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首页> 外文期刊>IEEE transactions on biomedical circuits and systems >A VLSI Implementation of Independent Component Analysis for Biomedical Signal Separation Using CORDIC Engine
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A VLSI Implementation of Independent Component Analysis for Biomedical Signal Separation Using CORDIC Engine

机译:使用CORDIC发动机的生物医学信号分离独立分量分析的VLSI实现

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This study aims to design and implement a very large scale integration (VLSI) chip of the extend InfoMax independent component analysis (ICA) algorithm which can separate the super-Gaussian source signals. In order to substantially reduce the circuit area, the proposed circuit utilizes the time sharing matrix multiplication array (MMA) to realize a series of matrix multiplication operations and employs the coordinate rotation digital computer (CORDIC) algorithm to calculate the hyperbolic functions sinh (theta) and cosh (theta) with the rotation of the hyperbolic coordinate system. Also, the rotation of the linear coordinate system of the CORDIC is adopted for the design of a divider used for obtaining the required function value of tanh (theta) simply by evaluating sinh (theta) cosh (theta). Implemented in a TSMC 90-nm CMOS technology, the proposed ICA has an operation frequency of 100 MHz with 90.8 K gate counts. Furthermore, the measurement results show the ICA core can be successfully applied to separating mixed medical signals into independent sources.
机译:本研究旨在设计和实现扩展InfoMax独立分量分析(ICA)算法的非常大的集成(VLSI)芯片,其可以分离超高斯源信号。为了基本上减少电路区域,所提出的电路利用时间共享矩阵乘法阵列(MMA)来实现一系列矩阵乘法操作,并采用坐标旋转数字计算机(CORDIC)算法来计算SINH(θ)的双曲函数并通过双曲坐标系的旋转来旋转(θ)。而且,通过简单地通过评估Sinh(θ)Cosh(θ)来采用用于获得Tanh(θ)所需功能值的分频器的分频器的旋转。在TSMC 90-NM CMOS技术中实现,所提出的ICA的操作频率为100 MHz,栅极计数为90.8 k。此外,测量结果显示ICA核心可以成功地应用于将混合的医疗信号分离成独立源。

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