A New Block Least Mean Square Algorithm for Improved Active Noise Cancellation

Abstract

Acoustic noise is an undesired disturbance that is present in the information carrying signal in telecommunication systems. The communication process gets affected because noise degrades the quality of speech signal. Adaptive noise reduction is a method of approximating signals distorted by additive noise signals. With no prior estimates of input or noise signal, the levels of noise reduction are attainable that would be difficult or impossible to achieve by other noise cancelling algorithms, which is the advantage of adaptive technique. Adaptive filtering before subtraction allows the treatment of inputs that are deterministic or stochastic, stationary or time variable. This paper provides an analysis of various adaptive algorithms for noise cancellation and a comparison is made between them. The strengths, weaknesses and practical effectiveness of all the algorithms have been discussed. This paper deals with cancellation of noise on speech signal using three existing algorithms—Least Mean Square algorithm, Normalized Least Mean Square algorithm and Recursive Least Square algorithm and a proposed algorithm—advanced Block Least Mean Square algorithm. The algorithms are simulated in Simulink platform. Conclusions have been drawn by choosing the algorithms that provide efficient performance with less computational complexity.

The original version of this chapter was revised: The spelling of one of the author’s name was corrected. The erratum to this chapter is available at DOI 10.1007/978-81-322-2757-1_66

An erratum to this chapter can be found at http://dx.doi.org/10.1007/978-81-322-2757-1_66