handout_week11_a

handout_week11_a - Stochastic Signals and Systems Random...

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Stochastic Signals and Systems Random Processes Virginia Tech Fall 2008 Autoregressive Random Processes A first order autoregressive (AR) process Y n has the form Y n = α Y n - 1 + X n where X n are iid random variables. α is a measure of statistical dependence of Y n on previous Y n - 1 . “First order” means that Y n depends on Y n - 1 . In general, kth-order AR process Y n depends on previous k variables { Y n - 1 . . . Y n - k } as Y n = α 1 Y n - 1 + . . . + α k Y n - k + X n
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Autoregressive Random Processes Example: “For digital speech communications at very low bit rates, speech is sometimes converted into a model consisting of a simple linear filter (called an autoregressive filter) and an input process. The idea is that the parameters describing the model can be communicated with fewer bits than can the original signal, but the receiver can synthesize the human voice at the other end using the model so that it sounds very much like the original signal. A system of this type is called a
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This note was uploaded on 05/05/2010 for the course ECECS 5605 taught by Professor Dasilver during the Fall '08 term at Virginia Tech.

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handout_week11_a - Stochastic Signals and Systems Random...

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