This paper concentrates on the recursive identification algorithms for the exponential autoregressive model with moving average noise. Using the decomposition technique, we transform the original identification model into a linear and nonlinear sub-identification model and derive a two-stage least squares extended stochastic gradient algorithm. In order to improve the parameter estimation accuracy, we employ the multi-innovation identification theory and develop a two-stage least squares multi-innovation extended stochastic gradient algorithm. A simulation example is provided to test the effectiveness of the proposed algorithms.

中文翻译：

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一类带色噪声非线性时间序列模型的两阶段递归辨识算法

本文重点研究具有移动平均噪声的指数自回归模型的递归识别算法。利用分解技术，将原始识别模型转化为线性和非线性子识别模型，推导出两阶段最小二乘扩展随机梯度算法。为了提高参数估计精度，我们采用多创新识别理论，开发了一种两阶段最小二乘多创新扩展随机梯度算法。提供了一个仿真例子来测试所提出算法的有效性。