1: For the following probabilities set: [0.02, 0.48. 0.1, 0.2, 0.12.0.08]:a- Determine the self-information for each one, and draw its relation with probabilities.b- Calculate the source entropy, and suggest a suitable values to approach the maximumself-information.c- Calculate the source entropy rate for the periods of [1, 2, 3, 2, 3, 1] msec.corresponding to each event.d- Rearrange the probabilities set as a (2 x 3) matrix, then find the joint entropy, sourceentropy, and marginal entropy.e Develop the Haffman and Shannon Fano codes for the above set, and calculate thecode efficiency for the each code.To enrode the message (1100101)

Here's detailed answers: Step 1 : Self-Information and Probability Relationship (Part (a))We're…

Answered: 1: For the following probabilities set:…

Computer Networking: A Top-Down Approach (7th Edition)

7th Edition

ISBN:9780133594140

Author:James Kurose, Keith Ross

Publisher:James Kurose, Keith Ross

Chapter1: Computer Networks And The Internet

Section: Chapter Questions

Problem R1RQ: What is the difference between a host and an end system? List several different types of end...

See similar textbooks

Similar questions

If there are only two possible class labels, what is the maximum impurity using entropy?
ExcelYou must answer the following question (obviously leaving a trace of the calculations made to answer it): If we start at site 0 (therefore p0=1 and all the others pi=0), after how many steps n the probabilities pin are they all close to the asymptotic probabilities πi at most 0.001, ie |pin-πi|≤ 0.001? To answer this question, follow the following steps (see example in image). To be efficient, consider using incrementing, cell calling, etc.(a) On line 2, enter a step counter starting at step 0.(b) On lines 4 and following, indicate the vectors of probabilities pin, so step 0 corresponds to the initial vector, then in the next column, in the column identified by step 1, the vector of probabilities after a step , etc.(c) On lines 15 and following, check if the distance between pin and πi is smaller; in the step 0 column, line 15, indicate: "=ABS(A4-cell containing π0)<=0.001". Then increment (blocking the addresses to be) to check the distances between each pin. Finally,…
Consider a real random variable X with zero mean and variance σ2X . Suppose that we cannot directly observe X, but instead we can observe Yt := X + Wt, t ∈ [0, T ], where T > 0 and {Wt : t ∈ R} is a WSS process with zero mean and correlation function RW , uncorrelated with X.Further suppose that we use the following linear estimator to estimate X based on {Yt : t ∈ [0, T ]}:ˆXT =Z T0h(T − θ)Yθ dθ,i.e., we pass the process {Yt} through a causal LTI filter with impulse response h and sample theoutput at time T . We wish to design h to minimize the mean-squared error of the estimate.a. Use the orthogonality principle to write down a necessary and sufficient condition for theoptimal h. (The condition involves h, T , X, {Yt : t ∈ [0, T ]}, ˆXT , etc.)b. Use part a to derive a condition involving the optimal h that has the following form: for allτ ∈ [0, T ],a =Z T0h(θ)(b + c(τ − θ)) dθ,where a and b are constants and c is some function. (You must find a, b, and c in terms ofthe…
Using R, Use the Monte Carlo simulation to estimate the probability that all six faces appear exactly once in six tosses of fair dice.
There are many sensors on a wind turbine, based on each sensor's reading many alerts are generated as (start, end). For easier monitoring, our customer is asking to raise alerts on the turbine level instead of on each sensor. If any sensor is having an alert, there should be an alert for the entire wind turbine. Suppose the alerts created with two sensors readings are [(0,3),(5,10),(1,4),(10,15)], then the turbine level alert should be [(0,4),(5,15)]. Return the alerts sorted by the start timestamp. If there is no alert from the sensor level, return an empty array []. Code needs to be in Python?
For a HMM, the hidden states are {bull, bear}, the observation variables are {rise, fall}, the initial state probability distribution is [0.5 0.5]¹, the transition probability distribution A is [0.4 0.7; 0.6 0.3], and the observation probability distribution B is [0.8 0.1;0.2 0.9]. If the observation sequence is {fall fall rise}, please show the computation procedure for estimating the most likely state sequence?

Recommended textbooks for you

Computer Networking: A Top-Down Approach (7th Edi…

Computer Engineering

ISBN:

9780133594140

Author:

James Kurose, Keith Ross

Publisher:

PEARSON

Computer Organization and Design MIPS Edition, Fi…

Computer Engineering

ISBN:

9780124077263

Author:

David A. Patterson, John L. Hennessy

Publisher:

Elsevier Science

Network+ Guide to Networks (MindTap Course List)

Computer Engineering

ISBN:

9781337569330

Author:

Jill West, Tamara Dean, Jean Andrews

Publisher:

Cengage Learning

Computer Networking: A Top-Down Approach (7th Edi…

Computer Engineering

ISBN:

9780133594140

Author:

James Kurose, Keith Ross

Publisher:

PEARSON

Computer Organization and Design MIPS Edition, Fi…

Computer Engineering

ISBN:

9780124077263

Author:

David A. Patterson, John L. Hennessy

Publisher:

Elsevier Science

Network+ Guide to Networks (MindTap Course List)

Computer Engineering

ISBN:

9781337569330

Author:

Jill West, Tamara Dean, Jean Andrews

Publisher:

Cengage Learning

Concepts of Database Management

Computer Engineering

ISBN:

9781337093422

Author:

Joy L. Starks, Philip J. Pratt, Mary Z. Last

Publisher:

Cengage Learning

Prelude to Programming

Computer Engineering

ISBN:

9780133750423

Author:

VENIT, Stewart

Publisher:

Pearson Education

Sc Business Data Communications and Networking, T…

Computer Engineering

ISBN:

9781119368830

Author:

FITZGERALD

Publisher:

WILEY

SEE MORE TEXTBOOKS