Johns Hopkins University 3 credits Electrical and Computer Engineering
Information theory concerns the fundamental limits for data compressibility and the rate at which data may be reliably communicated over a noisy channel. Course topics include measures of information, entropy, mutual information, Markov chains, source coding theorem, data compression, noisy channel coding theorem, error-correcting codes, and bounds on the performance of communication systems. Classroom discussion and homework assignments will emphasize fundamental concepts, and advanced topics and practical applications (e.g., industry standards, gambling/finance, machine learning) will be explored in group and individual research projects. Prerequisite(s): EN.525.614 Probability and Stochastic Processes for Engineers or equivalent.;***Computer Science students only: Must complete core courses first (EN.605.601 AND EN.605.611 AND EN.605.621).;***Cybersecurity students only: Must complete core courses first (EN.605.621 AND EN.695.601 AND EN.695.641).
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