On a Real-Time Blind Signal Separation Noise Reduction System

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ID: 10630
2018
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Abstract
Blind signal separation has been studied extensively in order to tackle the cocktail party problem. It explores spatial diversity of the received mixtures of sources by different sensors. By using the kurtosis measure, it is possible to select the source of interest out of a number of separated BSS outputs. Further noise cancellation can be achieved by adding an adaptive noise canceller (ANC) as postprocessing. However, the computation is rather intensive and an online implementation of the overall system is not straightforward. This paper intends to fill the gap by developing an FPGA hardware architecture to implement the system. Subband processing is explored and detailed functional operations are profiled carefully. The final proposed FPGA system is able to handle signals with sample rate over 20000 samples per second.
Reference Key
cedric2018oninternational Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Yiu, Ka Fai Cedric;Low, Siow Yong;Yiu, Ka Fai Cedric;Low, Siow Yong;
Journal international journal of reconfigurable computing
Year 2018
DOI
10.1155/2018/3721756
URL
https://www.hindawi.com/journals/ijrc/2018/3721756/abs/
Keywords Keywords not found

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