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We present a generic method for analyzing the effect of process variability in nanoscale circuits. The proposed framework uses kernel and a generic tail probability estimator to eliminate the need for a-priori density choice for the nature of circuit variation. This allows capturing the true nature of the circuit variation from a few random samples of its observed responses. The data-driven, non-parametric,...
The problem of concern here is the parameter estimation of chirp signals in the presence of additive noise. An improved cyclostationarity based algorithm is proposed to estimate the phase parameters. The novelty of the proposed algorithm lies in the iterative estimation of the second-order parameters. The main characteristics of the method include reduction in error propagation effect, increase in...
The difficulty for accurate determination of the angles of arrival (AOA) of signals arises from the optimization of likelihood functions of high dimension. Usually, a gradient-based technique is employed to find the optimum of the function. However, this method requires heavy computational work and the differentiability of the likelihood function. This paper presents two gradient-free methods: One...
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