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The first algorithm is based on a tensor product of regularized one-dimensional delta functions.
The first algorithm is based on a linear expansion around the zero-order solution.
The first algorithm is based on a new very general and precise approach applicable to planetary atmospheres with quite arbitrary absorption and scattering properties.
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The second algorithm is based on a Bayesian approach (Breassort).
The first algorithm is based on the smoother approach (Shumway and Stoffer [2]), and the second algorithm is based on dynamic filtering in conjunction with the expectation maximisation (EM) algorithm (Elliott and Krishnamurthy [3]).
The second algorithm is based on training a set of simple architecture multilayer neural networks.
The first algorithm is subgradient iteration based distributed decision making algorithm and the second algorithm is based on lower bound and upper bound switching.
· The first part of the algorithm is based on a fuzzy logic approach.
The algorithm is based on a second order Runge Kutta time integration.
The algorithm is based on a new loop detection criterion.
First, the algorithm is based on detecting over-represented short words in a sequence and clustering them.
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