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Robust crosstalk cancellation methods with multiple loudspeakers have been proposed [8, 20, 21].
Activation methods with multiple foils and a copper wire have been used for the mentioned measurements.
However, these methods with multiple reference images have limitation in online image dehazing applications [6, 7] and may need a special imaging sensor [1 3].
For purposes as our multi-area online approach, a sliding data window frame for estimating the distributed damping factor of low-frequency electromechanical oscillations based on Prony and Fourier methods with multiple empirical orthogonal functions (EOFs) analysis is presented.
Deep learning methods are representation learning methods with multiple levels of representation, obtained by composing simply but nonlinear modules that each transforms the representation at one level (starting with the raw input) into a higher representation slightly more abstract level, with the composition of enough such transformations, and very complex functions can be learned [1, 2].
However, both relative and absolute improvements of all three methods with multiple models were the highest in this category.
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Next, we tested the method with multiple constraints.
CLM method is a gradient-based method with multiple local optimization runs.
A novel faults analysis method with multiple PV grid-connected inverters for distribution systems is proposed.
The systematic method with multiple statistical models was coded for numerical solutions, and demonstrated for eight HMA IC projects.
This implies that the proposed method with multiple microphones and loudspeakers can be implemented as a simple extension of the single microphone-loudspeaker case.
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