Skip to content
GATETECH

GATE CS Eigenvalues and Eigenvectors, LU Decomposition questions

Practise Eigenvalues and Eigenvectors, LU Decomposition questions for GATE CS. Explore official PYQs and original topic-wise quizzes, check answers and view available solutions. Free, no sign-in.

Subject, topic, year and type filter the full library. Match any choice within a filter, and all selected filter categories. Search, source and sort apply to this page.

6 on this page
Official PYQ2011Engineering MathematicsEigenvalues and Eigenvectors, LU DecompositionMCQ · 1 mark
Consider the matrix as given below. [123047003]\begin{bmatrix} 1 & 2 & 3 \\ 0 & 4 & 7 \\ 0 & 0 & 3\end{bmatrix} Which one of the following options provides the CORRECT values of the eigenvalues of the matrix?
Official PYQ2010Engineering MathematicsEigenvalues and Eigenvectors, LU DecompositionMCQ · 1 mark
Consider the following matrix A=[23xy]A = \left[\begin{array}{cc}2 & 3\\x & y \end{array}\right] If the eigenvalues of A are 44 and 88, then
Official PYQ2008Engineering MathematicsEigenvalues and Eigenvectors, LU DecompositionMCQ · 1 mark
How many of the following matrices have an eigenvalue 1? [1000][0100][1−111]\left[\begin{array}{cc}1 & 0 \\0 & 0 \end{array} \right]\left[\begin{array}{cc}0 & 1 \\0 & 0 \end{array} \right] \left[\begin{array}{cc}1 & -1 \\1 & 1 \end{array} \right] and [−101−1]\left[\begin{array}{cc}-1 & 0 \\1 & -1 \end{array} \right]
Official PYQ2007Engineering MathematicsEigenvalues and Eigenvectors, LU DecompositionMCQ · 1 mark
Let A be a 4×44 \times 4 matrix with eigen values -5,-2,1,4. Which of the following is an eigen value of the matrix[AIIA]\begin{bmatrix} A & I \\ I & A \end{bmatrix}, where II is the 4×44 \times 4 identity matrix?
Official PYQ2005Engineering MathematicsEigenvalues and Eigenvectors, LU DecompositionMCQ · 1 mark
What are the eigenvalues of the following 2×22\times 2 matrix? (2−1−45)\left( \begin{array}{cc} 2 & -1\\ -4 & 5\end{array}\right)
Official PYQ1993Engineering MathematicsEigenvalues and Eigenvectors, LU DecompositionMSQ · 1 mark
The eigen vector (s)(s) of the matrix [00α000000],α≠0\begin{bmatrix} 0 &0 &\alpha\\ 0 &0 &0\\ 0 &0 &0 \end{bmatrix},\alpha \neq 0 is (are)