Model reduction methods from diverse fields-including control, statistical mechanics and
economics-aimed at systems that can be represented by Markov chains, are discussed in …

This paper addresses an image prediction problem focused on images with no identifiable
objects. In it, we present several approaches to predict the next image of a given sequence …

This paper introduces a new method for reducing large directed graphs to simpler graphs
with fewer nodes. The reduction is carried out through node and edge aggregation, where …

A comparative study based on combined special projections and important frequency-
weighted model order reduction (MOR) algorithms to compute optimal approximants for full …

Interval systems are a class of dynamic processes devoted to robotics, computer science,
estimation and observer theories, and control engineering. In control applications, the main …

Using a new model order reduction based on frequency selection and optimal genetic
algorithm, a second order speech model is calculated. In our algorithm, the modeling …

This paper presents a new approach for modeling linear time invariant (LTI) discrete
systems with fast and slow dynamics from its input-output data. The new method selects …

Analysis, prediction and control of parametric generative models for stochastic processes
arise in numerous applications, such as in biology, telecommunications, geography …

The objective of this paper is to present an overall approach to forecasting the future position
of the moving objects of an image sequence after processing the images previous to it. The …

Using a new model order reduction based on frequency selection and optimal genetic
algorithm, a very low order speech model is presented. In our approach, the modeling …