In many identi cation and tracking problems, an accurate estimate of the measurement noise variance is available. A partially adaptive LMS-type algorithm is developed which can exploit this information while maintaining the simplicity and robustness of LMS. This noise constrained LMS (NCLMS) algorithm is a type of variable step-size LMS algorithm, which is derived by adding constraints to the m...

a total of 260709 monthly test day milk records of 30903 first lactation holstein cows was used to determine the best function to describe the lactation curve. the records were obtained from first lactation holstein of 216 herds from 1988 to 2006 in khorasan province. the functions used in current study were wood’s incomplete gamma function, ali and schaeffer function, and legendre function of ...

In this paper we consider the problem of distributed adaptive estimation in wireless sensor networks for two different observation noise conditions. In the first case, we assume that there are some sensors with high observation noise variance (noisy sensors) in the network. In the second case, different variance for observation noise is assumed among the sensors which is more close to real scen...

Bayesian estimators are defined in terms of the posterior distribution. Typically, this is written as the product of the likelihood function and a prior probability density, both of which are assumed to be known. But in many situations, the prior density is not known, and is difficult to learn from data since one does not have access to uncorrupted samples of the variable being estimated. We sh...

Exploiting the benefits of multiple antenna technologies is strongly conditioned on knowledge of the wireless channel that affects the transmissions. To this end, various channel estimation algorithms have been proposed in the literature for multiple-input multiple-output (MIMO) channels. These algorithms are typically studied from a perspective that does not consider constraints on the energy ...

A simple model of the m-cornered hat estimation problem is set up and solved by the method of maximum likelihood. The method is compared by simulation to a leastsquares method of Barnes and is shown to be inferior to it on the basis of mean square error. A bootstrap method of computing estimator performance is presented.

In this paper, I demonstrate how structural mean models (SMMs) can be used to estimate quantities based on post-treatment variables. SMMs are semiparametric models where the parameters of the model or models correspond to meaningful functions of expected potential outcomes for subjects actually exposed to the treatment. SMMs provide a flexible framework for estimating causal effects with noncom...

Variables used in nonresponse adjustments are sometimes associated with the response outcome and sometimes with survey variables. Both associations are paramount to the reduction of nonresponse bias in survey estimates. We demonstrate that it is only when both are present that adjustments change the point estimate of the mean from the unadjusted mean. We also set out to test whether the relativ...

あらまし 本稿では,OFDM 受信における適応予測繰り返しチャネル推定を提案している.本方式は,繰り返しチャネル推定に適応 予測フィルタを導入して,そのタップ係数を伝搬環境の変化に適応して適応的に更新することに特徴がある.繰り返しチャネル推定の初 回では,周波数多重されているパイロットサブキャリアを用いて1次の内挿と外挿によりチャネル推定し,2 回目以降の繰り返しチャネル推 定では判定帰還,逆変調と適応予測フィルタを用いるチャネル推定を行う.適応予測フィルタのタップ係数の更新には,逆変調によって得 られた瞬時チャネル利得を参照信号とする正規化 LMS アルゴリズムを用いている.計算機シミュレーションにより,周波数選択性フェージ ング環境下でのビット誤り率(BER)特性を評価した.シミュレーション結果より,繰り返しチャネル推定は同じ BER を得るためのパイロットサ ブキャリア数を低減...

An analysis of two LMS-Newton adaptive filtering algorithms with variable convergence factor is presented. The relations of these algorithms with the conventional recursive least-squares algorithm are first addressed. Their performance in stationary and nonstationary environments is then studied and closed-form formulas for the excess mean-square error (MSE) are derived. The paper deals, in add...