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Komok [63]
4 years ago
9

3 Points

Computers and Technology
1 answer:
tino4ka555 [31]4 years ago
6 0

Answer:

its B the person in the comments were right

Explanation:

took an edge test

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Consider the following arrays. 1 4 21 2 4 100 B # 111(A) L3π 42 Write MATLAB expressions to do the tollowing a. Select just the
andriy [413]

Answer:

Complete Matalb code along with explanation and output results are given below

Explanation:

We are given following two matrices A and B of size 4x3

A = [1 4 2; 2 4 100; 7 9 7; 3 pi 42]

B = log(A)

(a) Select just the second row of B

% to extract any row use this syntax  B(row no, : )  we can also extract more than 1 row or any particular elements in a specific row

B_row_2 = B(2,:)

(b) Evaluate the sum of the second row of B

% simply use the sum function and pass it any vector or matrix and it will return their sum

sum_B_row_2 = sum( B_row_2(:) )  

(c) Multiply the second column of B and the first column of A element by element

% first we extract the column 2 of matrix B and column 1 of matrix A. use this syntax  B( : ,col no ) to extract any column  

B_col_2 = B(:,2)

A_col_1 = A(:,1)

% Then we use ( .*) to multiply element by element. To use standard multiplication of matrices only use asterisk sign without coma

multiply=B_col_2.*A_col_1

(d) Evaluate the maximum value in the vector resulting from element-by- element multiplication of the second column of B with the first column of A

% we can find the maximum value in a vector or matrix by using max function so we pass the multiply variable where our result was stored

max_value = max(multiply)

(e) Use element-by-element division to divide the first row of A by the first three elements of the third column of B. Evaluate the sum of the elements of the resulting vector

%  First we extract the row 1 of matrix A

A_row_1 = A(1,:)

%  Then we extract the column 3 of matrix B

B_col_3 = B(:,3)

%  Then we extract the first 3 elements of column 3 of matrix B

B_col_3 = B_col_3(1:3)

% Finally we use ( ./ ) to use element by element division

divide = A_row_1./B_col_3

% Using the sum function again results in the addition of entire elements of resultant matrix

sum_divide = sum( divide(:) )

Only Code:

A = [1 4 2; 2 4 100; 7 9 7; 3 pi 42]

B = log(A)

B_row_2 = B(2,:)

sum_B_row_2 = sum( B_row_2(:) )  

B_col_2 = B(:,2)

A_col_1 = A(:,1)

multiply=B_col_2.*A_col_1

max_value = max(multiply)

A_row_1 = A(1,:)

B_col_3 = B(:,3)

B_col_3 = B_col_3(1:3)

divide = A_row_1./B_col_3

sum_divide = sum( divide(:) )

Output Results:

A =

    1.0000     4.0000     2.0000

    2.0000     4.0000   100.0000

    7.0000     9.0000     7.0000

    3.0000     3.1416    42.0000

B =  

  0.00000   1.38629   0.69315

  0.69315   1.38629   4.60517

  1.94591   2.19722   1.94591

  1.09861   1.14473   3.73767

B_row_2 =   0.69315   1.38629   4.60517

sum_B_row_2 =  6.6846

B_col_2 =  

  1.3863

  1.3863

  2.1972

  1.1447

A_col_1 =

  1

  2

  7

  3

multiply =

   1.3863

   2.7726

  15.3806

   3.4342

max_value =  15.381

A_row_1 =     1   4   2

B_col_3 =  

  0.69315

  4.60517

  1.94591

  3.73767

B_col_3 =

  0.69315

  4.60517

  1.94591

divide =

  1.44270   5.77078   2.88539

  0.21715   0.86859   0.43429

  0.51390   2.05559   1.02780

sum_divide =  15.216

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