Abstract-In this paper, dynamic algorithm transformations (DAT's) for designing low-power reconfigurable signal-processing systems are presented. These transformations minimize energy dissipation while maintaining a specified level of mean squared error or signal-to-noise ratio. This is achieved by modeling the nonstationarities in the input as temporal/spatial transitions between states in the input state-space. The reconfigurable hardware fabric is characterized by its configuration state-space. The configurable parameters are taken to be the filter taps, coefficient and data precisions, and supply voltage V dd . An energy-optimal reconfiguration strategy is derived as a mapping from the input to the configuration state-space. In this strategy, taps are powered down starting with the tap with the smallest value of [