A CCD Time‐Series Photometer

Fuzzy Prediction of Timeseries

This paper presents an approach to time series extrapolation based on fuzzy control. The standard exponential averaging scheme is innexible in that it gives a xed weight to past history, thus ignoring transient phases in system dynamics. We present a modiication to the scheme where the control parameter of the averaging scheme is dynamically adjusted by a simple fuzzy logic controller. The desi...

Fuzzy Prediction of Timeseries

SRINIVASAN KESHAV CS Division, Department of EECS, University of California a t Berkeley and International Computer Science Institute, Berkeley, CA 94720. keshav0tenet.berkeley.edu This paper presents an approach to time series extrapolation based on fuzzy control. The standard exponential averaging scheme is inflexible in that it gives a fixed weight to past history, thus ignoring transient ph...

A lithium internal-standard flame photometer.

Scalar Wavelet Networks for Timeseries

1 1 2-layer neural networks whose basis functions are scalar wavelets, trained with the quickprop gradient descent algorithm, appear to train more quickly and yield lower prediction errors on the Mackey-Glass chaotic time series than comparable networks of conventional sigmoid units.

Timeseries of Determinisic Dynamic Systems

Starting from Renaissance rationality has dominated in the science. W. G. Leibnitz and I. Newton based foundations to mathematical and physical doctrine of determinism—everything in the nature is defined by few deterministic laws, and thus can be explained (computed) automatically from initial conditions. However, the 20th century made quite serious amendments to the core idea of determinism. I...