Key result
A VLSI chip of the extend InfoMax ICA algorithm using a CORDIC engine achieved an operation frequency of 100 MHz with 90.8 K gate counts and successfully separated mixed medical signals.
Why the study?
The study aimed to design and implement a VLSI chip of the extend InfoMax independent component analysis algorithm capable of separating super-Gaussian source signals while substantially reducing circuit area.
The proposed VLSI implementation of the ICA algorithm using a CORDIC engine successfully separates mixed medical signals into independent sources with reduced circuit area.
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Feasible low-area VLSI ICA implementation for medical signals; leaves open clinical validation before diagnostic adoption.
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.
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Chen et al. (2020) studied Biomedical signal separation. VLSI chip of extend InfoMax ICA algorithm using CORDIC engine was evaluated on Operation frequency and gate counts. A VLSI chip of the extend InfoMax ICA algorithm using a CORDIC engine achieved an operation frequency of 100 MHz with 90.8 K gate counts and successfully separated mixed medical signals.
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