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Original Articles

Systematic approach to linear approximation of non-linear stochastic systems Part 1. Asymptotic expansions

Pages 71-91 | Received 22 Dec 1988, Published online: 27 Mar 2007

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Koan-Yuh Chang, Wen-June Wang‡Wen-Jer Chang. (1997) Covariance control for stochastic multivariable systems with hysteresis nonlinearity. International Journal of Systems Science 28:7, pages 731-736.
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D. REARDON & W. E. LEITHEAD. (1990) Statistical linearization: a comparative study. International Journal of Control 52:5, pages 1083-1105.
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W. E. LEITHEAD. (1990) Systematic approach to linear approximation of non-linear stochastic systems Part 2. Filtering hypothesis. International Journal of Control 51:1, pages 93-117.
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Articles from other publishers (6)

Salman Baroumand, Amir Reza Zaman & Mohammad Reza Mahmoudi. (2020) A Covariance Feedback Approach to Covariance Control of Nonlinear Stochastic Systems. Complexity 2020, pages 1-12.
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R. J. ChangS. J. Lin. (2004) Statistical Linearization Model for the Response Prediction of Nonlinear Stochastic Systems Through Information Closure Method. Journal of Vibration and Acoustics 126:3, pages 438-448.
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L. Socha & M. Blachuta. (2000) Application of linearization methods with probability density criteria in control problems. Application of linearization methods with probability density criteria in control problems.
Wen-Jer Chang & Hung-Yuan Chung. (1996) A Covariance Controller Design Incorporating Optimal Estimation for Nonlinear Stochastic Systems. Journal of Dynamic Systems, Measurement, and Control 118:2, pages 346-349.
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A.D. Back & A.C. Tsoi. (1992) Nonlinear system identification using multilayer perceptrons with locally recurrent synaptic structure. Nonlinear system identification using multilayer perceptrons with locally recurrent synaptic structure.
A. Back & A.C. Tsoi. (1992) Internal representation of data in multilayer perceptrons with IIR synapses. Internal representation of data in multilayer perceptrons with IIR synapses.

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