ARMA model order estimation based on the SVD of the data matrix.
スポンサーリンク
概要
- 論文の詳細を見る
In many fields of digital signal processing such as acoustic echo path estimation, modelingof the unknown systems has been required. Since the selection of the model order isvery important in such modeling, various methods of selection have already been proposed.However, the order estimation of the ARMA model is very difficult due to thenoise of the observed data, even in the case of known input data. Since, in the presenceof additive noise in the output data, traditional methods fail to select a reasonable order, we propose a new algorithm to overcome this problem. Our proposed algorithm forARMA model order selection is based on singular value decomposition (SVD) and newcriteria of threshold values for the smallest singular value of the noisy data matrix. Inthe simulation, we show that our proposed algorithm is very effective for obtaining anappropriate rank of the noisy data matrix. We also show the good performance of our algorithm for practical estimation of the room acoustic transfer function.
- 一般社団法人 日本音響学会の論文
一般社団法人 日本音響学会 | 論文
- How large is the individual difference in hearing sensitivity?: Establishment of ISO 28961 on the statistical distribution of hearing thresholds of otologically normal young persons
- Applying generation process model constraint to fundamental frequency contours generated by hidden-Markov-model-based speech synthesis
- Vocal cord vibration in the production of consonants. Observation by means of high-speed digital imaging using a fiberscope.:Observation by means of high-speed digital imaging using a fiberscope
- The early reflections of the impulse response in an auditorium.
- Multiple reflections between rigid plane panels.