Information and Policies
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1) Subject Description
Fundamentals of signal processing, focusing on the use of Fourier methods to analyze and process signals such as sounds and images. Topics include Fourier series, Fourier transforms, the discrete Fourier transform, sampling, convolution, deconvolution, filtering, noise reduction, and compression. Applications draw broadly from areas of contemporary interest with emphasis on both analysis and design.The pre-requisite for 6.300 is 6.100A, and this pre-requisite will be strictly enforced. We recommend having prior exposure to complex exponentials and Fourier series, both of which are covered in 18.03.
2) Schedule
Lectures are on Tuesdays and Thursdays from 2:00 to 3:00 PM in 3-270 with Professor Jing Kong. Lectures are intended to provide a concise outline of the technical content as well as a conceptual framework for that content.
Recitations are on Tuesdays and Thursdays from 3:00 to 4:00 PM in 4-370 with Professor Laura Lewis. Recitations are intended to reinforce material from the lecture and to demonstrate how to solve problems using that material.
Common hours are provided for students to work together on problem sets and lab. Staff members will be available to answer questions about problem sets, labs, lectures, recitations, and 6.300-related concepts.
Weekly problem sets and labs are posted on Thursdays at 4:00 PM and due the Wednesday of the following week at 10:00 PM.
3) Assignments
Weekly assignments will consist of problem sets and computational labs.
Problems sets are designed to help you to develop a solid understanding of the subject matter and to become proficient in the skillful use of these concepts. The problems are self-contained, well-specified, and generally have a single correct answer. You should upload your submissions on the appropriate page on the sigproc.mit.edu website.
Computational labs are designed to illustrate the kinds of applications that can be addressed using signal processing techniques. Labs are generally more open-ended than conventional exam-style problems and can usually be solved in multiple ways. They often have multiple valid answers. Please start early on the lab, as they often take more time than students anticipate, especially when it comes to debugging. We strongly encourage you to take advantage of common hours to ask questions and get help from the staff early on.
To make sure that you understand what's being asked in each lab and don't leave it to be done at the last minute, we will have lab check-ins. This short check-in is intended to make sure that you understand the problem (which is somewhat open-ended by design) and that you have formulated an appropriate approach. As part of the check-in, the staff will generally ask questions about early sections of the lab, but we encourage you to feel free to ask about any section of the lab. You must complete a check-in to receive full credit for a lab.
Weekly problem sets and labs are posted on Thursdays at 4:00 PM and due the Wednesday of the following week at 10:00 PM. Lab check-ins must be completed by 9:00 PM on the Monday after the lab has been released.
3.1) Accommodations
If you are experiencing personal or medical difficulties that prevent you from completing some of the work in 6.300, please talk with a dean at Student Support Services. With their support, we will work with you to plan an effective accommodation.
4) Quizzes and Final Examination
Quizzes will be given during regular class times (2:00 to 4:00 PM) on Thursday, October 3, and Thursday, November 7. Requests to take a quiz at a different time will not be approved for conflicts with other activities -- including other classes -- since the quizzes are scheduled during the regular required meeting times for 6.300. Requests for quiz accommodations for personal or medical issues should be discussed with the instructors and Student Support Services at least a week before the quiz date.
The quizzes will cover all materials contained in lectures, recitations, problem sets, and labs up to the date of the quiz, including material covered on previous quizzes.
A three-hour final exam will be given during the final examination period at the end of the semester. The final exam will be comprehensive across all materials in this subject. However, materials since the second quiz will be weighted more heavily. The final exam will be scheduled by MIT's Registrar's Office. Conflicts with the scheduled time must be resolved by scheduling a conflict examination with MIT's Registrar's Office.
5) Grading
All assignments will be graded in a two-step process. First, each question will be awarded points based on technical correctness and reasoning. The total points will then be translated to a 10-point scale and associated letter grade as follows.
The grade boundaries are based on MIT's definitions of letter grades. For example, the boundary between an A and a B will be set to the lowest total point score for which an A will be assigned. The grade boundaries will be used to convert the total point score to a "normalized" 10-point score using piecewise linear interpolation.
5.1) Grading Scheme for Problems and Labs
Problem sets and computational labs will be graded on conceptual correctness as well as clarity of the exposition. Your lowest problem set and lab grades will be dropped. Solutions for problem sets will be posted after they are graded.
Each problem and lab will be graded on a 3-point scale.
0 points: No substantial progress made towards a correct solution. There is little evidence of any original thought or work. Simply writing a few equations or copying facts from the problem will not be awarded points. A solution clearly copied from solutions posted in earlier terms will receive no credit.
1 point: Meaningful progress towards a correct solution, but with significant gaps in understanding. Examples of this are: pursuing a feasible but non-preferred or non-ideal approach and making significant mistakes; or pursuing a correct approach but making one or more major mistakes.
2 points: Good effort but with some deficiencies in understanding; largely correct solution that could benefit from improvement due to important flaws. Examples of this are: pursuing a correct approach to reach the correct solution but explaining that solution in a confusing manner; not showing a clear understanding of the reasoning behind the solution; or submitting a solution that is difficult to grade.
3 points: Solid effort, demonstrating good understanding. Such a solution will be developed through a preferred approach, with all work clearly labeled and explained well; contain at worst trivial algebraic mistakes; and be easy to grade. Note that a 3-point-worthy solution doesn't need to be long. It need only be based on an appropriate direct approach that is clearly indicated.
5.2) Course Grade
Your final grade in 6.300 will be computed as a weighted average of several components, according to one of the following two schemes, whichever is most beneficial to you.
To earn credit for class participation, students must write down and hand in answers to a few questions that the instructors will ask in each lecture and recitation.
Option #1: with class participation
- Problem Sets: 15%
- Computational Labs: 10%
- Lab Check-Ins: 5%
- Quiz #1: 15%
- Quiz #2: 20%
- Final Examination: 25%
- Class Participation: 10%
Option #2: without class participation
- Problem Sets: 15%
- Computational Labs: 10%
- Lab Check-Ins: 5%
- Quiz #1: 15%
- Quiz #2: 20%
- Final Examination: 35%
- Class Participation: 0%
Each component grade is expressed on a 10-point scale, as described above. The weighted average -- a number between 0 and 10 -- will then be converted into a letter grade using the conversion described above.
6) Collaboration Policies
We encourage students to discuss 6.300 concepts and approaches with other students and with the teaching staff to better understand these materials. However, it is important that collaboration occur at a high level. Work that you submit under your name — including explanations, derivations, code, and plots — must be your own. When you submit an assignment under your name, you are certifying that the details are entirely your own work and that you played at least a substantial role in the conception stage.
Students should not take credit for work done by other students. Students should not use solutions of other students — from this semester or from previous semesters — in preparing their own solutions. Students should not share their work with other students, including through public repositories such as GitHub.
Copying work, or knowingly making work available for copying, in contravention of this policy is a serious offense that may incur reduced grades, failing the course, and disciplinary action. Those who violate this policy may be referred to MIT's Committee on Discipline, which has the power to force withdrawal from MIT.
Weekly homework assignments provide an opportunity to develop intuition for new concepts by actively applying the new concepts to solve problems and answer questions. The process of actively struggling with the use of new ideas until you understand them is an effective and rewarding form of education. Reading someone's solution to a problem is not educationally equivalent to generating your own solution. If you skip the process of personally struggling with new concepts by getting the answers from someone else, you will have lost a valuable learning experience.
Good problems are a valuable resource. Don't squander that resource.
These policies are in place with the primary goal of helping you learn more effectively. If you have any questions about why the policies are structured as they are, or if a certain type of collaboration is allowed, just ask! You can do so by sending an e-mail to the instructors at 6.300 at mit dot edu.
For more information, see the academic integrity handbook.
7) Staff Directory
Please contact6.300 at mit dot edu rather than individual staff members. This mailing list will forward the message only to the instructors and teaching assistants, not to the lab assistants. The instructors and teaching assistants will not divulge personal information to those who do not need to know.
