Conjugate-gradient acceleration provides a powerful tool for speeding up the convergence of a symmetrizable basic iterative method for solving a large system of linear algebraic equations with a sparse matrix. The object of this paper is to describe three generalizations of conjugate-gradient acceleration which are designed to speed up the convergence of basic iterative methods which are not necessarily symmetrizable. The application of the procedures to some commonly used basic iterative methods is described.