Precompute

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Precompute

Method of charging interest in which the annual interest is either deducted from the face amount of the loan when the funds are distributed or is added to the total amount and divided into the regular payments.

Precompute

To calculate the annual interest owed on a loan by either deducting the annual interest from the face amount of the loan, or adding the compound interest together and dividing it out equally over 12 monthly periods. This means that the effective interest paid will be higher than the stated amount on the loan. Because of this, most jurisdictions require lending institutions using precomputation to express the interest rate in simple interest terms.
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If not, the management server computes [mathematical expression not reproducible] using master key [MK.sub.Msrv] and sets [mathematical expression not reproducible], where I is an initial ordered index set with [absolute value of I] = t (we assume that the size of the expected response set t is predetermined and publicly known) and [mathematical expression not reproducible] (in our scheme, in order to audit integrity, the client precomputes the expected response set that contains a number of expected responses.
TNR technique precomputes the connections from each potential origin or destination to its access transit nodes and between all pairs of transit nodes [5].
Each node precomputes the routing from itself into a destination prior to receiving the requests and stores this information in its FIT.
Point of view OQRA PQRA Computation Every time a request Precomputes paths from initiated.
Trading even more memory for the acceleration of the computation, one might precompute all entries of the matrix A, which is only feasible for small [N.sub.[pi]] and M; see Example 4.1 in Section 4.
Linear algebra based NFFT: Using a fully discrete approach, one might fix the entries of the diagonal matrix D in (2.5) first and precompute optimised entries for the sparse matrix B to achieve higher accuracy [30, 31].
One possibility is to precompute all values [phi]([x.sub.j]-[n.sup.-1][dot encircle]l) for j = 0, ..., M-1 and l [member of] [I.sub.n,m]([x.sub.j]) explicitly.
In contrast, algorithms that perform static cost computations, precompute relative costs, and store differential costs for nonterminals.
We next precompute sets of augmented items that are valid for all augmented viable prefixes induced by the same input string.
It partitions a 2D square grid into blocks of equal block size, uses an [A.sup.*] search that expands blocks rather than vertices (by putting blocks onto the open list) and, for every block, precomputes paths from every fringe vertex of the block (that is, every vertex along the border of the block) to every other fringe vertex of the block and stores (them and) their lengths in a lookup table to speed up the [A.sup.*] search.
For the former, an indirect approach that precomputes the knots instead of optimizing them is applied.
Matt Bishop's fast version of crypt( ) [1] does all of these things and also precomputes even more functions, yielding twice the performance of the worm's algorithm but requiring nearly 200 KB of initialized data as opposed to the 6 KB used by the worm and the less than 2 KB used by the normal crypt( ).