For many years, various methods for the identification and estimation of parameters in linear, discrete-time transfer functions have been available and implemented in widely available Toolboxes for Matlab. This paper considers a unified Refined Instrumental Variable (RIV) approach to the estimation of discrete and continuous-time transfer functions characterized by a unified operator that can b...

In this paper, forecasting of monthly electricity load using Box-Jenkins methodology and feed forward neural networks is discussed. This study investigates application of neural networks models and the results of neural networks will be compared with those obtained by Box-Jenkins method.

STUDY DESIGN Biomechanical comparison of 5 atlantoaxial posterior arthrodesis techniques. OBJECTIVE To assess the relative value of different posterior wire constructs when one or two transarticular screws are used. SUMMARY OF BACKGROUND DATA A combination of Gallie or Brooks techniques and 2 posterior transarticular screws has been shown to be effective for atlantoaxial arthrodesis. Anatom...

The shape isomers of the 28Si nucleus are derived from Nilsson model calculations combined with quasidynamical SU(3) symmetry considerations, and their possible binary clusterizations are determined. The results are compared with those of other calculations. Concerning the superdeformed state our finding gives support to the new candidate suggested by Jenkins et al. [Phys. Rev. C 86, 064308 (20...

System identification is the process of creating models of dynamic process from inputoutput signals. The aim of system identification can be identified as “ to find a model with adjustable parameters and then to adjust them so that the predicted output matches the measured output”. This paper presents a method of modeling and simulating with system identification to achieve the maximum fitness ...