Since λ v(h) and λ d(h) vary over the day, the state probabilities will also be time varying functions, denoted as P n,m (h).
The short cytoplasmic tails of the CD11 molecules vary in length and sequence, and the differences observed are likely to be crucial for their varying functions, and/or intracellular signaling properties.
We believe it involves the learning of highly varying functions, in a mathematical sense.
Government agencies would simply be able to use two separate systems for varying functions, with the non-Internet system employed by federal agencies for the most essential needs requiring the greatest security.
In this study, the faults affecting the system behavior are considered as time varying functions modeled by exponential functions or first order polynomials.
As the functions considered in our treatment are slowly varying functions of r, the equations presented here are convenient for practical calculations.
A particular family of mappings constructed in this way is tested on a variety of rapidly varying functions similar to those occurring in applications.
A general strategy is introduced whereby mappings are adaptively constructed which map specified classes of rapidly varying functions into low order polynomials.
The non-stationary system parameters, which may include masses, restoring forces, material properties or damping, are considered to be slowly varying functions of time.
The nonstationary system parameters, which may include masses, restoring forces or damping, are considered to be slowly varying functions of time.
We bring forward two types of arguments which convey the message that many currently popular machine learning approaches to learning flexible functions have fundamental limitations that render them inappropriate for learning highly varying functions.
