Signal processing is a discipline concerned with transforming and manipulating signals for information extraction, signal estimation, and efficient r...
Signal processing is a discipline concerned with transforming and manipulating signals for information extraction, signal estimation, and efficient representation of signals. Digital signal processing has a wide range of applications and has become a key component of almost all modern electronic devices. Digital signal processing has applications in speech and audio signal processing, image processing, digital communications, control and robotics, medical equipment, and many other industrial and consumer electronics. Applications of digital signal processing in speech and audio processing include speech compression, speaker recognition and verification, noise reduction, music equalization and processing, and more.
Digital signal processing technology enables a wide range of image processing applications, such as face recognition, image enhancement and image compression. The rapid growth and expansion of wireless communication devices, systems and networks has recently been made possible due to complex digital signal processing algorithms. Likewise, radar systems and robotics owe their existence and development to digital signal processing. Additionally, biomedical digital signal processing has recently driven the development of many life-saving wearable medical devices.
The program structure
The curriculum of signal processing program reflects depth and breadth of faculty research expertise and provides graduate students with a solid foundation in signal processing and digital image processing. Relevant courses include: Probability and Random Process, Signal Processing, Digital Image Processing Applications, Predictive Learning from Data, Electronic Circuits, Digital IC Design and many others.
Students will learn:
Industry standard simulation tools such as Matlab, Spiece, and LabView.
Basic probability and random processes and their applications to engineering.
Digital signal processing techniques for analysis of systems and designing of digital filters.
Statistical signal processing which deals with random signals, their modeling, characterization, and transformation to extract useful information about the underlying mechanism that generates them.
Advanced image processing techniques, image filtering design, and its applications to images acquired from various imaging techniques.
Concepts of predictive learning algorithms for supervised and unsupervised learning tasks.
Career pathway
Experiences from classes in this key area of signal processing prepare students for a wide range of career opportunities in signal processing. Digital signal processing engineers work in a variety of industries including telecommunications, aerospace, semiconductor, consumer electronics, and more. Students should be prepared to consider the following competitive positions, such as:
Signal and Image Processing Engineer
Camera Algorithm Engineer
Principle Active Noise Cancelation Engineer
Camera Systems Engineer
Financial Signal Processing Engineer
Speed and Audio Processing Engineer
Machine Learning and Artificial Intelligence Engineer
Entry requirements for signal processing applicants
So as to be able to apply for a Master Signal processing degree, students have to obtain a Bachelor degree in electrical/electronic engineering, or a related subject with a substantial electrical/electronic engineering component. The appropriate English language qualification is also required.