An adaptive control framework for stabilization of 1-dimensional linear uncertain discrete-time dynamical systems with symbolic feedback is developed. The plant output is assumed to be quantized and only its symbolic quantity is fed back to the controller. In the case of multi-dimensional systems, ideal system matrix is constructed so that the approach for the scalar systems can be applied in separate subspaces in the state space.