Please help, the previous expert answer I got was incorrect. Please provide a unique solution. Thank you so much for your help. Problem 3. Means and Correlations.a. Here we consider mobile phone usage by Alice. Let us model her phoneusage as follows: First we pick a random number S₁ uniformly dis-tributed between 0 and 1 minute. This represents the start time ofthe call. Alice uses the phone for exactly 1 minute each time so endsthe first call at time E₁ = S₁ + 1. She then makes another call start-ing at a time S₂ where S₂ is uniformly distributed between E₁ andE₁ + 1 and ends the call at time E2 S2 + 1. This process contin-ues until Alice has made and completed N calls with Alice starting acall at a time Sk where Sk is uniformly distributed between Ek-1 andEk-1 + 1 and ends the call at time Ek = Sk + 1, k = 1, 2,..., N, withEo 0. Let us define X(u, t) 0 when Alice is not using the phoneand X(u, t) = 1 when Alice is using the phone, where u is a realizationfrom an N-dimensional sample space, i.e., u = {U₁, U₂,..., UN}, witheach ui, i = 1,2, ..., N, uniformly distributed in (Ei-1, Ei-1+1). ThenX(u, t) is a random process.==Below is an example of a sample function for N = 3.10 S1 E1 S2 E2 S3 E3 i. Compute E[X(u, t)] for 0 ≤ t ≤ 2. Using your expression evaluateE[X(u, 1)] and E[X(u, 2)].ii. Now as t becomes large, E[X(u, t)] → µ (a constant). Find u(you may assume that N → ∞ so that t can be arbitrarily large).Note that you can work this part independent of part (i).

For modeling Alice's phone usage, a random is picked that has a uniform distribution within and…

i. Compute E[X(u, t)] for 0 ≤ t ≤ 2. Using your expression evaluate E[X(u, 1)] and E[X(u, 2)]. ii. Now as t becomes large, E[X(u, t)] → µ (a constant). Find u (you may assume that N → ∞ so that t can be arbitrarily large). Note that you can work this part independent of part (i).

i. Compute E[X(u, t)] for 0 ≤ t ≤ 2. Using your expression evaluate E[X(u, 1)] and E[X(u, 2)]. ii. Now as t becomes large, E[X(u, t)] → µ (a constant). Find u (you may assume that N → ∞ so that t can be arbitrarily large). Note that you can work this part independent of part (i).

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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Please help, the previous expert answer I got was incorrect. Please provide a unique solution. Thank you so much for your help.

Problem 3. Means and Correlations.
a. Here we consider mobile phone usage by Alice. Let us model her phone
usage as follows: First we pick a random number S₁ uniformly dis-
tributed between 0 and 1 minute. This represents the start time of
the call. Alice uses the phone for exactly 1 minute each time so ends
the first call at time E₁ = S₁ + 1. She then makes another call start-
ing at a time S₂ where S₂ is uniformly distributed between E₁ and
E₁ + 1 and ends the call at time E2 S2 + 1. This process contin-
ues until Alice has made and completed N calls with Alice starting a
call at a time Sk where Sk is uniformly distributed between Ek-1 and
Ek-1 + 1 and ends the call at time Ek = Sk + 1, k = 1, 2,..., N, with
Eo 0. Let us define X(u, t) 0 when Alice is not using the phone
and X(u, t) = 1 when Alice is using the phone, where u is a realization
from an N-dimensional sample space, i.e., u = {U₁, U₂,..., UN}, with
each ui, i = 1,2, ..., N, uniformly distributed in (Ei-1, Ei-1+1). Then
X(u, t) is a random process.
=
=
Below is an example of a sample function for N = 3.
1
0 S1 E1 S2 E2 S3 E3

i. Compute E[X(u, t)] for 0 ≤ t ≤ 2. Using your expression evaluate
E[X(u, 1)] and E[X(u, 2)].
ii. Now as t becomes large, E[X(u, t)] → µ (a constant). Find u
(you may assume that N → ∞ so that t can be arbitrarily large).
Note that you can work this part independent of part (i).

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