SUMMARY
The Gram matrix, represented as A^TA, is positive definite if and only if the columns of matrix A are linearly independent, which implies that A is left invertible. This condition holds true exclusively for real matrices. For complex matrices, the Gram matrix is defined as A^*A, where A^* denotes the Hermitian adjoint of A. Thus, the positive definiteness of the Gram matrix is contingent upon the linear independence of the columns of A.
PREREQUISITES
- Understanding of linear independence in vector spaces
- Knowledge of matrix multiplication and properties
- Familiarity with real and complex matrices
- Concept of Hermitian adjoint in linear algebra
NEXT STEPS
- Study the properties of left invertible matrices
- Explore the concept of Hermitian matrices in detail
- Learn about the implications of positive definiteness in various applications
- Investigate the role of Gram matrices in machine learning and statistics
USEFUL FOR
Mathematicians, data scientists, and anyone involved in linear algebra, particularly those working with matrix theory and its applications in real and complex spaces.