and Applied Analysis 3 Additionally, we assume that there exist positive constants γ and γ such that 0 < γ ≤ 󵄩󵄩󵄩gk 󵄩󵄩󵄩 ≤ γ, ∀k ≥ 1, (21) then we have the following result. Theorem2. Consider the method (2), (8) and (12), where d k is a descent direction. If (21) holds, there exist positive constants ξ 1 , ξ 2 , and ξ 3 such that relations

Conjugate gradient methods are widely used for solving large-scale unconstrained optimization problems, because they do not need the storage of matrices. In this paper, we propose a general form of three-term conjugate gradient methods which always generate a sufficient descent direction. We give a sufficient condition for the global convergence of the proposed general method. Moreover, we pres...

Abstract. In this paper, we present a new stochastic algorithm, namely the stochastic block mirror descent (SBMD) method for solving large-scale nonsmooth and stochastic optimization problems. The basic idea of this algorithm is to incorporate the block-coordinate decomposition and an incremental block averaging scheme into the classic (stochastic) mirror-descent method, in order to significant...

This paper presents a novel fuzzy identification method for dynamic modelling of quadrotor UAVs. The method is based on a special parameterization of the antecedent part of fuzzy systems that results in fuzzy-partitions for antecedents. This antecedent parameter representation method of fuzzy rules ensures upholding of predefined linguistic value ordering and ensures that fuzzy-partitions remai...

In this paper, the self-alignment for stationary strapdown inertial navigation system (SINS) is formulated as an optimization problem, and two gradient descent optimization-based SINS methods (GD1 GD2) are proposed. The highlight lies in that quaternion-based objective functions firstly to solve problem. Different from conventional initial alignment methods, we construct a function using gravit...