# A robust orthogonal algorithm for system identification and time-series analysis

@article{Korenberg2004ARO, title={A robust orthogonal algorithm for system identification and time-series analysis}, author={Michael J. Korenberg}, journal={Biological Cybernetics}, year={2004}, volume={60}, pages={267-276} }

We describe and illustrate methods for obtaining a parsimonious sinusoidal series representation or model of biological time-series data. The methods are also used to identify nonlinear systems with unknown structure. A key aspect is a rapid search for significant terms to include in the model for the system or the time-series. For example, the methods use fast and robust orthogonal searches for significant frequencies in the time-series, and differ from conventional Fourier series analysis in…

## 138 Citations

Applications of fast orthogonal search: Time-series analysis and resolution of signals in noise

- Computer ScienceAnnals of Biomedical Engineering
- 2006

Simulations are provided to demonstrate precise detection of component frequencies and weights in short data records, coping with missing or unequally spaced data, and recovery of signals heavily contaminated with noise.

Iterative Fast Orthogonal Search for Modeling by a Sum of Exponentials or Sinusoids

- Computer ScienceAnnals of Biomedical Engineering
- 2004

A modification of FOS is considered in which iteration of the original procedure is used to further reduce the mean-squared error between model and data, approaching a minimum in the m.s.e.

Fast, Robust Identification of Nonlinear Physiological Systems Using an Implicit Basis Expansion

- Computer ScienceAnnals of Biomedical Engineering
- 2004

Simulations, using a simple nonlinear model of peripheral auditory processing, show the equivalence between the kernels estimated using a direct basis expansion, and those computed using the fast, implicit basis expansion technique which is proposed.

Identification of Linear Time Varying Systems using Basis Pursuit

- Mathematics2005 IEEE Engineering in Medicine and Biology 27th Annual Conference
- 2005

A novel algorithm for identifying time-varying systems is presented that combines a temporal expansion with a term selection step that uses the "least absolute shrinkage and selection operator", or Lasso.

Using the Fast Orthogonal Search with First Term Reselection to Find Subharmonic Terms in Spectral Analysis

- EngineeringAnnals of Biomedical Engineering
- 2004

This paper considers the resolution of subharmonic frequencies using the FOS algorithm and introduces a new criterion for determining the number of non-noise terms in the model, called FOS first-term reselection (FOS-FTR).

A Robust Time-Varying Identification Algorithm Using Basis Functions

- EngineeringAnnals of Biomedical Engineering
- 2004

Comparison via computer simulations of AR models between the proposed method and one of the well-known iterative methods, recursive least squares, shows the greater capability of the new method to track TV parameters.

Parallel cascade identification and kernel estimation for nonlinear systems

- Computer Science, MathematicsAnnals of Biomedical Engineering
- 2006

It is shown that any discrete-time finite-memory nonlinear system having a finite-order Volterra series representation can be exactly represented by a finite number of parallel LN cascade paths.

Compact and accurate linear and nonlinear autoregressive moving average model parameter estimation using Laguerre functions

- Computer ScienceAnnals of Biomedical Engineering
- 2007

Simulation results show better performance of the proposed approach in estimating the system dynamics than LEK in certain cases, and it remains effective in the presence of significant additive measurement noise.

A Novel Fast Orthogonal Search Method for design of functional link networks and their use in system identification

- Computer Science2007 IEEE International Conference on Systems, Man and Cybernetics
- 2007

The proposed architecture is tested on noise-free and noisy nonlinear systems and shown to find sparse models that can approximate the experimented systems with acceptable accuracy.

System Identification Using Optimally Designed Functional Link Networks via a Fast Orthogonal Search Technique

- Computer ScienceJ. Comput.
- 2009

The proposed architecture is tested on noisefree and noisy nonlinear systems and shown to find sparse models that can approximate the experimented systems with acceptable accuracy.

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