Establishment of Nonlinear ARMA Model for Non-Gaussian Stochastic Process and Its Application to Time Series Data of Road Traffic Noise (Special Section on Information Theory and Its Applications)
スポンサーリンク
概要
- 論文の詳細を見る
In the actual acoustic environment, the stochastic process exhibits various non-Gaussian distribution forms, and there exist potentially various nonlinear correlations in addition to the linear correlation between time series. In this study, a nonlinear ARMA model is proposed, based on the Bayes' theorem, where no artificially pre-established regression function model is assumed between time series, while reflecting hierarchically all of those various correlation informations. The proposed method is applied to the actual data of road traffic noise and its practical usefulness is verified.
- 社団法人電子情報通信学会の論文
- 1994-08-25
著者
-
Ikuta Akira
Faculty Of Engineering Kinki University
-
Ohta Mitsuo
Faculty Of Engineering Kinki University
-
Ohta Mitsuo
Faculty Of Engineering Hiroshima University
-
Ohta Mitsuo
Faculty of Eng.,Kinki Univ.Umenobe 1,Takaya,Higashi-Hiroshima,729-2116 Japan
関連論文
- A new trial to estimate the noise propagation characteristics of a traffic noise system
- A mew estimation method of noise evaluation index, L_<eq>, by use of the statistical information on the arbitrary type noise level fluctuation
- An Improved Stochastic Restoration Method Using Digital Filter for Medical X-Ray Images Contaminated by Quantum Mottles
- Preparation of p-Type CdS Thin Film by Laser Ablation
- A functional prediction method on the response probability for linear sound systems on energy scale based on the stochastic information and its application to room acoustics
- A State Estimation Method in Acoustic Environment Based on Fuzzy Observation Contamihated by Background Noise-Utilization of Inverse Probability and Digital Filter
- Establishment of Nonlinear ARMA Model for Non-Gaussian Stochastic Process and Its Application to Time Series Data of Road Traffic Noise (Special Section on Information Theory and Its Applications)
- Some New Type Regression Analysis Methods for Acoustic Environmental System Based on the Introduction of Multiplicative Noise
- Stochastic Signal Processing for Incomplete Observations under the Amplitude Limitations in Indoor and Outdoor Sound Environments Based on Regression Analysis (Special Section on Information Theory and Its Applications)
- A Stochastic Evaluation Theory of Arbitrary Acoustic System Response and Its Application to Various Type Sound Insulation Systems : Equivalence Transformation Toward the Standard Hermite Expansion Type Probability Expression
- A Stochastic Evaluation Method on the Elimination of Background Sound Noises with Aid of Vibration Information and Its Experiment (Special Section on Advanced Signal Processing Techniques for Analysis of Acoustical and Vibrational Signals)
- A Signal Information Processing for the Stochastic Response Prediction of Double-Wall Type Sound Insulation System
- A Probabilistic Evaluation Method of Discriminating System Characteristics from Background Noise by Use of Multi-Output Observations in a Complicated Sound Environment (Special Section on Digital Signal Processing)
- Generalization of Rician distribution for speckle pattern in ultrasound image processing and random flights problem in Shannon's signal space
- A Probabilistic Evaluation Method of Output Response Based on the Extended Regression Analysis Method for Sound Insulation Systems with Roughly Observed Data (Special Section on Digital Signal Processing)
- 量子化レベルの粗観測デ-タに基づく確率分布の一高精度推定法と環境騒音計測への適用
- A practical probabilistic evaluation method for the noise reduction effect of sound absorbing materials
- A prediction for level probability of random noise with quantized level (theory and experiment)
- An evaluation method of L_<eq> for noise fluctuation of non-Gaussian and nonstationary types
- A statistical analysis for estimating the noise level probability distribution from L_<eq> and L_x noise levels
- A practical determination of an optimal order of state probability distribution expression with hierarchical expansion form observed in the actual sound and vibration environments
- A fundamental consideration on the stochastic blind signal separation based on the rotational transformation and a measure of statistical independency