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Exact(17)
To calculate the background weight matrix in [B], we directly add the weighted paths to the weight matrix along with the Monte Carlo simulation, instead of storing all the photon trajectories.
We will consider the assignment of the weight matrix in the following section.
Next, the algorithm for the conventional subspace MOE detector in [17] resembles that for the projected weight matrix in (19).
By imposing group sparsity of pose weight matrix in slice GAC, we interestingly provide a way to connect uniform and non-uniform deblurring.
Therefore, the constrained MOE weight matrix in (18) is projected onto the signal subspace, which can minimize the effects of noise and improve system performance.
This result is not surprising, as uncorrelated random perturbations of the weight matrix in a Hopfield network have been shown to have a small effect on the dynamics [45, 46].
Similar(43)
There are some minor differences in the results of hotspot analysis when applying different spatial weight matrices in ArcGIS.
Therefore, ESN randomly generates the input and recurrent weight matrices in network initialization and fixes them during network learning.
The approach presents parametrization in terms of linear matrix equation and quadratic matrix inequalitity which depend on parameter matrices similar to weight matrices in LQR theory.
This method allows designers to use any matrix function of the state as the weight matrices in the quadratic cost function.
Subsequently, the modal parameters of the model for different mean velocities of wind flow are directly estimated using weight matrices in the neural network.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com