Adaptive Noise Cancellation Using Partially Recurrent Fuzzy System
In this paper, a partially recurrent fuzzy system is developed to function as an adaptive noise canceller. In order to cancel noise distorting the information signal, the temporal information (dynamics) underlying the noise source and the distorting noise, which is generated by the noise source passing through some unknown channels, should be captured accurately. For this purpose, short-term memory is embedded into the input layer of the fuzzy system for handling local time information and internal feedback is introduced into the consequent part for processing global time information by virtue of a partially recurrent mechanism. A novel adaptive algorithm is proposed to tune the parameters of the premise and consequent part online. Simulation studies show that the proposed fuzzy system can cancel noise cancellation successfully for nonlinear dynamic channels.
A new estimator for a four-element plane array is introduced in order to get acoustic-passive direction estimation of targets.We concern much about the performance of the estimator under a two-target situation.In this paper,the two targets concerned are of the same type of acoustic source.Under different signal to interfere ratios,we propose the change of the precision of the direction estimation as the angle between the two targets changes.Our study was done under the real time Warfield situation,and may help the design of small acoustic-passive direction estimation arrays.