Slides_on_Random_Processes

Slides_on_Random_Processes - Figure 10.1 (p. 354):...

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Figure 10.1 (p. 354): Conceptual representation of a random process. Sample space , outcomes of a random experiment result in random parameters (variables) which further induce random functions of time
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Figure 10.2 (p. 356): A sample function m ( t,s ) of the random process M ( t ) described in Example 10.4.
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Figure 10.3 (p. 358) : Sample functions of four kinds of stochastic processes. X cc ( t ) is a continuous-time, continuous-value process. X dc ( t ) is discrete-time, continuous-value process obtained by sampling X cc ) every 0.1 seconds. Rounding X cc ( t ) to the nearest integer yields X cd ( t ), a continuous-time, discrete- value process. Lastly, X dd ( t ), a discrete-time, discrete-value process, can be obtained either by sampling X cd ( t ) or by rounding X dc ( t ).
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Figure 10.4 (p. 363): Sample path of a counting process .
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Figure 10.5 (p. 385): A graph of a Poisson process sample path N(t) generated by poissonprocess.m.
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(a) Figure 10.6 (p. 386): Output for simswitch.m ; Simulated 60 minutes of
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This note was uploaded on 09/14/2011 for the course ECE 321 taught by Professor Hongyage during the Spring '11 term at NJIT.

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Slides_on_Random_Processes - Figure 10.1 (p. 354):...

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