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Two arrays are considered to be equal when the result of one array subtracted from the other is an array of zeros. In the script file, create the MATLAB commands to prove the following relationships (use arrays that you makeup yourself):
E(FG) = (EF)G (using matrix multiplication of square arrays)
Write the modified text file with the same name as the original file, but preprended with 'new_'. For instance, if the input filename was 'data.txt', the output filename would be 'new_data.txt'.
A one-dimensional steady-state heat flow, the mathematical formulation of problem - find out the temperature differences at each locations and calculate the temperatures at each locations
Write a function named solveSystem that has three inputs: two vectors consisting of coefficients [a b c] of two line equations of the form ax + by = c and a vector of x values.
An Efficient Human Identification Using Gait Analysis, Apply specific approach for Pattern Recognition,Implement this approach in MATLAB,Compare and discuss the results with others.
create a function that will use the secant method to tryt to find out the root
Compute the power spectral density vector. Plot the spectrogram using the same parameters as in lecture.
Verify that your code works by saving some text into a file (created in notepad / textedit) and saving the file with extension '.txt'. You should attach the file (call it 'test.txt') with your code.
assemble 1,000 bolt + hole combinations. The bolts have a mean diameter of 1.000 cm, normally distributed with standard deviation of 0.010 cm. The holes have a mean diameter of 1.030 cm, normally distributed with standard deviation of 0.015 cm.
To design a "custom" controller to reduce the vibrations of the seat and a PID controller to reduce the vibration of the seat
create two vectors X and Y of values from (-pi) to pr with a spacing of pi/10. Define the vector Z as: Z=(sin(sqrt(x^2+y^2)))/sqrt(x^2+y^2)
Select 10 features characterizing the population of about 100 countries. load it into Matlab. Normalize the data between 0 and 1. (min, max and minmax are some useful Matlab commands)
The body fat percentage (BFP) of a person can be estimated by the formula BFP= 1.2xBMI+0.23xAGE -10.8xGEnder-0.54 where BMI is the body mass index, given by BMI = 703 W/H^2, in which W is the weight in pounds and H is the height in inches
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