Literature DB >> 18244558

FPGA implementation of ICA algorithm for blind signal separation and adaptive noise canceling.

Chang-Min Kim1, Hyung-Min Park, Taesu Kim, Yoon-Kyung Choi, Soo-Young Lee.   

Abstract

An field programmable gate array (FPGA) implementation of independent component analysis (ICA) algorithm is reported for blind signal separation (BSS) and adaptive noise canceling (ANC) in real time. In order to provide enormous computing power for ICA-based algorithms with multipath reverberation, a special digital processor is designed and implemented in FPGA. The chip design fully utilizes modular concept and several chips may be put together for complex applications with a large number of noise sources. Experimental results with a fabricated test board are reported for ANC only, BSS only, and simultaneous ANC/BSS, which demonstrates successful speech enhancement in real environments in real time.

Entities:  

Year:  2003        PMID: 18244558     DOI: 10.1109/TNN.2003.818381

Source DB:  PubMed          Journal:  IEEE Trans Neural Netw        ISSN: 1045-9227


  3 in total

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Authors:  P Sutha; V E Jayanthi
Journal:  J Med Syst       Date:  2017-12-08       Impact factor: 4.460

2.  Micropower Mixed-signal VLSI Independent Component Analysis for Gradient Flow Acoustic Source Separation.

Authors:  Milutin Stanaćević; Shuo Li; Gert Cauwenberghs
Journal:  IEEE Trans Circuits Syst I Regul Pap       Date:  2016-06-29       Impact factor: 3.605

3.  A Null Space-Based Blind Source Separation for Fetal Electrocardiogram Signals.

Authors:  Luay Taha; Esam Abdel-Raheem
Journal:  Sensors (Basel)       Date:  2020-06-22       Impact factor: 3.576

  3 in total

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