The `ssi` algorithm module

This module implements the Stochastic Subspace Identification (SSI) [BPDG99], [MiDo11] algorithm in various forms, tailored for both single and multiple experimental setup scenarios [MiDo11], [DOME13]. It includes classes and methods for conducting data-driven and covariance-driven SSI analyses, with optional uncertainty bounds estimation [DLM13].

Classes:

SSIdat: Implements the Data-Driven SSI algorithm for single setup.
SSIcov: Implements the Covariance-Driven SSI algorithm for single setup.
SSIdat_MS: Extends SSIdat for multi-setup experiments.
SSIcov_MS: Extends SSIdat_MS for covariance-based analysis in multi-setup experiments.

Important

Each class contains methods for executing the SSI algorithm, extracting modal parameters, plotting results, and additional utilities relevant to the specific SSI approach.

Note

Users should be familiar with the concepts of modal analysis and system identification to effectively use this module.

The `ssi` algorithm module

The `SSIdat` class

The `SSIcov` class

The `SSIdat_MS` class

The `SSIcov_MS` class

The ssi algorithm module

The SSIdat class

The SSIcov class

The SSIdat_MS class

The SSIcov_MS class

The `ssi` algorithm module

The `SSIdat` class

The `SSIcov` class

The `SSIdat_MS` class

The `SSIcov_MS` class