Sentence examples for descent strategy from inspiring English sources

The Block Leaky Least Mean Square (BLLMS) algorithm, being the solution of the steepest descent strategy for minimizing the mean squared error in a complete signal occurrence, is shown to be steady-state unbiased and with a lower variance than the LMS algorithm.

This creates a gradient, an exploitable structure, which allows future work to develop a gradient descent strategy, which would be an improvement over current hill climbing techniques.

Considering the block structure of b, we apply a block-wise descent strategy [ 14], i.e., cyclically optimize one block of parameters, b j, at a time.

The MLP learning problem is usually tackled by the backpropagation (BP) algorithm [34], which applies a stochastic gradient-descent strategy over the weight space.

A population based multi-objective optimization (MOO) algorithm based on a steepest descent like strategy with proper orthogonal decomposition (POD) is used to search robust Pareto solutions.

Canadian-born, but of Greek descent, his strategy appears to be targeted at winning over exactly the group that talking heads say it should be alienating: Immigrants.

The data set was processed with the novel TTV reconstruction method using the steepest descent optimization strategy described in Eq. 6.

In practice, the TTV reconstructed 3D volumetric image S c can be computed via a steepest descent optimization strategy [ 42], where the steepest descent for minimizing the tensor energy functional E(s) can be expressed as (5) ∂ S ∂ t = div (K * (1 λ 1 ϕ 1 ⋅ ϕ 1 T + 1 λ 2 ϕ 2 ⋅ ϕ 2 T + 1 λ 3 ϕ 3 ⋅ ϕ 3 T ) ∇ S ).

Based on an analysis of well-known metaheuristic algorithms, several new global optimization algorithms based on Tabu Search TSS) were developed in our group [2, 3], which are using a steepest descent – modest ascent strategy.

PropClust adopts a block descent (or ascent) strategy that alternates cluster re-assignment and parameter re-estimation until clusters stabilize.

Combining block coordinate descent and majorization minimization strategies, we derive a new re-weighed algorithm to solve the problem by transforming the subproblems in every iteration into convex ones.