Answer:
% here x and y is given which we can take as
x = 2:2:10;
y = 2:2:10;
% creating a matrix of the points
point_matrix = [x;y];
% center point of rotation which is 2,2 here
x_center_pt = x(2);
y_center_pt = y(2);
% creating a matrix of the center point
center_matrix = repmat([x_center_pt; y_center_pt], 1, length(x));
% rotation matrix with rotation degree which is 45 degree
rot_degree = pi/4;
Rotate_matrix = [cos(rot_degree) -sin(rot_degree); sin(rot_degree) cos(rot_degree)];
% shifting points for the center of rotation to be at the origin
new_matrix = point_matrix - center_matrix;
% appling rotation
new_matrix1 = Rotate_matrix*new_matrix;
Explanation:
We start the program by taking vector of the point given to us and create a matrix by adding a scaler to each units with repmat at te center point which is (2,2). Then we find the rotation matrix by taking the roatational degree which is 45 given to us. After that we shift the points to the origin and then apply rotation ans store it in a new matrix called new_matrix1.
Standing for an exceptional performance would be normal "acceptable" in both scenarios.
(D) Standard of living. Because, from this text you can tell that Leo is a wealthy person, and welthy people tend to get the best things, including fancy neighborhoods and Cars. So its most likely (D)
The view that perpetual processes can be thought of in terms of a software/hardware metaphor is known as the: information processing view.
<h3>What is the Information Processing View?</h3>
Information processing view is explained by the cognitive theory to explain how the brain encodes information and how information are filtered from what we pay attention to in a particular moment. This also determines what is stored in the short-term or in our long-term memory.
Therefore, the view that perpetual processes can be thought of in terms of a software/hardware metaphor is known as the: information processing view.
Learn more about the information processing view on:
brainly.com/question/24863946
Answer:
A table with sample values
A chart with sample values
Explanation:
