02:28 PM on Tuesday, January 17, 2017.
  • PDF file of Chapter 7 as of 02:48 PM on Tuesday, January 17, 2017.
  • PDF file of Chapter 8 as of 02:46 PM on Tuesday, January 17, 2017.
  • PDF file of Chapter 9 as of 02:29 PM on Tuesday, January 17, 2017.
  • PDF file of Chapter 10 as of 02:49 PM on Tuesday, January 17, 2017.

Python Code Modules

  • Code base as of 07:03 PM on Sunday, November 06, 2016.
Lecture Videos - Download

Spring 2017 Lectures as MP4 Movies

All lectures, when available, are double length, meaning the class met for two lecture periods once per week. The .mp4 file size is typically 350 MB per 150 min lecture.

Problem Sets with Solutions
  • Set 1 as of 07:33 PM on Tuesday, January 17, 2017. Hints as of 08:45 AM on Saturday, January 21, 2017 Solved as of 06:37 AM on Wednesday, February 15, 2017.
  • Set 1p as of 07:37 PM on Tuesday, January 17, 2017. Hints as of 06:35 AM on Wednesday, February 15, 2017
  • Set 2 as of 07:34 PM on Tuesday, January 17, 2017 Hints as of 12:37 PM on Tuesday, February 07, 2017 Solved as of 11:20 AM on Wednesday, March 08, 2017..
  • Set 3 as of 07:36 PM on Tuesday, January 17, 2017. Hints as of 06:36 AM on Wednesday, February 15, 2017. Solved as of 11:15 AM on Wednesday, March 08, 2017.
  • Set 4 as of 07:40 AM on Wednesday, March 01, 2017. Hints as of 07:45 AM on Wednesday, March 01, 2017
  • Set 5 as of 11:10 AM on Wednesday, March 08, 2017. Hints as of 11:51 AM on Wednesday, March 08, 2017
  • Midterm as of 08:53 AM on Wednesday, March 01, 2017.
Python/Jupyter Projects
  • TBD
Takehome Exams
  • Midterm 2015 as of [an error occurred while processing this directive].
  • Final 2015 as of 06:45 PM on Saturday, April 11, 2015.