A simple model characterizing the convergence properties of an adaptive digital lattice filter using gradient algorithms has been reported [ 11. This model is extended to the least mean square (LMS) lattice joint process estimator [SI, and to the least squares (LS) lattice and “fast” Kalman algorithms [9] -[16]. The models in each case are compared with computer simulation. The single-stage LMS...

Scanning movements are added to a tracking antenna's trajectory to estimate the true spacecraft position. T h e scanning movements are composed of the harmonic axial movements of an antenna. This motion produces power variations of t he received signal, which are used to estimate the spacecraft's position. Three different scanning patterns (conical scan, Lissajous scan, and rosette s can ) are ...

A QR-decomposition based algorithm is presented for unbiased, equation error adaptive IIR filtering. The algorithm is based on casting the adaptive IIR filtering in a mixed Least Squares Total Least Squares (LS-TLS) framework. This formulation is shown to be equivalent to the minimization of the mean-square equation error subject to a unit norm constraint on the denominator parameter vector. An...

Least squares (LS) estimation has been extensively used for parameter identification and model-based diagnosis. However, if ill-conditioning is present, the LS estimation approach tends to generate imprecise results and thus impacts the diagnostic performance. In this paper, an adjusted least squares approach is proposed to deal with the illconditioning problem in the diagnosis of compliant she...

as: Mang ng Saud Abstract Recently, many realistic spatially and temporally clustered channel models were developed to be applied in the simulations of multiple input multiple output (MIMO) systems. IEEE 802.11n standard channel model includes spatio-temporal fading correlation effects and accounts for six various real propagation profiles. These profiles represent variety of propagation scenar...

The aim of this study is to develop the Bayesian Least Squares Support Vector Machine (LS-SVM) classifiers, for preoperatively predicting the malignancy of ovarian tumors. We describe how to perform parameter estimation, input variable selection for LS-SVM within the evidence framework. The issue of computing the posterior class probability for risk minimization decision making is addressed. Th...

In this article, we introduce a new extension of the power Lomax (PLo) model by combining type II exponentiated half-logistic class statistical models and PLo model. The suggested called half-logistic-PLo (TIIEHL-PLo) However, TIIEHL-PLo is more flexible applicable than some extensions THE model, especially those in environmental medical fields. Some general properties are computed. Six differe...

This paper presents a simple DFT-based golden section searching algorithm (DGSSA) for the single tone frequency estimation. Because of truncation and discreteness in signal samples, Fast Fourier Transform (FFT) and Discrete Fourier Transform (DFT) are inevitable to cause the spectrum leakage and fence effect which lead to a low estimation accuracy. This method can improve the estimation accurac...

The estimation of average-power dissipation of a circuit through exhaustive simulation is impractical due to the large number of primary inputs and their combinations. In this brief, two algorithms based on least square estimation are proposed for determining the average power dissipation in complementary metal–oxide–semiconductor (CMOS) circuits. Least square estimation converges faster by att...

Neugebauer modeling plays an important role in obtaining end-to-end device characterization profiles for halftone color printer calibration. This paper proposes total least square (TLS) regression methods to estimate the parameters of various Neugebauer models. Compared to the traditional least squares (LS) based methods, the TLS approach is physically more appropriate for the printer modeling ...