a probability density function (pdf) of wind speed, y, pl)that is flat from 0 mis to a cutof velocity ve m/s, Pr(v)-( and turbine power, P, as a function of the random variable v of the form 2 where n is the turbine efficiency and v, is the rated velocity such that 2 For the following, assume vc-20 m/s, η-04, ρ 122 kg/m3, A-4x104 m? and v-20 m/s-ve- (a) Calculate the mean value of the random variable defined by this...
Marilyn v Hypothesis test for the population mean: t test It seer ve days that college graduates who are employed full-time work more than 40-hour weeks. Data are available that can help us decide if this is true A survey was recently sent to a group of adults selected at random. There were 13 respondents who were college graduates employed full-time. The mean number of hours worked per week by these 13 respondents was 45 hours, with a standard deviation...
Methyl Red Methyl Red ve MR/V/P Questions For MR Test what does red mean? Which bacteria is positive for MR? For VP, which acid are we detecting? B A Can a bacteria be positive for both MR and VP?
Exercise 4) Consider the RC network shown, where v(t) is the input voltage and ve(t) is the circuit output voltage. R is the same for all resistors (4a) Write differential equations of the circuit in terms of the currents. Convert the equa tions to the Laplace domain (5 marks)v(oO 4b) Find the transfer function Ve(s)/V(s) (5 marks) (4c) Using the final value theorem, calculate the steady-state value of ve(t) for an unit step input of u(t), i.e., u(t)-1 V (2.5...
Suppose V is a zero-mean Gaussian random variable, and define the random processes X(t) = Vt and Y(t) = V2t for −∞ < t < ∞. a)Find the crosscorrelation function for these two random processes. b)Are these random processes jointly wide-sense stationary?
Suppose V is a zero-mean Gaussian random variable, and define the random processes X(t) = Vt and Y(t) = V2t for −∞ < t < ∞. a)Find the crosscorrelation function for these two random processes. b)Are these random processes jointly wide-sense stationary?
Let X and Y be two independent Gaussian random variables with common variance σ2. The mean of X is m and Y is a zero-mean random variable. We define random variable V as V- VX2 +Y2. Show that: 0 <0 Where er cos "du is called the modified Bessel function of the first kind and zero order. The distribution of V is known as the Ricean distribution. Show that, in the special case of m 0, the Ricean distribution simplifies...
4. , XnER, let Eo,E1,..,Enbe independent normally distributed random Let Xo, X1, variables with common mean 0 and common variance σ2, and suppose Let a, b and σ2 be the maximum likelihood estimators of b,a and σ2 Note that these expressions involve only the training data(X1, Y the test data(xo. Yo) ,(xn%,). They omit The training error of our regression model is While its teat prediction) error is We know that In this exercise, we prove MSE (1+1+grt*)e* Note that...
3.24. Problem*. (Section 11.3) (a) Show that for a nonnegative random variable X with mean, P(X > 2m) S (b) For a nonnegative random variable X, what upper bound can we achieve for PX > 3)?
1. Show that if X(t) is a real random process with finite mean power and a mean power spectral density function Sx(S), then for all f. (a) Sx(f) > 0: (b) Sx(-f)=Sx(f). Hint: Recall that if x(t) is a real signal with spectrum X(f), then X (f) = X(-).