Computationally Simple Neural Network Approach to Determine Piecewise-Linear Dynamical Model

Title:

Computationally Simple Neural Network Approach to Determine Piecewise-Linear Dynamical Model

Creator:

Dolezel, P. and Heckenbergerova, J.

Identifier:

https://cdk.lib.cas.cz/client/handle/uuid:a1b68c3c-7a05-4f61-8633-11363c6dd3f9
uuid:a1b68c3c-7a05-4f61-8633-11363c6dd3f9
doi:10.14311/NNW.2017.27.020

Subject:

artificial neural network, momdeling, and nonlinear systems

Type:

model:article and TEXT

Format:

bez média and svazek

Description:

The article introduces a new technique for nonlinear system modeling. This approach, in comparison to its alternatives, is straight and computationally undemanding. The article employs the fact that once a nonlinear problem is modeled by a piecewise-linear model, it can be solved by many efficient techniques. Thus, the result of introduced technique provides a set of linear equations. Each of the equations is valid in some region of state space and together, they approximate the whole nonlinear problem. The technique is comprehensively described and its advantages are demonstrated on an example.

Language:

English

Rights:

http://creativecommons.org/publicdomain/mark/1.0/
policy:public

Source:

Neural network world: international journal on neural and mass-parallel computing and information systems | 2017 Volume:27 | Number:4

Harvested from:

CDK

Metadata only:

false