TY - JFULL AU - Miljan B. Petrović and Dušan B. Petrović and Goran S. Nikolić PY - 2016/4/ TI - An Approach to Noise Variance Estimation in Very Low Signal-to-Noise Ratio Stochastic Signals T2 - International Journal of Computer and Information Engineering SP - 468 EP - 472 VL - 10 SN - 1307-6892 UR - https://publications.waset.org/pdf/10003872 PU - World Academy of Science, Engineering and Technology NX - Open Science Index 111, 2016 N2 - This paper describes a method for AWGN (Additive White Gaussian Noise) variance estimation in noisy stochastic signals, referred to as Multiplicative-Noising Variance Estimation (MNVE). The aim was to develop an estimation algorithm with minimal number of assumptions on the original signal structure. The provided MATLAB simulation and results analysis of the method applied on speech signals showed more accuracy than standardized AR (autoregressive) modeling noise estimation technique. In addition, great performance was observed on very low signal-to-noise ratios, which in general represents the worst case scenario for signal denoising methods. High execution time appears to be the only disadvantage of MNVE. After close examination of all the observed features of the proposed algorithm, it was concluded it is worth of exploring and that with some further adjustments and improvements can be enviably powerful. ER -