CAPTAIN

Computer-Aided Program for Time-series Analysis and Identification of Noisy Systems (CAPTAIN) Toolbox. This Website is intended primarily to support the CAPTAIN Toolbox for Matlab, which provides access to novel, mainly recursive, algorithms for various important aspects of identification, estimation, nonstationary time series analysis and signal processing, adaptive forecasting and automatic control system design. These have been developed between 1981 and the present at Lancaster University, UK, based on research carried out by Peter Young with colleagues at Lancaster, the Australian National University, Canberra, Australia (1975-1981) and the University of Cambridge, UK (1965-1975).


References in zbMATH (referenced in 35 articles , 1 standard article )

Showing results 1 to 20 of 35.
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  1. Alegria, Elvis Jara; Giesbrecht, Mateus; Bottura, Celso Pascoli: Causal regression for online estimation of highly nonlinear parametrically varying models (2021)
  2. Wei, Baolei; Xie, Naiming: Parameter estimation for grey system models: a nonlinear least squares perspective (2021)
  3. Pan, Siqi; González, Rodrigo A.; Welsh, James S.; Rojas, Cristian R.: Consistency analysis of the simplified refined instrumental variable method for continuous-time systems (2020)
  4. Pan, Siqi; Welsh, James S.; González, Rodrigo A.; Rojas, Cristian R.: Efficiency analysis of the simplified refined instrumental variable method for continuous-time systems (2020)
  5. Sobolic, Frantisek M.; Aljanaideh, Khaled F.; Bernstein, Dennis S.: A numerical investigation of direct and indirect closed-loop architectures for estimating nonminimum-phase zeros (2020)
  6. Young, Peter C.; Janot, A.: Efficient parameterisation of nonlinear system models: a comment on Nöel and Schoukens (2018) (2020)
  7. Pascu, Valentin; Garnier, Hugues; Ljung, Lennart; Janot, Alexandre: Benchmark problems for continuous-time model identification: design aspects, results and perspectives (2019)
  8. Wang, Xiaolong; Jiang, Yao-Lin: An efficient hybrid reduction method for time-delay systems using Hermite expansions (2019)
  9. Wilson, Emma D.; Clairon, Quentin; Henderson, Robin; Taylor, C. James: Robustness evaluation and robust design for proportional-integral-plus control (2019)
  10. Brunot, Mathieu; Janot, Alexandre; Young, Peter C.; Carrillo, Francisco: An instrumental variable method for robot identification based on time variable parameter estimation. (2018)
  11. Chen, Fengwei; Zhuan, Xiangtao; Garnier, Hugues; Gilson, Marion: Issues in separable identification of continuous-time models with time-delay (2018)
  12. Marco Villegas; Diego Pedregal: SSpace: A Toolbox for State Space Modeling (2018) not zbMATH
  13. Chen, Fengwei; Gilson, Marion; Garnier, Hugues; Liu, Tao: Robust time-domain output error method for identifying continuous-time systems with time delay (2017)
  14. Ouakasse, Abdelhamid; Mélard, Guy: A new recursive estimation method for single input single output models (2017)
  15. Marsili-Libelli, Stefano: Environmental systems analysis with MATLAB (2016) ioport
  16. Garnier, Hugues: Direct continuous-time approaches to system identification. Overview and benefits for practical applications (2015)
  17. He, Fei; Wei, Hua-Liang; Billings, Stephen A.: Identification and frequency domain analysis of non-stationary and nonlinear systems using time-varying NARMAX models (2015)
  18. Mehrabi, Hamid; Voosoghi, Behzad: Recursive moving least squares (2015)
  19. Young, Peter C.: Refined instrumental variable estimation: maximum likelihood optimization of a unified Box-Jenkins model (2015)
  20. Padilla, Arturo; Yuz, Juan I.; Herzer, Benjamin: Continuous-time system identification of the steering dynamics of a ship on a river (2014)

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