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The most involved step in the prediction procedure is finding the eigendecomposition of A∗.
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The second challenge is finding a procedure for learning a mapping from state activations to state posterior probabilities that provides the same excellent generalization to unseen conditions that has been found with sparse coding.
A lack of written guidelines for the extubation procedure is another finding for a future educational programme.
A design procedure is proposed for finding all the time-optimal set stabilizers.
Second, a fuzzy evaluation procedure is developed for finding reference designs with similar technological specifications.
This procedure is based on finding the frequencies of magnitude characteristic extreme values in closed form.
A finite element analysis procedure is developed for finding the final geometric configuration from an initial configuration.
A procedure is presented for finding a number of the smallest eigenvalues and their associated eigenvectors of large sparse Hermitian matrices.
The first part of the calculation procedure is concerned with finding the sound reflection and transmission coefficients for a plane wave of given frequency and direction.
Specifically, the procedure is applied to finding the subspace spanned by the first m singular components of an n-dimensional dataset.
Fermat's and Hamilton's principles are but two examples out of many whereby a procedure is established for finding the correct solution to a problem by discovering under what conditions a certain function takes an extremal value.
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CEO of Professional Science Editing for Scientists @ prosciediting.com