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Decomposition is an important tool that is used in many differential systems for solving real engineering problems and improving the stability of a system. It involves breaking down of high-order linear systems into lower-order commutative pairs. Commutativity plays an essential role in mathematics, and its applications are extended in physical science and engineering. This paper explicitly expresses all form of necessary and sufficient conditions for decomposition of any kind of fourth-order linear time-varying system as commutative pairs of two second-order systems. Regarding the nonzero initial conditions, additional requirements are derived in order to satisfy the decomposition process. In this paper, explicit method for reducing fourth-order linear time-varying systems (LTVS) into two second-order commutative pairs is derived and solved. The method points out the effect of disturbance and sensitivity on the systems and also highlights the necessary and sufficient conditions for commutativity of the decomposed systems. The results are illustrated by solving some examples. [ABSTRACT FROM AUTHOR]

The fast QR-decomposition based recursive least-squares (FQRD-RLS) algorithms offer RLS-like convergence and misadjustment at a lower computational cost, and therefore are desirable for implementation on a fixed-point digital signal processor (DSP). Furthermore, the FQRD-RLS algorithms are derived from QR-decomposition based RLS algorithms that are well known for their numerical stability in finite precision. Hence, these algorithms are often assumed numerically stable, although there is no rigorous analysis addressing the stability of such algorithms in finite precision. In this paper, we derive the conditions that guarantee stability of the FQRD-RLS algorithms, and also derive mathematical expressions for the mean-squared quantization error (MSQE) of internal variables of the FQRD-RLS algorithms at steady state. The objective is to quantify the propagation error due to quantization effects. The derived MSQE expressions have been verified by comparisons with fixed-point computer simulations. [ABSTRACT FROM AUTHOR]