MIMO Volterra Modeling for Nonlinear Communication Channels

SECURING INTERPRETABILITY OF FUZZY MODELS FOR MODELING NONLINEAR MIMO SYSTEMS USING A HYBRID OF EVOLUTIONARY ALGORITHMS

In this study, a Multi-Objective Genetic Algorithm (MOGA) is utilized to extract interpretable and compact fuzzy rule bases for modeling nonlinear Multi-input Multi-output (MIMO) systems. In the process of non- linear system identi cation, structure selection, parameter estimation, model performance and model validation are important objectives. Furthermore, se- curing low-level and high-level ...

Properties of Space MIMO Communication Channels

— This paper discusses the characteristics of a space-to-space multiple-input, multiple-output (MIMO) communication channel that distinguish it from more common terrestrial MIMO communication channels. These characteristics imply that the channel matrices for space communication channels have a particularly simple structure that leads to statistical characteristics that are both predictable and...

Linear multichannel blind equalizers of nonlinear FIR Volterra channels

Truncated Volterra expansions model nonlinear systems encountered with satellite communications, magnetic recording channels, and physiological processes. A general approach for blind deconvolution of single-input multiple-output Volterra finite impulse response (FIR) systems is presented. It is shown that such nonlinear systems can be blindly equalized using only linear FIR filters. The approa...

Modeling of MIMO Mobile-to-Mobile Channels

securing interpretability of fuzzy models for modeling nonlinear mimo systems using a hybrid of evolutionary algorithms

in this study, a multi-objective genetic algorithm (moga) is utilized to extract interpretable and compact fuzzy rule bases for modeling nonlinear multi-input multi-output (mimo) systems. in the process of non- linear system identi cation, structure selection, parameter estimation, model performance and model validation are important objectives. furthermore, se- curing low-level and high-level ...