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(θ) and cosh(θ) 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(θ) simply by evaluating sinh(θ)/cosh(θ). 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.

中文翻译：

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使用 CORDIC 引擎进行生物医学信号分离独立分量分析的 VLSI 实现


本研究旨在设计并实现一种扩展InfoMax独立分量分析(ICA)算法的超大规模集成(VLSI)芯片，该芯片可以分离超高斯源信号。为了大幅减少电路面积，该电路利用分时矩阵乘法阵列（MMA）实现一系列矩阵乘法运算，并采用坐标旋转数字计算机（CORDIC）算法计算双曲函数sinh（θ）和 cosh(θ) 随着双曲坐标系的旋转。此外，除法器的设计采用了CORDIC线性坐标系的旋转，用于简单地通过计算sinh(θ)/cosh(θ)来获得所需的tanh(θ)函数值。所提出的 ICA 采用 TSMC 90 nm CMOS 技术实现，工作频率为 100 MHz，门数为 90.8 K。此外，测量结果表明 ICA 核心可以成功地将混合医疗信号分离成独立的信号源。