Where hydrological data are sparse, scaling issues in surface runoff modeling can be dealt more effectively by integrating topographical indicators of structural hydrologic connectivity.
In this paper, signal flow graphs are mainly addressed for the efficient and forward stable Discrete Sine Transform (DST) algorithms having sparse, scaled orthogonal, rotational, rotational-reflection, and butterfly matrices.
The correlation-based networks that we analyzed are highly connected and not scale-free, as opposed to the sparse, scale-free networks that are observed in many biological and physical phenomena [ 2].
Since we can expect a vast number of true negatives when working with sparse, scale-free graphs, it would be helpful to see the loss over interacting and non-interacting node pairs separately.
In general, the feature of DAEs is a sparse large scale system of fully nonlinear and high index.
An improved three-dimensional local sparse motion scale invariant feature transform descriptor is used in [14], for RGB-D videos, based on grey pyramid, depth pyramid and optical flow pyramids that are built for both colour frames and depth maps.
However, models have mostly employed a daily time-step and have used a rather simple net calculation of the net photosynthesis, particularly for the estimation of future rice yield because the temperature projected by climate model still has sparse time scale.
The strong but sparse small-scale eddies along the x direction are partly decomposed to Fourier components of large scales >5 km.
The objective in this paper is to establish the connection between algebraic operations used in sparse and scaled orthogonal factorizations of DST I IV matrices, with the signal flow graph building blocks.
Large scale, sparse, complex numerical experiments are performed on clusters of magnetic dipoles, a quantum many-body system that is not block-diagonalizable.
A predictor-corrector continuation method tailored for large scale, sparse systems enables the quick calculation of the optimal solution as exhibited in challenging engineering problems such as the control of a cart with a double pendulum.
