@article{oai:ir.kagoshima-u.ac.jp:00009358,
 author = {NAKAMORI, Seiichi},
 journal = {鹿児島大学教育学部研究紀要. 自然科学編, Bulletin of the Faculty of Education, Kagoshima University. Natural science},
 month = {},
 note = {This paper proposes an estimation technique in terms of the recursive least-squares (RLS) Wiener filter by applying the wavelet transformation to the state vector generating a signal in linear discrete-time stochastic systems. The RLS Wiener filter uses the factorized covariance information of the signal and the variance of observation noise. Here, it is assumed that the observed value vector consists of subsequent scalar observed values on the time axis. This paper also examines an estimation technique in terms of the RLS Wiener filter by operating an identity matrix trans-formation to the state vector. It is advantageous that the estimation accuracy by the proposed estimation method is superior to the standard RLS Wiener filter and the estimation procedure with the identity transformation matrix.},
 pages = {47--59},
 title = {Estimation Technique Using Covariance Information with Relation to Wavelet Transformation in Linear Discrete Stochastic Systems},
 volume = {54},
 year = {2003}
}