General Information

• Instructor: Ilia Vovsha (iv2121 at columbia dot edu)
  
• Office Hours: Fri 1:00-2:00pm (TA room, Mudd 122A), Mon 3:00-4:00pm (email to notify) (9/9 - 10/21).
  
• Lecture: Monday 4:10-6:00pm (9/9 - 10/14).
  
• Classroom: 224 Pupin Laboratories
  


• TA: Amit Singh (as4483 at columbia dot edu)
  
• TA Office Hours: Wed 3:00-5:00pm (TA room, Mudd 122A)
  

Introduction

Course Description:
MATLAB is a high-level language and interactive environment that allows one to solve science/engineering problems quickly using built-in functionality. MATLAB is typically used to perform the following tasks:

• Various mathematical operations, e.g. matrix and vector multiplication.
  
• Data manipulation and analysis.
  
• Plotting and visualization.
  
• Complex mathematical functionality, e.g. optimization.
  
• Implementing prototypes of algorithms and models.
  

• MATLAB Documentation from Mathworks
  
• MATLAB File Exchange repository for MATLAB code
  

Requirements

• Access to MATLAB (version 7 or higher). The Cunix machine (cunix.cc.columbia.edu) has MATLAB installed.
  To access the machine type 'ssh your_uni@cunix.cc.columbia.edu' at your terminal/shell/telnet and enter your UNI password.
  Alternatively, there are computer labs on campus where you can use your CS account to access MATLAB, or you can get a student copy at no cost under the Engineering School's site licence here.
  
• Access to courseworks for homework and grades.
  
• No textbook is required, but you are encouraged to consult the references mentioned above.
  
• Basic understanding of linear algebra, and some programming experience is useful, but not required.
  

Lectures

This is a rough (ordered) list of topics that will be covered in this class:

• Basic functionality (workspace, variables, errors, generic commands).
  
• Scripts, simple functions.
  
• Arrays (vectors, matrices).
  
• Control flow, operators.
  
• File input/output.
  
• Cell arrays, character strings.
  
• Advanced functions.
  
• Basic plotting.
  
• Advanced plotting.
  
• Debugging, time and profile commands.
  
• Optimization toolbox.
  

• Lecture 1 (Sept. 9)
  
• Lecture 2 (Sept. 16)
  
• Lecture 3 (Sept. 23)
  
• Lecture 4 (Sept. 30)
  
• Lecture 5 (Oct. 7)
  
• Lecture 6 (Oct. 14)
  

Homework

Instructions:

• Due at the beginning of class, 50% penalty if late. You are allowed to submit ONE homework late (before the next HW is due).
  
• Place your code and any additional files into a folder, and name it 'youruni_hw#' (e.g. iv2121_hw1).
  
• Upload the zipped folder to courseworks before the due date (4:00pm on Monday).
  
• Bring a printout of your code to class.
  

• HW#1 (Due: Sept. 16)   HW#1 Extra (Optional)
  
  
• HW#2 (Due: Sept. 23)   HW#2 Extra (Optional)
  
  
• HW#3 (Due: Sept. 30)   HW#3 Extra (Optional)
  
  
• HW#4 (Due: Oct. 7)   HW#4 Extra (Optional)
  

• HW1:   hw1, ehw1b, ehw1c
  
• HW2:   hw2a, hw2b, hw2c
  
• EHW2:   ehw2b, ehw2c
  
• HW3:   hw3a, hw3b, hw3c
  
• EHW3:   ehw3b, ssort
  
• HW4:   hw4a, hw4b, hw4c
  
• EHW4:   bwt2
  

Final Project

Instructions:

• The project has two parts. Part 1 (write-up) is due October 14th, 4:10pm (last class). Part 2 (implementation, updated write-up) is due by October 21st, 11:59pm.
  
• Late submissions (write-up or implementation) will not be accepted. No exceptions.
  
• Place your code and any additional files into a folder, and name it 'youruni_project' (e.g. iv2121_project).
  
• Upload the zipped folder to courseworks before the due date.
  
• Bring a printout of your write-up to class.
  
• You will receive an email with your grade and comments. If you submit your project early, it will be graded earlier.
  

Grading

Homeworks: (4 x 15% = 60% of grade)

Project: (40% of grade)

Grading Policy: Homeworks are due on Mondays by 4:00pm. Late submissions will be penalized by 50%. Late projects will not be accepted.