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机译:迭代前向正交最小二乘回归算法用于非持久性激励非线性系统的辨识
Department of Automatic Control and Systems Engineering, The University of Sheffield, Mappin Street, Sheffield, S1 3JD, UK;
Department of Automatic Control and Systems Engineering, and INSIGNEO Institute for in silico Medicine, The University of Sheffield, Mappin Street, Sheffield, S1 3JD, UK;
Department of Automatic Control and Systems Engineering, The University of Sheffield, Mappin Street, Sheffield, S1 3JD, UK;
Department of Automatic Control and Systems Engineering, The University of Sheffield, Mappin Street, Sheffield, S1 3JD, UK;
model structure detection; nonlinear system identification; non-persistence; orthogonal forward regression; OFR; iterative learning algorithm; OFR algorithm; iOFR algorithm;
机译:基于噪声回归器的系统建模的改进正交正向回归最小二乘算法
机译:基于噪声回归器的系统建模的改进正交正向回归最小二乘算法
机译:用迭代正交正向回归算法识别动态参数模型
机译:非线性时变系统神经识别的正交迭代学习最小二乘法。
机译:使用Hammerstein /非线性反馈模型对二次约束最小二乘辨识和非线性系统辨识。
机译:基于最小二乘支持向量回归的非线性自适应波束成形算法
机译:利用迭代正交最小二乘回归算法识别非持续激励非线性系统
机译:利用正回归正交估计器识别mImO(多输入多输出)非线性系统