P.A. Mastorocostas, D.N. Varsamis, C.A. Mastorocostas, and C.S. Hilas (Greece)
block-diagonal recurrent networks, adaptive noise cancellation
This paper presents a dynamic neural filter for adaptive noise cancellation. The cancellation task is transformed to a system-identification problem, which is tackled by use of the Block-Diagonal Recurrent Neural Network. The filter is applied to a benchmark noise cancellation problem, where a comparative analysis with a series of other dynamic models is conducted, underlining the effectiveness of the proposed filter and its superior performance over its competing rivals.
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