Applied Mathematics in Bioengineering
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About this course
Covers and emphasizes practical applications of linear algebra, statistics, complex analysis, and signal processing in bioengineering. Students develop fluency with matrix decompositions, statistical inference and curve fitting, complex-number representations of signals, linear time-invariant systems, and Fourier analysis, and apply these tools to representative biomedical problems.
What you'll learn
- fluency with matrix decompositions
- understanding of statistical inference
- ability to perform curve fitting
- knowledge of complex-number representations of signals
- applying Fourier analysis to biomedical issues
Skills you'll gain
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