PERFORMANCE COMPARISION OF ENVIRONMENTAL NOISE MODELLING USING HIDDEN MARKOV MODEL AND FUZZY HIDDEN MARKOV MODEL

摘要

Signal model can provide the basis for the theoretical description of a signal processing system. The signal models are used to learn about the signal source when it is unavailable. Also these models are used to realize many practical systems. In this paper environmental noise signals are modelled and these modelled noise signals can be used as a reference noise signal for the noise cancellation system when the type of noise is not known priori. In this work, an approach to model the environmental noises using Hidden Markov Model (HMM) and Fuzzy Hidden Markov models (FHMM) are used and thereby use the modelled noise as reference noise input for cancelling the encountered noise using Fuzzy Recursive Least Square algorithm (FRLS) is proposed. The system is tested for various noises like horn noises from bus, car and babble noise. The performance of both the algorithms is compared. Experimental results show that Fuzzy Recursive Least Square algorithm with reference noise from fuzzy HMM based modelled noise provides 33% better performance than Recursive Least Square algorithm with reference noise from HMM based modelled noise.