MSc in Electrical and Computer Engineering - Signal and Image Processing and Machine Learning in Ann Arbor United States | University of Michigan Ann Arbor

Signal processing is a vast engineering field focused on retrieving, modifying, and preserving data contained within intricate signals and visual data. Techniques in this domain encompass: information compression, analog-to-digital transformation, signal and image recovery/enhancement, dynamic filtering, decentralized sensing and computation, and machine-driven pattern recognition. From the initial development of the fast Fourier transform (FFT) to modern widespread compression standards like MP3/JPEG/MPEG, signal processing has powered numerous innovations that enhance daily life. Applications span: medical imaging systems (cardiac scan algorithms and cross-modality image alignment), digital sound technology (MP3 players and adaptive noise-reducing headphones), satellite navigation (GPS and location-enabled mobile devices), smart vehicle sensors (airbag triggers and crash prevention systems), multimedia gadgets (PDAs and smartphones), and digital forensics (online surveillance and voice recognition systems). The University of Michigan approaches signal processing as a scientific discipline where novel techniques are mathematically formulated and applied through core principles that enable performance evaluation and reliability assessment. UM's research in this field is pioneering innovative models, methodologies, and technologies that will further influence medical diagnostics and treatments, radar systems, sensor networks, visual data compression, telecommunications, and other sectors.