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Audio De-noising using Adaptive Inertia Weight Particle Swarm Optimization Algorithm (AIW-PSO)

Jyoti Kaurav, Ravindra Pratap Narwaria

Abstract


There has been a lot of research in Audio de-noising so far but scope for improvement is always there. The motivation to use AIW-PSO algorithm as a possible alternative is to explore new ways to reduce global cost and to achieve better noise reduction performance. Particle swarm optimization is a heuristic stochastic evolutionary algorithm. However, standard PSO provides unbalanced exploration and exploitation. This paper presents a methodology to improve the performance of PSO optimization algorithm by changing the inertia weight dynamically and adaptively. As the optimization is required in PSO algorithm in different situations, the inertia weight in the proposed research method is adjusted automatically. Experimental results show that the proposed AIW-PSO algorithm outperforms the remaining methods such as Linear, Non-linear and Constant inertia weight strategies in most of the cases.

Keywords: PSO, AIW-PSO, CWI, LDI, NLI, SNR, PRE, MSE, Audio signal, ES, AD

Cite this Article

Jyoti Kaurav, Ravindra Pratap Narwaria. Audio De-noising using Adaptive Inertia Weight Particle Swarm Optimization Algorithm (AIW-PSO). Recent Trends in Electronics & Communication Systems. 2017; 4(2): 11–18p.


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