The forcing function (in black) in essence forces the system to resonate with it (although with a slight delay)
It can be seen that the different solutions start out from different positions (blue, red, orange graphs) but eventually fall in line with the forcing function. Thus we can say that eventually the forcing function forces out system to resonate with it drowning any effects of initial position or velocity.
G.3.a.i) Forced by 5 Sin[1.5 t) Here are three plots of solutions of a random forced...
Here are three plots of
solutions of the forced exponential diffeq y'[t] + 2.13 y[t] = 3
Sin[2 t] + Sin[4 t] with starter values on y[0] equal to -6, 0, and
7:
G.4.b.i) Merging onto a certain curve Here are three plats of solutions of the forced exponential diffeq with 0,and 7 r 2.13 fit 13 Sin [2 t]Sin [4 t]; endtine 9; Clearly, yl, y2, y3, t, s]; starterl 7; starter3 = -6: 1[t v2[t starter2 E(-r t)...
Problem 5 . This question considers uniform random points on the unit disc x2+92 〈 1 (a) A point (X, Y) is uniformly chosen in the unit disc. Find the CDF and PDF of its distance from the origin R X2 +Y2 (b) Compute the expected distance from the origin. (c) Determine the marginal PDF of X and Y (d) Are X and Y independent? (Justify your claims) e) One way to generate uniform random points on this disc is...
Consider these three moment generating functions, for X, Y and Z: (5 points each) m (t)=W-3 m, (t)=e + m,(t)=eW-7 a. What is the mean of X? b. What is the mean of Y? c. What is the mean of Z? d. What is the variance of X? e. What is the variance of Y? f. What is the variance of Z? Consider independent random variables X and Y with the following pmfs: y=1 (0.5 x=1 S(x)= {0.5 x =...
Can you please help me answer Task 2.b?
Please show all work.
fs=44100; no_pts=8192;
t=([0:no_pts-1]')/fs;
y1=sin(2*pi*1000*t);
figure;
plot(t,y1);
xlabel('t (second)')
ylabel('y(t)')
axis([0,.004,-1.2,1.2]) % constrain axis so you can actually see
the wave
sound(y1,fs); % play sound using windows driver.
%%
% Check the frequency domain signal. fr is the frequency vector and
f1 is the magnitude of F{y1}.
fr=([0:no_pts-1]')/no_pts*fs; %in Hz
fr=fr(1:no_pts/2); % single-sided spectrum
f1=abs(fft(y1)); % compute fft
f1=f1(1:no_pts/2)/fs;
%%
% F is the continuous time Fourier. (See derivation...
Someone plz plz help with this Statistics Intro to R programming
question!!!
Here are the examples and follow by my question!!
Thank you so much!! I appreciate it
!!!!My question!!!!
Question Type 1: If possible, calculate the 90% confidence intervals for the temperature it takes for crickets to chirp 15 chirps per second. Code (you must copy and paste your code like below in blue color): # Reading in the data Crickets-read.table(C:/Desktop/CricketChirpsvsTemperature.csv', header TRUE, #View Data View Crickets) #Data analysis...