In the book Quantum Mechanics: A Modern Development by Leslie E. Ballentine the Spectral Theorem is defined as follows (and I cite):
To each self-adjoint operator $A$ there corresponds a unique family of projection operators, $E(\lambda)$, for real $\lambda$, with the properties:
If $\lambda_1 < \lambda_2$ then $E(\lambda_1)E(\lambda_2)=E(\lambda_2)E(\lambda_1)=E(\lambda_1)$
If $\epsilon>0$, then $E(\lambda+\epsilon)|\psi\rangle \rightarrow E(\lambda)|\psi\rangle$ as $\epsilon\rightarrow 0$
$E(\lambda)|\psi\rangle \rightarrow 0$ as $\lambda\rightarrow-\infty$
$E(\lambda)|\psi\rangle \rightarrow |\psi\rangle$ as $\lambda \rightarrow +\infty$
$\displaystyle \int_{-\infty}^{\infty}\lambda \, \mathrm dE(\lambda)=A$
However, if we define $A$ to be a symmetric matrix (So $A=A^T$) then we can decompose $A$ as $A=T\Lambda T^{-1}$ with $T$ containing the eigenvectors of $A$ and $\Lambda$ being a diagonalized matrix containing the eigenvalues of $A$. How does this description of the spectral theorem for symmetric matrices apply to the definition given by Ballentine? I mean how do each step for defining the spectral theorem given by Ballentine support (or rather expand) the definition of the spectral theorem for symmetric matrices?