Convergence, consistency, stability and pathwise positivity of balanced Milstein methods for numerical integration of ordinary stochastic differential equations (SDEs) are discussed. This family of numerical methods represents a class of highly efficient linear-implicit schemes which generate mean square converging numerical approximations with qualitative improvements and global rate 1.0 of me...

This paper represents a comparative Study of filter algorithms Least Mean Square (LMS), Normalized Least Mean Square (NLMS) and Recursive Least Square (RLS) by considering a Quasi Orthogonal Space Time Block Code (QOSTBC) encoded Multiple Input Multiple output (MIMO) Code Division Multiple Access (CDMA) system. MIMO-CDMA system has been currently acknowledged as one of the most competitive tech...

Abstract. We study mean-square consistency, stability in the mean-square sense and meansquare convergence of drift-implicit linear multi-step methods with variable step-size for the approximation of the solution of Itô stochastic differential equations. We obtain conditions that depend on the step-size ratios and that ensure mean-square convergence for the special case of adaptive two-step Maru...

Constrained adaptive filtering algorithms inculding constrained least mean square (CLMS), constrained affine projection (CAP) and constrained recursive least squares (CRLS) have been extensively studied in many applications. Most existing constrained adaptive filtering algorithms are developed under mean square error (MSE) criterion, which is an ideal optimality criterion under Gaussian noises....