A class-B transistor amplifier with a volage gain of two has cross-over distortion, resulting in a non-linearfunction from input a to output y(x) as plotted below.y(x)slope=2hand written plz asapx/slope=2A zero-mean Gaussian random process with a standard deviation of 1 is fed into the input. i.e. X~ N(0, 1²).a) Draw an illustration of the mapping from px(x) into py(y) through the above non-linear function.b) Determine the output PDF py (y) and write as a mathematical expression.c) Plot the py(y).-0.5, 0 0.5

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Answered: A class-B transistor amplifier with a…

Advanced Engineering Mathematics

10th Edition

ISBN:9780470458365

Author:Erwin Kreyszig

Publisher:Erwin Kreyszig

Chapter2: Second-order Linear Odes

Section: Chapter Questions

Problem 1RQ

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A researcher is interested in testing whether annual house hold income in Philadelphia is normal. So she took a sample of 50 house holds and found that skewness (s)= 2.3190 and Kurtosis (k) = 6.7322. Use the Jarque- Bera Test to test , at alpha 0.05, whether income follows normal distribution. -Yes, population is normal because Chi-Square test is higher than critical value. -Yes, population is normal because Chi-Square test is less than critical value. -No, population is not normal because Chi-Square test is higher than critical value. -No, population is not normal because Chi-Square test is less than critical value.
Consider a real random variable X with zero mean and variance σ2X . Suppose that wecannot 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 information…
From exercise 9-15 Find the boundary of the critical region if the type I error probability is a) alpha = 0.01 and n = 10 b) alpha = 0.05 and n=10 c) alpha = 0.01 and n=16 d) alpha = 0.05 and n=16 From exercise 9-15 standard deviation = 20 H0: mu = 175 H1: mu >175
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