Impulsive noise are relatively short duration “on/off” pulses, caused by switching noise or adverse channel environments in a communication system, drop outs or surface degradation of audio recordings, clicks from computer keyboards etc. An impulsive noise filter can be used for enhancing the quality and intelligibility of noisy signals, and for achieving robustness in pattern recognition and adaptive control systems. This chapter begins with a study of the characteristics of an impulsive noise, and then proceeds to consider several methods for statistical modelling of an impulsive noise process. The classical method for removal of impulsive noise is the median filter. However, the median filter often results in some signal degradation. For optimal performance, an impulsive noise removal system should utilise (a) the distinct features of the noise and the signal, (b) the statistics of the signal and the noise, and (c) a model of the physiology of the signal and the noise generation. We describe a model-based system that detects each impulsive noise, and then proceeds to replace the samples obliterated by the impulse. We also consider the methods for introducing robustness to impulsive noise in parameter estimation.
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