handout_week10_a[1] - Stochastic Signals and Systems Random...

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Stochastic Signals and Systems Random Processes Virginia Tech Fall 2008 Random Processes: Example In certain random experiments, the outcome is a function of time, position, angle, or some other parameter. Statistical multipath channel model: a multipath channel is time-varying in nature. This time variation arises because either the transmitter or receiver is moving and hence the location of reflectors in the transmission path, which gives rise to multipath, will change over time.
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Random Processes: Example In certain random experiments, the outcome is a function of time, position, angle, or some other parameter. Thermal noise is the noise arising from the random motion of charge carriers in a conducting or semiconducting medium. Thermal noise is clearly random and time-varying. Random Processes: Example In certain random experiments, the outcome is a function of time, position, angle, or some other parameter. Brownian motion: motion of particles suspended in a fluid that move under the rapid and random impact of neighboring particles. The position of the particle is random and time-varying.
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Random Processes: Example In certain random experiments, the outcome is a function of time, position, angle, or some other parameter. Binary sequence and its non-return-to-zero level-encoded waveform. Random Process The random time functions in all of the previous examples can be viewed as numerical quantities that evolve randomly in time, position, angle, or some other parameter. Thus, what we really have is a family of random variables indexed by a parameter. For ease of presentation, we consider the indexing parameter to be time.
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