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01:32
Note: This problem uses the same setup as the Jacobi and Gauss-Seidel questions, but you are asked to calculate different values. It will probably be useful to copy code from those problems, but make sure that you alter your final answers accordingly.
Any matrix can be decomposed into diagonal, upper, and lower parts:A = D + U + L
You can easily find these matrices in Matlab with the commands diag, triu, and tril. These matrices are useful for devising different matrix splitting methods. For instance, in the Jacobi method we let P = D and T = U + L, and in the Gauss-Seidel method we set P = D and T = U. Another common matrix splitting method is called successive over-relaxation (SOR). It is exactly the same as the splitting methods we have already seen, except we set P = (L + D) and T = D + U, where w is a constant between 0 and 2. (Notice that if w = 1, then this is exactly the same as Gauss-Seidel). We will use this method to solve the system A*x = b that was described in the Jac…
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computer problem 1 can be found here:https://www.bartleby.com/questions-and-answers/blems-1.-design-a-monte-carlo-simulation-to-estimate-the-probability-of-a-random-walk-reaching-the-t/0892d4b2-194d-4f0d-869a-ae3b8e101eb9
USE EITHER PYTHON OR MAPLE FOR THESE (or matlab if you know it)
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Can you help me with finding the volume of this figure?
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matlab
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Problem 1: The following three figures show simulated sample paths of stochastic processes: 1 0 100 200 300 400 500 2 0 100 200 300 400 500 3 0 100 200 300 400 500
Which of these processes could be a simulated AR(1) process? 5 MARKS
Problem 2: The following figure shows the scatterplot of a simulated process (Xt), with Xt -2 on the x-axis (the abscissa), and Xt on the y-axis (the ordinate). The correlation of the points in the scatterplot is about 0.80.
−4 −2 0 2 4 6 â— â— â— â— â— â— â— â— â— â— â— â— â— â— â— â— â— â— â— â—â— â— â— â— â— â— â— â— â— â— â— â— â— â— â— â— â— â— â— â— â— â— â— â— â— â— â— â— â— â— â— â— â— â— â— â— â— â— â— â— â— â— â— â— â— â— â— â— â— â— â— â— â— â— â— â— â— â— â— â— â— â— â— â— â— â— â— â— â— â— â— â— â— â— â— â— â— â— â— â— â— â— â— â— â— â— â— â— â— â— â— â— â— â— â— â— â— â— â— â— â— â— â— â— â— â— â— â— â—…
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Practice Another: Use technology to find the quadratic regression curve through the given points. (Round all coefficients to four decimal places.) (1, 4), (3, 7), (4, 5), (5, 3) y(x) = Need Help? Read It Watch It 5. [–/0.62 Points] DETAILS WANEFMAC7 2.1.027. MY NOTES PRACTICE ANOTHER Crude oil imports to one country from another for 2009–2013 could be approximated by the following model where t is time in years since the start of 2000. I(t) = -33t^2 + 800t - 3,000 thousand barrels per day (9 ≤ t ≤ 13) According to the model, approximately when were oil imports to the country greatest? HINT [See Example 1.] (Round your answer to two decimal places.) t = How many barrels per day were imported at that time? (Round your answer to two significant digits.) thousand barrels Need Help? Read It 6. [–/0.62 Points] DETAILS WANEFMAC7 2.1.031. MY NOTES PRACTICE ANOTHER Revenue The market research department of the Better Baby Buggy Co. predicts that the demand equation for its buggies is…
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The following sub-parts address the quantization and rounding principle, as well as the effect of undersampling. Answer the following: A digital signal processing system, with a twelve-bit uniformly quantizing analog-to-digital converter and a sampling rate of 16 kHz, is used to process analog signals band-limited to the frequency range 0 Hz to 4 kHz. Estimate the maximum achievable signal-to-quantization noise ratio (SQNR) for sinusoidal input signals, and state what assumptions it is reasonable to make about the statistical and spectral properties of the quantization noise.
ii. Use MATLAB to quantize a random white noise signal. Quantize a random white noise signal (use randn(1,N) with N the number of samples generated) and compute the mean square error (MSE) and plot the histogram of the quantization error. Comment if this reflects the theory well - i.e. by comparing the histogram with the theoretical PDF model and/or by calculating the theoretical error and comparing it against t…
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FIN 5309 Homework 6 - Spring 2021Due May 17, 2021
Instructions:You can either write down your assignment or type it in a Word file or a combination of both. Please submit it in Moodle and make sure it is clear to see if you scan your handwritten homework. Unless explicitly stated otherwise, solve every question manually. Your answers will be graded both on your demonstrated understanding of the concepts from the book and from the class, as well as the clarity of your explanations. For any R application, including the screenshots of both commands and results in your homework, will allow us to more easily give partial credit. No late submissions will be accepted, except with prior permission.
(30 points) Consider the following autocorrelation and partial autocorrelation coefficients estimated using 500 observations for a weakly stationary series, Yt:acf: 0.307, -0.013, 0.086, 0.031, -0.197pacf: 0.307, 0.264, 0.147, 0.086, 0.049
Using the simple 'rule of thumb,' determine which, i…
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