A rank 1 approximation (starting with the highest eigenvalue lambda-1) can be done using * ul * u{ where and ui are column vectors. These column vectors are the first columns of the orthogonal matrices U and V, that are part of the SVD. We note that the multiplication of a column vector by a row vector in fact produces an approximated matrix. ## Find the rank-1 approximation and show the image generated by it. BEGIN SOLUTION ## END SOLUTION Clipping input data to the valid range for imshow with RGB data (1o..1] for floats or [O..2551 for integers) 50 100 150 200 250 300 0 50 100 150 200 A rank 1 approximation (starting with the highest eigenvalue lambda-1) can be done using * ul * u{ where and ui are column vectors. These column vectors are the first columns of the orthogonal matrices U and V, that are part of the SVD. We note that the multiplication of a column vector by a row vector in fact produces an approximated matrix. ## Find the rank-1 approximation and show the image generated by it. BEGIN SOLUTION ## END SOLUTION Clipping input data to the valid range for imshow with RGB data (1o..1] for floats or [O..2551 for integers) 50 100 150 200 250 300 0 50 100 150 200