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Unformatted text preview: ECE 3250 DISCRETETIME LTI SYSTEMS Fall 2008 In this handout I’d like to summarize the material from class on discretetime LTI systems. Such systems serve as effective models for a variety of realworld processes that arise in applications. The models are useful not only in ECE — particularly in the areas of signal processing, communication, and control — but in other fields of science and engineering including MAE, ORIE, economics, and dynamical systems theory. The ideas are more transparent in the context of discretetime models, which is why we start there. As in the handout on discretetime convolution, we think of the integers Z as a math ematical model for “discrete time.” Integer n corresponds to “time n .” Integer 0 corre sponds to “time 0.” If m > n , then “time m is later than time n .” It is not really helpful to think of these “integer times” as being embedded somehow in a familiar “continuous time axis” or as having standard time units such as seconds or milliseconds or whatever. Integer times are just indices with a natural ordering. Having used Z to model discrete time, we can think of a discretetime signal over F as a function with domain Z that takes values in F . As usual, F is either R or C . Alternatively and equivalently, a discretetime signal is a doubly infinite sequence of elements of F . So any such signal x is a sequence ...x ( 2) ,x ( 1) ,x (0) ,x (1) ,x (2) ,x (3) ,... where x ( n ) ∈ F for all n ∈ Z . Think of x ( n ) as the value of the signal x at time n . As before, we denote the set of all discretetime signals by F Z . The realworld processes we’re interested in modeling are processes that take discrete time input signals and generate discretetime output signals. An appealing way to model such a process is as a mapping S : X→ F Z where X is a subset of F Z that represents the set of possible input signals for the system. The idea of the mapping S is that when x ∈ X is the input signal to the system, S ( x ) ∈ F Z is the output signal that arises. It’s worth formalizing all this with a definition. Definition 1: A discretetime inputoutput system consists of • A subset X of F Z representing the system’s set of possible input signals; and • A mapping S : X → F Z that maps each input signal x ∈ X to its corresponding output signal S ( x ) ∈ F Z . One usually assumes that the input space X is “rich enough” to include a lot of signals of interest. We’ll always require that X contain at least all the finiteduration signals. Recall that a signal x ∈ F Z has finite duration if and only if there exist integers N 1 and N 2 so that x ( n ) = 0 when n < N 1 and x ( n ) = 0 when n > N 2 . Recall also the (linear) mappings Shift k o : F Z → F Z defined by Shift k o ( x )( n ) = x ( n k o ) for all x ∈ F Z and n ∈ Z ....
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 LIPSON
 Digital Signal Processing, Signal Processing, Impulse response, fz

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