Примери коришћења Each iteration на Енглеском и њихови преводи на Српски
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Each iteration approximately doubles the number of correct digits.
Its initial value is 0 and after each iteration it increases by 1.
Instructions at addresses 26, 27 and 28 decrement this value by 1 in each iteration.
At each iteration, design modifications are made and new functional capabilities are added.
While the array a initially has n items,we remove one array item in each iteration.
For example, consider a loop that on each iteration applies a hundred operations, and runs for a thousand iterations. .
Coordinate descent does a line search along one coordinate direction at the current point in each iteration.
After each iteration, one less element the last one is needed to be compared until there are no more elements left to be compared.
The crossbar learning algorithm,written in mathematical pseudocode in the paper, in each iteration performs the following computation.
During each iteration, the first remaining element of the input is only compared with the right-most element of the sorted subsection of the array.
A loop invariant is an assertion which must be true before the first loop iteration andremain true after each iteration.
The assessed prefix length doubles in each iteration of the algorithm until a prefix is unique and provides the rank of the associated suffix.
Rather it uses a simple performance-oriented method, based on the update of the search dimensionality ratio(SDR) parameter at each iteration.
The assessed prefix length doubles in each iteration of the algorithm until a prefix is unique and provides the rank of the associated suffix.
A tetrix constructed from an initial tetrahedron of side-length L has the property that the total surface area remains constant with each iteration.
During each iteration the algorithm chooses a classifier of a single feature(features that can be shared by more categories shall be encouraged).
This is a quadratically convergent algorithm,which means that the number of correct digits of the approximation roughly doubles with each iteration.
And work they did, with each iteration trying to address the criticisms of previous performances, all set to Tchaikovsky's amazing score.
The total enclosed volume, however,is geometrically decreasing(factor of 0.5) with each iteration and asymptotically approaches 0 as the number of iterations increases.
Monotonicity ensures that on each iteration the value will either stay the same or will grow larger, while finite height ensures that it cannot grow indefinitely.
In this way, as the number of vertices withcorrect distance values grows, the number whose outgoing edges that need to be relaxed in each iteration shrinks, leading to a constant-factor savings in time for dense graphs.
The area remaining after each iteration is clearly 3/4 of the area from the previous iteration, and an infinite number of iterations results in zero.[9].
Furthermore, if the increment of X occurs by repeated addition,accumulated rounding errors may mean that the value of X in each iteration can differ quite significantly from the expected sequence 0.1, 0.2, 0.3,…, 1.0.
The area remaining after each iteration is 3/4 of the area from the previous iteration, and an infinite number of iterations results in an area approaching zero.
Repeating this iterative process a large number of times,selecting the vertex at random on each iteration, and throwing out the first few points in the sequence, will often(but not always) produce a fractal shape.
At each iteration, hill climbing will adjust a single element in x{\displaystyle\mathbf{x}} and determine whether the change improves the value of f( x){\displaystyle f(\mathbf{x})}.
For example, in binary search, the size of the problem to be solved is halved with each iteration, and therefore roughly log2 n iterations are needed to obtain a problem of size 1, which is solved easily in constant time.
Each iteration of the main loop of the algorithm, after the first one, adds at least two edges to the set of edges whose relaxed distances match the correct shortest path distances: one from Ef and one from Eb.
The Fortran code below can be auto-parallelized by a compiler because each iteration is independent of the others, and the final result of array z will be correct regardless of the execution order of the other iterations. .
In each iteration of the greedy algorithm the tentative solution is added the set which contains the maximum residual weight of elements divided by the residual cost of these elements along with the residual cost of the set.