Implementation of a new adaptive algorithm using fuzzy cost function and robust to impulsive noise

Adaptive filters are used in a wide range of applications such as noise cancellation, system identification, and prediction. One of the main problems for theses filters is the impulsive noise as it generates algorithm unstability. This work shows the development, simulation and hardware implementation of a new algorithm robust to impulsive noise. Hardware implementation becomes essential in many cases where a real time execution, reduced size, or low power system is needed. An efficient hardware architecture is proposed and different optimizations for size and speed are developed: no need for control state machine, reduced computation requirements due to simplifications, etc. Furthermore, two different implementations were done to test two simplified cost functions. Finally, comparison results are provided to test accuracy, performance and logic occupation, showing an efficient architecture for impulsive noise robustness.