Proceedings ArticleDOI
A single-chip FPGA design for real-time ICA-based blind source separation algorithm
Charayaphan Charoensak,Farook Sattar +1 more
- pp 5822-5825
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TLDR
An efficient hardware architecture for the implementation of real-time BSS that can be implemented using a low-cost FPGA is proposed and a good balance between hardware requirement (gate count and minimal clock speed) and separation performance is offered.Abstract:
Blind source separation (BSS) of independent sources from their mixtures is a common problem in real world multi-sensor applications. In this paper, we propose an efficient hardware architecture for the implementation of real-time BSS that can be implemented using a low-cost FPGA. The architecture offers a good balance between hardware requirement (gate count and minimal clock speed) and separation performance. The FPGA design implements the modified Torkkola BSS algorithm for audio signals based on the ICA (independent component analysis) technique. The separation is performed by implementing noncausal filters, instead of the typical causal filters, within the feedback network. The architecture of the hardware is described. Results of various FPGA simulations and real-time testing of the final hardware design in a real environment are given.read more
Citations
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Journal ArticleDOI
Implementation of Pipelined FastICA on FPGA for Real-Time Blind Source Separation
TL;DR: This paper implements the FastICA algorithm in a field-programmable gate array (FPGA), with the ability of real-time sequential mixed signals processing by the proposed pipelined FastICA architecture, and demonstrates the effectiveness of the presented hardware FastICA as expected.
Journal ArticleDOI
Energy-Efficient FastICA Implementation for Biomedical Signal Separation
TL;DR: This paper presents an energy-efficient fast independent component analysis (FastICA) implementation with an early determination scheme for eight-channel electroencephalogram (EEG) signal separation and the proposed four parallel one-units architecture.
Proceedings ArticleDOI
FPGA implementation of 4-channel ICA for on-line EEG signal separation
TL;DR: This paper presents an independent component analysis method with information maximization (Infomax) update applied into 4-channel one-line EEG signal separation that can be implemented on FPGA with a fixed-point number representation, and then the separated signals are transmitted via Bluetooth.
Proceedings ArticleDOI
A high-level synthesis flow for the implementation of iterative stencil loop algorithms on FPGA devices
Alessandro Antonio Nacci,Vincenzo Rana,Francesco Bruschi,Donatella Sciuto,Ivan Beretta,David Atienza +5 more
TL;DR: An automatic design flow to extract parallelism from an ISL algorithm is introduced and a design space exploration is performed to identify its best FPGA hardware implementation, in terms of both area and throughput.
Proceedings ArticleDOI
FPGA Implementation of FastICA based on Floating-Point Arithmetic Design for Real-Time Blind Source Separation
Kuo-Kai Shyu,Ming-Huan Li +1 more
TL;DR: The field programmable gate array (FPGA) implementation of FastICA for real-time signal process is proposed and the sample rate of 192 kHz is reached under the presented architecture.
References
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Book
Independent Component Analysis: Theory and Applications
TL;DR: This work presents a Unifying Information-Theoretic Framework for ICA, a novel and scalable framework for independent component analysis that combines supervised and unsupervised classification with ICA Mixture Models.
Proceedings ArticleDOI
Blind separation of convolved sources based on information maximization
TL;DR: This paper presents a feedback network architecture capable of coping with convolutive mixtures, and derives the adaptation equations for the adaptive filters in the network by maximizing the information transferred through the network.
Evaluation of blind signal separation methods
TL;DR: A unified methodology of evaluating BSS algorithms along with providing data online such that researches can compare their results is provided.
Proceedings ArticleDOI
Mixed-signal real-time adaptive blind source separation
TL;DR: A mixed-signal adaptive VLSI architecture for real-time blind separation of linear source mixtures is presented, which allows to separate and localize multiple acoustic sources in the acoustic scene.
Proceedings ArticleDOI
Blind source separation of audio signals using improved ICA method
TL;DR: An improved BSS method for audio signals based on ICA (independent component analysis) technique is proposed, which reduces the required length of the unmixing filters considerably as well as providing better results and faster convergence compared to the case with the conventional causal filters.