๐”– Bobbio Scriptorium
โœฆ   LIBER   โœฆ

Learning and imprinting in stationary and non-stationary environment

โœ Scribed by Pfaffelhuber, E. ;Damle, P. S.

Publisher
Springer-Verlag
Year
1973
Weight
767 KB
Volume
13
Category
Article
ISSN
0023-5946

No coin nor oath required. For personal study only.

๐Ÿ“œ SIMILAR VOLUMES

Learning dynamical systems in a stationa
Learning dynamical systems in a stationary environment
โœ M.C. Campi; P.R. Kumar ๐Ÿ“‚ Article ๐Ÿ“… 1998 ๐Ÿ› Elsevier Science ๐ŸŒ English โš– 119 KB

We consider the problem of learning the input-output relation of a dynamical system from noisy data. Our method rests on the use of a smooth simultaneous estimator which generalizes the standard empirical estimator. In a stationary environment, our algorithm is shown to select a model which exhibits

Molecule imprinting chiral stationary ph
Molecule imprinting chiral stationary phase
โœ Zihui Meng; Liangmo Zhou; Jinfang Wang; Qinghai Wang; Daoqian Zhu ๐Ÿ“‚ Article ๐Ÿ“… 1999 ๐Ÿ› John Wiley and Sons ๐ŸŒ English โš– 58 KB

Molecule imprinting polymers (MIPs) with high chiral selectivity for N a -protected amino acids were synthesized in polar solvent using acrylamide (AM) or combined functional monomer methacrylic acid (MAA) vinyl pyridine (VP). Factors that influence the chiral selectivity of MIPs and mechanisms of t

Reconfigurable combined forecasts in a n
Reconfigurable combined forecasts in a non-stationary inflationary environment
โœ V. Ya. Volkov; Y. U. M. Gladkov ๐Ÿ“‚ Article ๐Ÿ“… 1995 ๐Ÿ› John Wiley and Sons ๐ŸŒ English โš– 412 KB

This paper presents a composite method for non-stationary economic forecasts, incorporating reconfigurable exponential trend extraction and linear combinations of parabolic and spectral estimators for short-term prediction. The method automatically identifies the points of time series misalignment i