Sentence examples for a broad class of problems from inspiring English sources

MAF constitutes a metaphor for a broad class of problems including robotic exploration, navigation, object identification, manipulation and transport.

The BLSA acts as a hardware accelerator for implementing a broad class of problems which are met in a variety of applications such as digital signal processing, computer graphics, graph algorithms, etc.

It is well known that SEP contains a broad class of problems arising in pure and applied mathematics, such as fixed point, minimax and variational inequality, Nash equilibrium, complementarity, and convex optimization problems (see, for example, [1 5] and the references therein).

We formulate an integer program to address this problem, discuss a real-world application in which cross-arc costs are found, and conduct computational experiments on a broad class of problems to analyze how the model performs as network characteristics vary.

However, there is a broad class of problems where this does not apply.

So factoring is thought to be harder and reside in a broader class of problems know as NP for "nondeterministic polynomial".

These results can help researchers in the mathematical sciences who are trying to understand the assumptions underpinning this class of fixed point theorems and apply them to a broader class of problems.

Our goal is to better understand the accuracy and performance characteristics of TRRM on massive scale problems, and to provide community software that facilitates further algorithmic development and potentially its application to a broader class of problems.

The objective of this note is to propose a method for stabilization of structurally fixed modes in expansions of LTI dynamic systems in the scope of overlapping decentralized control design based on the expansion/contraction framework, enabling successful design for a broader class of problems than considered so far.

The problem of finding the Kalai Nash solution to a simple bargaining game belongs to a broad class of equivalent problems in Statistics and Operations Research which includes finding nonparametric maximum likelihood estimators for finite mixture distributions and constructing Bayesian D-optimal designs for one-parameter nonlinear models (South African Statist. J. 32 (1998) 43).

Furthermore, the framework is extended with respect to plastic compressibility thereby providing its applicability to a broad class of engineering problems.