I need help programming this in MATLAB. Transformation from cartesian coordinates to Keplerian orbital elements. This has to be done as a function script in the form (a,ecc,inc,raan,argp,f) = cart2orb(x,y,z,vx,vy,vz) whose inputs are the cartesian coordinates x, y, and z with their respective velocities vx, vy, (expressed in km and km/s respectively), and whose outputs are the semi-major axis (a) (in km), the eccentricity (ecc), the inclination (inc), the right ascension of the ascending node (raan), the argument of perigee (argp), and the true anomaly (f) (with all the angles expressed in degrees). Use μ⊕ = 398600.4418 km3/s2 as the gravitational constant of the Earth

make a code , if you can uses mathlab keep basic code no if or return

Write MATLAB code that will plot the function x² - 10x + 25 over the x values 0 to 10 on a regular plot (use the command plot) using 21 evenly spaced points with the linspace command in one subplot and then for the second subplot, plot the same function over the x values 10-¹ to 10 ¹ using 21 evenly spaced points on a semi logarithmic plot (use the command semilogx). Put markers on each point used in the calculations (using a circle, x, or +, your choice) using a different marker and color for each plot, and include axis labels on each subplot. If the code is written correctly, your subplots should appear like the ones below. 25 y-axis 20 15 10 X 5 0 0 2 4 x-axis 6 8 10 25 PO 20 y-axis 15 10 5 0 10-1 O Copy/paste your code that will create the subplots in the text box below. 0 0 0 0 0 0 0 10⁰ x-axis 0 0 0 0 0 10¹

Write a MatLab user-defined function that determines the coefficients of a cubic polynomial, f(x)=a₂x³ + a₂x² + a₁x + a that best fits a given set of data points. The function should also calculate the overall error E. Name the function [a,Er] = CubPolFit(x,y), where the input arguments x and y are vectors with the coordinates of the data points, and the output argument a is a four-element vector with the values of the coefficients a3, a₂, a₁, a. The output argument Er is the value of the overall error. " (a) Use CubPolFit to find the cubic polynomial that best fits the data in the rubber tension tests (see lecture slides): Curve fitting - polynomial regression - Example A tension test is conducted for determining the stress-strain be- havior of rubber. The data points from the test are shown in the figure, and their values are given below. Determine the fourth order polynomial that best fits the data points. Make a plot of the data points and the curve that corresponds to the…

Can you represent the following Boolean function f(A, B) with a linear classifier? If yes, show the linear classifier. If not, briefly explain why not. f(A, B) A B 1 1 1 1

I'm having trouble understanding what exactly makes a linear ordinary differential equation "linear". I know that the major advantage of the linear ODEs is that a linear combination of particular solutions gives another particular solution. Characterized by additivity and homogeneity, this means that the output for a sum of inputs is equal to the sum of outputs for each individual input (e.g., f(3) + f(5) = f(3+5)= f(8)) and scaling the input by a factor scales the output by the same factor (e.g., f(6x) =6f(x)...but how would this look? Like say if I had 4e^5(t-1) satisfying the differential equation dy/dt=5y where y(1)=4, what would that "linear combination" look like?

Write Matlab program to plot the functions: f1 = sin(2x)  f2 = 2sin(x)cos(x) Given x = 0:0.01:2pi

answer  last time was not understood or incorrect C=3 for the code

Determine if each function is injective, surjective or bijective. Give one counterexample for each that it is not. 1. function f from {a,b,c,d} to itself, where f(a) = d,  f(b) = b,  f(c) = a,  f(d) = c