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DAC
2005
ACM

A non-parametric approach for dynamic range estimation of nonlinear systems

10 years 9 months ago
A non-parametric approach for dynamic range estimation of nonlinear systems
It has been widely recognized that the dynamic range information of an application can be exploited to reduce the datapath bitwidth of either processors or ASICs, and therefore the overall circuit area, delay, and power consumption. Recent advances in analytical dynamic range estimation methods indicate that by systematically decomposing the system inputs into orthonormal random variables using a mathematical procedure called polynomial chaos expansion (PCE), output statistics of interest can be obtained for both linear and nonlinear systems. Despite its power for capturing both spatial and temporal correlation, the application of this method has been limited only to near-Gaussian inputs. In this paper, we propose the first algorithm with the capacity of handling both near-Gaussian and non-Gaussian input signals. Our method is based on the use of independent component analysis (ICA). Our experiments show that the new algorithm can reduce the original relative errors of 2nd order momen...
Bin Wu, Jianwen Zhu, Farid N. Najm
Added 13 Nov 2009
Updated 13 Nov 2009
Type Conference
Year 2005
Where DAC
Authors Bin Wu, Jianwen Zhu, Farid N. Najm
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