Signal and Image Processing—Graduate Certificate

Signal and Image Processing

Applications range from medical imaging to autonomous vehicle technology.

Learn data manipulation techniques to improve signal or image fidelity. Understand the theory of probability and stochastic processes. Detect and estimate signals. Use computer programming in digital image processing. Autonomous navigation through sensors relies on process control and computer vision.

3 courses in 3 semesters.

Department	Electrical and Computer Engineering
Admissions requirement	Electrical or computer engineering, data science, or related degree.
Contact	Paul L. Bergstrom

Length	3 courses in 2-3 semesters
Effort	3 hours per credit per week
Each course	3 credits
Total credits	9
Course type	Online or on-campus
Modality	Watch class recordings on demand
Cost	Based on credits and course type
Already enrolled?	Speak with your advisor.

Apply

Progress quickly with a compact curriculum.

Work with the program advisor to select courses that fit your interests and pre-requisite skills.

Take a 3 credit required course.

EE 5500 - Probability and Stochastic Processes

Theory of probability, random variables, and stochastic processes, with applications in electrical and computer engineering. Probability measure and probability spaces. Random variables, distributions, expectations. Random vectors and sequences. Stochastic processes, including Gaussian and Poisson processes. Stochastic processes in linear systems. Markov chains and related topics.

Credits: 3.0
Lec-Rec-Lab: (3-0-0)
Semesters Offered: Fall
Restrictions: Must be enrolled in one of the following Major(s): Electrical Engineering, Electrical Engineering, Electrical & Computer Engineer; May not be enrolled in one of the following Class(es): Freshman, Sophomore, Junior

Take 6 credits of elective courses.

EE 5300 - Mathematical and Computational Methods in Engineering

Overview of problem-solving tools and techniques in engineering, considered from both the analytical and computational point of view. Systems of linear equations, eigenvalue and eigenvector computations, boundary value and initial value problems, Fourier analysis, large-scale systems, optimization. Mathematical modeling and computar programming.

Credits: 3.0
Lec-Rec-Lab: (3-0-0)
Semesters Offered: Fall, Spring
Restrictions: Must be enrolled in one of the following Major(s): Electrical & Computer Engineer, Electrical Engineering, Computer Engineering; May not be enrolled in one of the following Class(es): Freshman, Sophomore, Junior

EE 5521 - Detection & Estimation Theory

Detecting and estimating signals in the presence of noise. Optimal receiver design. Applications in communications, signal processing, and radar.

Credits: 3.0
Lec-Rec-Lab: (3-0-0)
Semesters Offered: Fall, Spring
Restrictions: Must be enrolled in one of the following Level(s): Graduate; Must be enrolled in one of the following Major(s): Electrical & Computer Engineer, Electrical Engineering, Computer Engineering
Pre-Requisite(s): EE 5500

EE 5522 - Digital Image Processing

Fundamentals of image processing are covered including image representation, geometric transformations, binary image processing, compression, space and frequency domain processing. Computer programming in MATLAB and Python required.

Credits: 3.0
Lec-Rec-Lab: (3-0-0)
Semesters Offered: Fall, Spring
Restrictions: Must be enrolled in one of the following Level(s): Graduate; Must be enrolled in one of the following Major(s): Electrical & Computer Engineer, Electrical Engineering, Computer Engineering

EE 5532 - Sensing and Processing for Robotics

Sensing modes, signal and image processing for industrial robotic automation processes. Emphasis placed on widely used sensors, including cameras and 3-D sensors for process control and computer vision for autonomous navigation.

Credits: 3.0
Lec-Rec-Lab: (3-0-0)
Semesters Offered: Spring
Restrictions: Must be enrolled in one of the following Major(s): Electrical & Computer Engineer, Electrical Engineering, Computer Engineering; May not be enrolled in one of the following Class(es): Freshman, Sophomore, Junior
Pre-Requisite(s): EE 5522

The minimum completion time is one semester.

Here are typical schedules.

Sample Plan 1

Fall
EE 5300 EE 5500 EE 5522

Sample Plan 2

Fall	Spring
EE 5500 EE 5522	EE 5532

Enroll for Online

Check the schedule of online classes to see which of your required or elective courses are available for upcoming semesters.
Consult the academic calendar for fall and spring instruction start dates.
Estimate costs based on tuition and online fees.
Apply to the Graduate School for fall or spring semester.

Enroll for On-campus

Review MTU Flex announcements related to the Graduate School.
Check the schedule of classes to see which of your required or elective courses are available for upcoming semesters.
Consult the academic calendar for fall and spring instruction start dates.
Estimate costs based on tuition.
Apply to the Graduate School for fall or spring semester.

Interested in taking a single, online course? Enroll as a non-degree seeking student.

Upon completion of the Certificate the student should be able to:

Demonstrate proper utilization of signal and image processing techniques.

Students receiving this certificate will have demonstrated the ability to solve open-ended problems in statistical signal and/or image processing from fundamental principles, and be able to apply their solution to real world problems.

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