模数矩阵乘法的因式分解

2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) Pub Date : 2015-04-19 DOI:10.1109/ICASSP.2015.7178132

Edward H. Lee, Madeleine Udell, S. Wong

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引用次数: 5

摘要

我们提出矩阵分解作为一种使能技术模拟到数字矩阵乘法(AD-MM)。研究表明，模拟域中的因式分解提高了AD-MM在精度有限的模拟乘法中的总精度，减少了过完备矩阵所需的模数(A/D)转换次数，并避免了数字域中不必要的计算。最后，我们提出了一种使用交替凸松弛的分解算法。

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Factorization for analog-to-digital matrix multiplication

We present matrix factorization as an enabling technique for analog-to-digital matrix multiplication (AD-MM). We show that factorization in the analog domain increases the total precision of AD-MM in precision-limited analog multiplication, reduces the number of analog-to-digital (A/D) conversions needed for overcomplete matrices, and avoids unneeded computations in the digital domain. Finally, we present a factorization algorithm using alternating convex relaxation.

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2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

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