Sentence examples for update the variable from inspiring English sources

We update the variable x, z, y at the tth iteration by solving subproblems (12), (15), and (21), and update u 1, u 2 by (23) iteratively.

You do not need to initialize or update the variable, though you can do that in the main body of the loop.

(c) Select from among which satisfies (d) Update the variable weights by 4. Update l = l + 1 and repeat Step 3 until a stopping criterion is satisfied or the number of iterations attains M. As a stopping criterion, we calculate the sum of the values of model selection criterion for j = 1,..., m: (19) The algorithm stops if SMC(l ) (λ2) - SMC(l - 1)(λ2) > 0 (l = 2, 3,..., M) holds.

On the other hand, the solution of variable W is only related to the variable F. Therefore, we can update the variables F, Z, S and E, iteratively, by fixing the other variables fixed.

Use the same instructions as stated in ST2; update the variables α, β, γ, and θ, and at the next clock cycle, the process passes unconditionally to the next state.

Note that the updated value of u is used to update the variables x and y.

The event AddAuthorisation to add the RBAC policy to the system by updating the variable allowed.

role,mapsto, items in allowed Rightarrow &(exists source. items,mapsto, source in belong_to) end{aligned} The event AddAuthorisation to add the RBAC policy to the system by updating the variable allowed.

The event AddDataItemsToSource is refined to classify each data item by updating the variable classified as follows: begin{aligned} {mathbf{grd1:}}&quad i in {mathbb{P}}1 DATA_ITEM) {mathbf{grd2:}}&quad j in CLASSIFICATION {mathbf{grd3:}}&quad i notin dom(classified) {mathbf{act1:}}&quad classified:= classified cup { i,mapsto, j } end{aligned}.

Update the plan once you've got firm figures: By going back to the business plan and updating the variables in your financial models and forecasts with real time figures you will have a far clearer idea of where your business is - and most importantly where it is going.

The main characteristics of ADMM are that it in full exploits the separable structure of problem (1), and that it updates the variables (x_{1}), (x_{2}), λ in an alternating order by solving a series of low-dimensional sub-problems with only one unknown variable.