Weighted maximum likelihood autoregressive and moving average spectrum modeling

机译：加权最大似然自回归和移动平均频谱建模

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We propose new algorithms for estimating autoregressive (AR), moving average (MA), and ARM A models in the spectral domain. These algorithms are derived from a maximum likelihood approach, where spectral weights are introduced in order to selectively enha

机译：我们提出了用于在频谱域中估计自回归（AR），移动平均（MA）和ARM A模型的新算法。这些算法源自最大似然方法，其中引入了频谱权重以选择性地增强

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《Personal, Indoor and Mobile Radio Communications,2005 IEEE 16th International Symposium on》|2008年|P.3761-3764|共4页
会议地点 Las Vegas,NV
作者
Badeau; R.; David; B.;
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autoregressive moving average processes; maximum likelihood estimation; speech processing; ARMA modeling; harmonic signals; moving average spectrum modeling; spectral envelope; speech processing; weighted maximum likelihood autoregressive modeling; Autoregressive;

机译：自回归移动平均过程；最大似然估计；语音处理； ARMA建模；谐波信号；移动平均频谱建模；频谱包络语音处理；加权最大似然自回归建模；自回归;

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1. Data filtering based multi-innovation extended gradient method for controlled autoregressive autoregressive moving average systems using the maximum likelihood principle [J] . Feiyan Chen, Feng Ding, Ahmed Alsaedi, Mathematics and computers in simulation . 2017,第feba期

机译：基于最大似然原理的受控自回归自回归移动平均系统的基于数据过滤的多创新扩展梯度方法
2. The filtering-based maximum likelihood iterative estimation algorithms for a special class of nonlinear systems with autoregressive moving average noise using the hierarchical identification principle [J] . Li Meihang, Liu Ximei, Ding Feng International Journal of Adaptive Control and Signal Processing . 2019,第7期

机译：基于分级识别原理的自回归移动平均噪声的一类特殊非线性系统基于滤波的最大似然迭代估计算法
3. The filtering-based maximum likelihood iterative estimation algorithms for a special class of nonlinear systems with autoregressive moving average noise using the hierarchical identification principle [J] . Li Meihang, Liu Ximei, Ding Feng International Journal of Adaptive Control and Signal Processing . 2019,第7期

机译：基于滤波的最大似然迭代估计估计算法，具有分层识别原理的自动增加移动平均噪声的特殊类非线性系统
4. Weighted maximum likelihood autoregressive and moving average spectrum modeling [C] . Badeau R., David B. IEEE International Conference on Acoustics, Speech and Signal Processing . 2008

机译：加权最大似然自回归和移动平均频谱建模
5. AUTOREGRESSIVE MOVING-AVERAGE (ARMA) MODEL IDENTIFICATION FOR DEGENERATE TIME SERIES WITH APPLICATION TO MANEUVERING TARGET TRACKING (STOCHASTIC MODELING, KALMAN FILTER). [D] . SPEAKMAN, NORMAN OWEN. 1985

机译：退化时间序列的自动回归平均（ARMA）模型识别，应用于机动目标跟踪（随机建模，卡尔曼滤波器）。
6. Assessment of autoregressive integrated moving average (ARIMA), generalized linear autoregressive moving average (GLARMA), and random forest (RF) time series regression models for predicting influenza A virus frequency in swine in Ontario, Canada [O] . Tatiana Petukhova, Davor Ojkic, Beverly McEwen, 2012

机译：评估加拿大安大略省猪甲型流感病毒频率的自回归综合移动平均值（ARIMA），广义线性自回归移动平均值（GLARMA）和随机森林（RF）时间序列回归模型
7. Computational aspects of maximum likelihood estimation of autoregressive fractionally integrated moving average models [O] . Jurgen A. Doornik, Marius Ooms 2003

机译：自回归分数综合移动平均模型的最大似然估计的计算方面
8. Maximum Likelihood Estimation of the Autoregressive Coefficients and Moving Average Covariances of Vector Autoregressive Moving Average Models. [R] . Ahrabi, F. 1979

机译：向量自回归滑动平均模型的自回归系数和移动平均协方差的极大似然估计。

Weighted maximum likelihood autoregressive and moving average spectrum modeling

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