Abstract
In this paper, known methods for estimating the stochasticity of acoustic signals are compared, along with a new method based on adaptive signal filtration. Statistical simulation shows that the described method has better characteristics (lower variance and bias) than the other stochasticity measures. The parameters of the method, and their influence on performance, are investigated. Practical implementations for using the method are considered.
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CITATION STYLE
Aleinik, S., & Kudashev, O. (2014). Estimating stochasticity of acoustic signals. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8773, pp. 192–199). Springer Verlag. https://doi.org/10.1007/978-3-319-11581-8_24
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