An adaptive deadzone inverse approach is developed for control of discrete-time systems with unknown deadzones at the input of linear dynamics. The proposed controller consists of an adaptive deadzone inverse, whose parameters are updated to cancel the effect of the deadzone, and a linear part, which is designed to achieve tracking of a reference signal by the system output. When the linear part of the system is known, its parameters are used to specify the parameters of the linear part of the controller. When the linear part of the plant is unknown, the linear control parameters are adaptively estimated. The control error caused by the adaptive deadzone inverse is expressed as a linearly parametrizable part plus a bounded disturbance. Adaptive laws which employ parameter projection are used to update the controller parameters. They are robust with respect to the bounded disturbance, and they result in parameter estimates needed to implement an adaptive deadzone inverse. We prove the closed-loop signal boundedness, and illustrate by simulations that the system tracking performance is significantly improved.