47,671 research outputs found
Moving sum procedure for change point detection under piecewise linearity
We propose a computationally and statistically efficient procedure for
segmenting univariate data under piecewise linearity. The proposed moving sum
(MOSUM) methodology detects multiple change points where the underlying signal
undergoes discontinuous jumps and/or slope changes. Theoretically, it controls
the family-wise error rate at a given significance level asymptotically and
achieves consistency in multiple change point detection, as well as matching
the minimax optimal rate of estimation when the signal is piecewise linear and
continuous, all under weak assumptions permitting serial dependence and
heavy-tailedness. Computationally, the complexity of the MOSUM procedure is
which, combined with its good performance on simulated datasets, making
it highly attractive in comparison with the existing methods. We further
demonstrate its good performance on a real data example on rolling
element-bearing prognostics
Moving sum procedure for change point detection under piecewise linearity
We propose a computationally and statistically efficient procedure for
segmenting univariate data under piecewise linearity. The proposed moving sum
(MOSUM) methodology detects multiple change points where the underlying signal
undergoes discontinuous jumps and/or slope changes. Theoretically, it controls
the family-wise error rate at a given significance level asymptotically and
achieves consistency in multiple change point detection, as well as matching
the minimax optimal rate of estimation when the signal is piecewise linear and
continuous, all under weak assumptions permitting serial dependence and
heavy-tailedness. Computationally, the complexity of the MOSUM procedure is
which, combined with its good performance on simulated datasets, making
it highly attractive in comparison with the existing methods. We further
demonstrate its good performance on a real data example on rolling
element-bearing prognostics
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Wyner-Ziv side information generation using a higher order piecewise trajectory temporal interpolation algorithm
Distributed video coding (DVC) reverses the traditional coding paradigm of complex encoders allied with basic decoding, to one where the computational cost is largely incurred by the decoder. This enables low-cost, resource-poor sensors to be used at the transmitter in various applications including multi-sensor surveillance. A key constraint governing DVC performance is the quality of side information (SI), a coarse representation of original video frames which are not available at the decoder. Techniques to generate SI have generally been based on linear temporal interpolation, though these do not always produce satisfactory SI quality especially in sequences exhibiting asymmetric (non-linear) motion. This paper presents a higher-order piecewise trajectory temporal interpolation (HOPTTI) algorithm for SI generation that quantitatively and perceptually affords better SI quality in comparison to existing temporal interpolation-based approaches
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