wilsonrljr / sysidentpy

A Python Package For System Identification Using NARMAX Models
https://sysidentpy.org
BSD 3-Clause "New" or "Revised" License
390 stars 78 forks source link

How to add a new basis function #106

Open wilsonrljr opened 1 year ago

wilsonrljr commented 1 year ago

SysIdentPy is a comprehensive package for building Nonlinear AutoRegressive Moving Average with eXogenous input (NARMAX) models. One of the powerful features of the package is the ability to use different basis functions for building NARMAX models. However, the documentation currently lacks a detailed explanation of how users can create their own basis functions and use them with the package. This is a highly underrated feature that can significantly improve the modeling capabilities of SysIdentPy. Therefore, the maintainer of SysIdentPy is committed to creating a new example that demonstrates how users can create their own basis functions and use them to build NARMAX models.

The new example will showcase how users can leverage the power of SysIdentPy to create customized basis functions for their specific needs. It will provide a step-by-step guide on how to create a new basis function, implement it in the package, and use it to build NARMAX models. The example will feature detailed explanations and code snippets to help users understand the process of creating and implementing their own basis functions. Additionally, the example will highlight the benefits of using customized basis functions, such as improved accuracy and flexibility in modeling dynamic systems.

The SysIdentPy maintainer, wilsonrljr, will help you in every step. With his guidance, the example will provide users with a comprehensive understanding of how to create and use customized basis functions in SysIdentPy. Furthermore, the new example will contribute to the documentation of the package, making it easier for users to use the package to its full potential.

In summary, the creation of a new example showcasing the creation of customized basis functions will greatly enhance the modeling capabilities of SysIdentPy and empower users to build more accurate and powerful NARMAX models.