Due to the nonconvex problem of the objective function, we could not employ the

convex optimization algorithm to obtain the optimal sensing time directly.

Therefore, the solution methods of

convex optimization problem can not be used directly.

For antenna pattern synthesis, the methods are divided into three types: analytical method, swarm intelligence algorithm, and

convex optimization algorithm.

In the low-sparsity approach, the attack vector can be constructed based on the

convex optimization as a sparse term where only few components are nonzeros, which indicates that a small number of sensors need to be controlled.

For more generality, we first consider the following stochastic

convex optimization problem:

One kind of reconstruction algorithm is

convex optimization algorithm [20].

The main contributions of the present study are as follows: (1) we reformulate the projections in the Gerchberg super-resolution algorithm using linear matrix equations, (2) we formulate a

convex optimization problem, in which the reformulated projections and the low-TV/low-rank regularization are represented in a cost function and constraints, (3) we explicitly describe the algorithm for solving the

convex optimization problem with the alternating direction method of multipliers (ADMM), and (4) we present extensive experimental evaluations conducted using the proposed method.

It was this research that led him to create GPkit software, which is designed around the idea of

convex optimization.

In the literature, analog design automation is an active research area, so that a couple of studies, which are

convex optimization based [1]-[3] and utilized from genetic algorithm [4] were developed.

By weighting combination of the nuclear and the L1norms, a convenient

convex optimization problem (principal component pursuit) was demonstrated, under suitable assumptions, to recover the low-rank and sparse components exactly of a given data-matrix (or video for our purposes).

Nedic, "Distributed random projection algorithm for

convex optimization," IEEE Journal on Selected Topics in Signal Processing, vol.