Innovative Research
Team Members
A Collaborative & Highly Motivated Group
Izzi Nolan
A sophomore studying electrical engineering at the University of Michigan with a passion for Signal Processing. Izzi is mainly interested in audio process applications to automotive technology. These attractions encouraged Izzi to enroll in EECS 351.
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​Izzi carried out initial data extraction and filter applications with different frequency and roll out responses. This process included working with the Filter Designer App provided in MATLAB and researching other successful methods for underwater signal processing. In addition, also formatted the website and wrote documentation.
Jason Ribbentrop
A senior studying Computer Engineering at the University of Michigan. Although his concentration in CE is more towards chip design, most chips commonly interact with digital signals. This prompted Jason to take EECS 351.
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Jason worked on the data processing and preparation before it was used for classification training. This included some tools such as resampling and data augmentation. Also worked with the MATLAB Classification Learner App which helped create our trained models. Once the trained models were ready, determined the test accuracies of those models.
Sebastian Sulborski
A senior studying Electrical Engineering at the University of Michigan. His focus is tailored more toward powertrain systems for electric vehicles. Hence, Sebastian decided to take EECS 351 to obtain fundamental concepts on signals and data communication.
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Sebastian researched different types of filters to use that would work best for our data. Applied basic low pass and high pass filters to our data and designed a Targeted Moving Average filter. Then researched more specific filters like the Kalman and Wiener filter.