MATLAB
%%
T = 1;
N = 11;
np = 2;
dt = 0.001;
tmax = np*T;
t = -tmax:dt:tmax;
%% Function 1
%the following code was used to create the x(t) function
xrange = floor((T/dt)/15);
x1 = linspace(0,1,xrange);
x2 = x1(end-1:-1:1);
x3 = linspace(0,2,2*xrange);
x4 = x3(end-1:-1:1);
x5 = zeros(1,xrange);
x6 = x1;
x7 = 2*ones(1,xrange);
x8 = 1+x2;
x9 = -0.5*ones(1,xrange);
x10 = x1/2-0.5;
xtemp = [x1 x2 x3 x4 x5 x6 x7 x8 x9 x10];
ztemp = zeros(1,floor(T/dt)-length(xtemp));
xtT = [ztemp xtemp];
tT = dt:dt:T;
xt = 0;
for nn = 1:np
xt = [xtT xt xtT];
end
plot(t,xt)
axis([-tmax tmax -1 3])
grid on
xlabel('Time(s)');
%%
% Determine ak coefficients for x(t)
% Plot the approximation of x(t) using ak coefficients for
|k|<=11
%% function 2
% x2(t) = sin(4*pi*t) 0<t<1/2
% x2(t) = 0 1/2<t<1
% x2(t) = x2(t+1)
% Determine ak coefficients for x2(t)
% Plot the approximation of x2(t) using ak coefficients for
|k|<=11
ANSWER:
Given that
Executable Code:
T = 1;
N = 11;
np = 2;
dt = 0.001;
tmax = np*T;
t = -tmax:dt:tmax;
%% Function 1
%the following code was used to create the x(t) function
xrange = floor((T/dt)/15);
x1 = linspace(0,1,xrange);
x2 = x1(end-1:-1:1);
x3 = linspace(0,2,2*xrange);
x4 = x3(end-1:-1:1);
x5 = zeros(1,xrange);
x6 = x1;
x7 = 2*ones(1,xrange);
x8 = 1+x2;
x9 = -0.5*ones(1,xrange);
x10 = x1/2-0.5;
xtemp = [x1 x2 x3 x4 x5 x6 x7 x8 x9 x10];
ztemp = zeros(1,floor(T/dt)-length(xtemp));
xtT = [ztemp xtemp];
tT = dt:dt:T;
xt = 0;
for nn = 1:np
xt = [xtT xt xtT];
end
plot(t,xt)
axis([-tmax tmax -1 3])
grid on
xlabel('Time(s)');
%%
% Determine ak coefficients for x(t)
% Plot the approximation of x(t) using ak coefficients for
|k|<=11
%% function 2
% x2(t) = sin(4*pi*t) 0<t<1/2
% x2(t) = 0 1/2<t<1
% x2(t) = x2(t+1)
% Determine ak coefficients for x2(t)
% Plot the approximation of x2(t) using ak coefficients for
|k|<=11
Expected output:

Now, let’s assume that the distribution of codons is not uniformly random. We also assume that only 5 codons {C1,C2,C3,C4,C5} appear in a dataset with a set of 10 of observations of codon {X1=C2, X2=C1, X3=C1, X4=C4, X5=C1, X6=C3, X7=C5, X8 =C2, X9=C4, X10=C3}. Compute the probability distribution of the five codons. If C2 is a start codon and C3 is a stop codon, with the distribution you just computed, what is the probability that a start codon (C2) is...
Could someone help me to solve this problem? Please explain
the steps
Insulated x1 x 2 x 3 x4 x5 x 6 x7 x8 x9 x10 x1 x12 x13 x14 x15 x16 x17 x18 x19 x20 x21 x22 x23 x24 x25 T 30 ← |T-50C h- 500 W/m2 C T-20 C 1. 2. Write the Finite Volume equation for node 23. [3 points] Write the 23"d line of the coefficient matrix and the right hand side [2 points] [ k-200...
Let X denote the proportion of allotted time that a randomly selected student spends working on a certain aptitude test. Suppose the pdf of X is otherwise where-1くθ. A random sample of ten students yields data X1 = 0.49, x2-0.94, x3-0.92, X1 0.90, x8-0.65, x9 = 0.77, x10 = 0.97. 0.79, x5-0.86, x6-0.73, x7 = (a) Use the method of moments to obtain an estimator of θ 1 + X 1 + X (1-%)2 Compute the estimate for this data....
Let X denote the proportion of allotted time that a randomly selected student spends working on a certain aptitude test. Suppose the pdf of X is otherwise where-1くθ. A random sample of ten students yields data X1 = 0.49, x2-0.94, x3 = 0.92, xa 0.90, x8-0.65, x9 = 0.77, x10 = 0.97. 0.79, x5-0.86, x6-0.73, x7 = (a) Use the method of moments to obtain an estimator of θ 1 + X 1 + X (1-%)2 Compute the estimate for...
Find the DTFT a. x1[n]=(.3)^nµ[n] b. x2[n]=(.3)µ[n-1] c. x3[n]=(.3)^n(µ[n]-µ[n-10]) d. x4[n]=(.3)^n(µ[n-1]-µ[n-10]) e. x5[n]=δ[n] f. x6[n]=δ[n-1] g. x7[n]=δ[n]+3δ[n-1]+7δ[n-3]
identify the leading and lagging measures, find the correlation matrix, and purpose a cause and effect model using the strongest correlations Myatt Steak House 2010 2011 2012 2013 2014 Order Accuracy X1 86.0% 86.0% 89.0% 90.0% 95.0% Timeliness of Delivery X2 84.0% 82.0% 86.0% 93.0% 95.0% Table Cleanliness X3 4.8 4.8 5.1 5.6 5.8 Customer Satisfication X4 93.4% 93.2% 94.2% 95.3% 96.7% Total # Complaints X5 492 467 431 326 310 Customer Referrals X6 6 12 24 48 96 Gross...
Consider the high temperature diffusion of Arsenic at 1619°C for 290 hours into a semi-infinite solid cylinder of pure silicon having a radius R=810 E-6 m. Assume values of Do = 0.218 cm2/s, Q = 332.2 kJ/mole, R = 8.314 J/mole-K and a surface concentration 6E18 atoms/cm3. Determine the concentration at the ten (10) equally spaced distances from the surface listed below. a) Cx(@x0=0.0∙R) = Cx0= ___6E+18_________ C@surface b) Cx(@x1=0.1∙R) = Cx1= _________________ c) Cx(@x2=0.2∙R) = Cx2= ...
function x(t) = sin(4*pi*t) 0<t<1/2 x(t) = 0 1/2<t<1 x(t) = x2(t+1) Determine ak coefficients for x(t) Plot the approximation using matlab of x(t) using ak coefficients for |k|<=11
MATLAB
code starts here ---------
clear
T0=2;
w0=2*pi/T0;
f0=1/T0;
Tmax=4;
Nmax=15;
%---
i=1;
for t=-Tmax: .01:Tmax
T(i)=t;
if t>=(T0/2)
while (t>T0/2)
t=t-T0;
end
elseif t<=-(T0/2)
while (t<=-T0/2)
t=t+T0;
end
end
if abs(t)<=(T0/4)
y(i)=1;
else
y(i)=0;
end
i=i+1;
end
plot(T,y),grid, xlabel('Time (sec)'); title('y(t) square wave');
shg
disp('Hit return..');
pause
%---
a0=1/2;
F(1)=0; %dc freq
C(1)=a0;
for n=1:Nmax
a(n)=(2/(n*pi))*sin((n*pi)/2);
b(n)=0;
C(n+1)=sqrt(a(n)^2+b(n)^2);
F(n+1)=n*f0;
end
stem(F,abs,(C)), grid, title(['Line Spectrum: Harmonics = '
num2str(Nmax)]);
xlabel('Freq(Hz)'), ylabel('Cn'), shg
disp('Hit return...');
pause
%---
yest=a0*ones(1,length(T));
for n=1:Nmax
yest=yest+a(n)*cos(2*n*pi*T/T0)+b(n)*sin(2*n*pi*T/T0);...
python
1
import matplotlib.pyplot as plt
2
import numpy as np
3
4
abscissa = np.arange(20)
5
plt.gca().set_prop_cycle(
’
color
’
, [
’
red
’
,
’
green
’
,
’
blue
’
,
’
black
’
])
6
7
class MyLine:
8
9
def __init__(self,
*
args,
**
options):
10
#TO DO: IMPLEMENT FUNCTION
11
pass
12
13
def draw(self):
14
plt.plot(abscissa,self.line(abscissa))
15
16
def get_line(self):
17
return "y = {0:.2f}x + {1:.2f}".format(self.slope,
self.intercept)
18
19
def __str__(self):...