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Stochastic Processes, Detection, and Estimation
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This course examines the fundamentals of detection and estimation for signal processing, communications, and control. Topics covered include: vector spaces of random variables; Bayesian and Neyman-Pearson hypothesis testing; Bayesian and nonrandom parameter estimation; minimum-variance unbiased estimators and the Cramer-Rao bounds; representations for stochastic processes, shaping and whitening filters, and Karhunen-Loeve expansions; and detection and estimation from waveform observations. Advanced topics include: linear prediction and spectral estimation, and Wiener and Kalman filters.

Subject:
Applied Science
Career and Technical Education
Electronic Technology
Engineering
Mathematics
Statistics and Probability
Material Type:
Full Course
Provider:
MIT
Provider Set:
MIT OpenCourseWare
Author:
Willsky, Alan
Wornell, Gregory
Date Added:
02/01/2004
Topics in Linguistic Theory: Laboratory Phonology
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CC BY-NC-SA
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The goal of this course is to prepare you to engage in experimental investigations of questions related to linguistic theory, focusing on phonetics and phonology.

Subject:
Applied Science
Arts and Humanities
Career and Technical Education
Electronic Technology
Engineering
Linguistics
Social Science
Material Type:
Full Course
Provider:
MIT
Provider Set:
MIT OpenCourseWare
Author:
Flemming, Edward
Date Added:
02/01/2007