PPU Adaptive LMS Algorithm, a Hardware-Efficient Approach; a Review on

The periodic partial updates (PPU) method is evaluated. Cost, performance, portability and physical size considerations compel serious resource limitations on adaptive signal processing systems. Partial-Selective weight updates techniques can be used to decrease the resource usage and hardware complication in practical fields at the likely price of greater steady-state MSE error and more lower convergence speed. Periodic partial update (PPU) is one of partial-selective weight update techniques by which, on behalf of updating the all weights (coefficients), a limit number of the weights are updated at each epoch. The performance, convergence speed and MSE error of periodic partial updates is evaluated in the presence of white and colored Gaussian input. It is concluded that in some practical fields, this method could be considered on behalf of full-update algorithm with some loses on quality.