👉 In linear algebra, an eigenvector is a vector that changes by a scalar multiple (a scalar exponent) when a matrix in linear algebra is multiplied by it. Eigenvectors are particularly important because they provide a basis for the space of vectors, and they can also be used to represent linear transformations. An eigenvector is typically represented as a column vector (also known as a row vector), with each entry being the eigenvalue associated with that eigenvector. The product of an eig
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What is the definition of Eigenvector? 🙋
👉 In linear algebra, an eigenvector of a square matrix A is a non-zero vector v such that when multiplied by A, the result is a scalar multiple of v. Mathematically, this means that for any scalar λ, there exists a vector w such that (A - λI)v = 0. This concept can be understood in terms of linear transformations: if you have two vectors u and v, then multiplying them together gives you a new vector that is another vector that is
