2 resultados para Noise mapping


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Band excitation piezoresponse force microscopy enables local investigation of the nonlinear piezoelectric behavior of ferroelectric thin films. However, the presence of additional nonlinearity associated with the dynamic resonant response of the tip-surface junction can complicate the study of a material's nonlinearity. Here, the relative importance of the two nonlinearity sources was examined as a function of the excitation function. It was found that in order to minimize the effects of nonlinear tip-surface interactions but achieve good signal to noise level, an optimal excitation function must be used. (C) 2011 American Institute of Physics. [doi: 10.1063/1.3593138]

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A technique for optimizing the efficiency of the sub-map method for large-scale simultaneous localization and mapping (SLAM) is proposed. It optimizes the benefits of the sub-map technique to improve the accuracy and consistency of an extended Kalman filter (EKF)-based SLAM. Error models were developed and engaged to investigate some of the outstanding issues in employing the sub-map technique in SLAM. Such issues include the size (distance) of an optimal sub-map, the acceptable error effect caused by the process noise covariance on the predictions and estimations made within a sub-map, when to terminate an existing sub-map and start a new one and the magnitude of the process noise covariance that could produce such an effect. Numerical results obtained from the study and an error-correcting process were engaged to optimize the accuracy and convergence of the Invariant Information Local Sub-map Filter previously proposed. Applying this technique to the EKF-based SLAM algorithm (a) reduces the computational burden of maintaining the global map estimates and (b) simplifies transformation complexities and data association ambiguities usually experienced in fusing sub-maps together. A Monte Carlo analysis of the system is presented as a means of demonstrating the consistency and efficacy of the proposed technique.