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Matrix Methods
Eigenvalues and Eigenvectors:
• Engineering applications may require solution of a matrix
equation in the form:
• Equation 1. AX = LAMBDA X
• where A is a square matrix (usually 2x2 or 3x3).
Lambda represents scalar values called eigenvalues, and X
are a column matrices called eigenvectors containing x, y,
z values. Eigenvectors represent a direction, and it the ratios
of x : y : z that is important, rather than the actual values. An
eigenvalue is said to be normalized when x^2 + y^2 +z^2 = 1
Matrix Methods.pptxhhhhhhhhhhhhhhhhhhhhh
Matrix Methods.pptxhhhhhhhhhhhhhhhhhhhhh

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Matrix Methods.pptxhhhhhhhhhhhhhhhhhhhhh

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  • 5. Eigenvalues and Eigenvectors: • Engineering applications may require solution of a matrix equation in the form: • Equation 1. AX = LAMBDA X • where A is a square matrix (usually 2x2 or 3x3). Lambda represents scalar values called eigenvalues, and X are a column matrices called eigenvectors containing x, y, z values. Eigenvectors represent a direction, and it the ratios of x : y : z that is important, rather than the actual values. An eigenvalue is said to be normalized when x^2 + y^2 +z^2 = 1