A deterministic interpretation of the Kalman filtering formulas is given, using the principle of least squares estimation. The observed signal and the to-be-estimated signal are modeled as being generated as outputs of a finite-dimensional linear system driven by an input disturbance. Postulating ...
We describe in this paper a novel distributed particle filtering algorithm that performs blind equalization of frequency-selective channels in a setup with... CJ Bordin,MGS Bruno 被引量: 0发表: 2013年 Subspace approaches for blind equalization and identification. In this thesis we address the probl...
Therefore, fungal communities were constrained to be highly dissimilar in a way that could not be explained by niche-based environmental filtering. In the two deeper soil layers, the confidence interval of the central tendency also overlapped with zero, suggesting an important role of neutral ...
Finally, a big factor people forget is any filtering, averaging or discretization that is done. When the sensor changes, it takes time to propagate through the filters based on the filter parameters. And if the discretization is large, you might not even see the change. (If T is at 449,...
We derive then a criterion that makes a balance between discrepancy with data and with the model, and we minimize it by using optimization in functions spaces: our approach is related to the so-called Deterministic Kalman Filtering, but different from the usual statistical Kalman filtering. e ...
A new multi-objective H ∞ /γο problem is considered as a framework for control and filtering problems under multiple deterministic and stochastic distur... DV Balandin,MM Kogan - European Control Conference 被引量: 5发表: 2016年 On the adaptive deterministic block coordinate descent methods wi...
factors varying horizontally, as (i) phylogenetic signal is consistent with Brownian opposed to vertically or temporally, that lead to evolution; (ii) the environment is heterogeneous; changes in the relative influence of environmental and (iii) more than one aspect of organismal filtering. An...
R. (1976) A Comparison between Wiener Filtering, Kalman Filtering, and Deterministic Least Square Estimation. Geophys. Prospecting 24: pp. 141-197A comparison between Wiener filtering, Kalman filtering and deterministic least squares estimation - Berkhout, Zaanen - 1976...
The problem of space time adaptive processing (STAP) is approached in a two step process, filtering and detection. For a certain look direction, the signal strength is estimated by a least squares technique. The receiver scans through all possible look directions and returns estimates of the ...
4(d) shows a spectrum after filtering in which only one peak remains. Figure 4(d) shows the detected fluorescent counts on a silicon single-photon detector as a function of normalized pulse laser power, achieving the total flux \({N}_{total}\) = 1,679,000 counts/s. To deduce ...