Laguerre-volterra model and architecture for MIMO system identification and output prediction

Author

Li, Will X. Y. ; Yao Xin ; Chan, Rosa H. M. ; Dong Song ; Berger, Theodore W. ; Cheung, Ray C. C.

Author_Institution

Dept. of Electr. Eng., City Univ. of Hong Kong, Hong Kong, China

fYear

2014

fDate

26-30 Aug. 2014

Firstpage

4539

Lastpage

4542

Abstract

A generalized mathematical model is proposed for behaviors prediction of biological causal systems with multiple inputs and multiple outputs (MIMO). The system properties are represented by a set of model parameters, which can be derived with random input stimuli probing it. The system calculates predicted outputs based on the estimated parameters and its novel inputs. An efficient hardware architecture is established for this mathematical model and its circuitry has been implemented using the field-programmable gate arrays (FPGAs). This architecture is scalable and its functionality has been validated by using experimental data gathered from real-world measurement.

Keywords

MIMO systems; behavioural sciences computing; biological techniques; biology computing; equivalent circuits; field programmable gate arrays; physiological models; FPGA; Laguerre-volterra model; MIMO system identification; behavior prediction; biological causal systems; circuitry; estimated parameters; field-programmable gate arrays; functionality; generalized mathematical model; hardware architecture; model parameters; multiple inputs and multiple outputs; output prediction; random input stimuli; real-world measurement; system properties; Biological system modeling; Computer architecture; Hardware; Kernel; MIMO; Predictive models; Vectors;

fLanguage

English

Publisher

ieee

Conference_Titel

Engineering in Medicine and Biology Society (EMBC), 2014 36th Annual International Conference of the IEEE

Conference_Location

Chicago, IL

ISSN

1557-170X

Type

conf

DOI

10.1109/EMBC.2014.6944633

Filename

6944633