On the Converse Inequality of Markov Type in L Norm

The converse inequality of Markov type is discussed in this note. The main result says that the best possible constant for this inequality is the square root of the least eigenvalue of a certain positive definite matrix. As applications of the main result, the Laguerre weight and Hermite weight are investigated in detail, and the best constants in these two cases are obtained explicitly.