This paper deals with the problem of landmark detection for application of Simultaneous Localization and Mapping (SLAM) for agricultural robots. A new method of using a fuzzy rule base for fast evaluation of landmarks based on its measurement error, amount of dynamic nature, need for a landmark and evaluation time has been proposed. The output of the fuzzy system is a multiplier which represent...

Multiscale analysis of univariate time series has appeared in the literature at an ever increasing rate. Here we introduce the multiscale analysis of covariance between two time series using the discrete wavelet transform. The wavelet covariance and wavelet correlation are deened and applied to this problem as an alternative to traditional cross-spectrum analysis. The wavelet covariance is show...

Data assimilation in meteorology seeks to provide a current analysis of the state of the atmosphere to use as initial conditions in a weather forecast. This is achieved by using an estimate of a previous state of the system and merging that with observations of the true state of the system. Ensemble Kalman filtering is one method of data assimilation. Ensemble Kalman filters operate by using an...

The solution to the problem of factorization of the covariance function of a stationary, discrete-time process is obtained by using a Newton-Raphson procedure which converges quadratically in I1 provided the initial iterate is chosen suitably. The existence of a suitable initial iterate is guaranteed by an approximation result. An application to error localization in spectral factorization is s...

Electro- and magnetoencephalography allow for non-invasive investigation of human brain activation and corresponding networks with high temporal resolution. Still, no correct network detection is possible without reliable source localization. In this paper, we examine four different source localization schemes under a common Variational Bayesian framework. A Bayesian approach to the Minimum Nor...

In this paper we consider the problem of error localization of complex DFT codes and the reconstruction of message. A propagator-based subspace algorithm is proposed for error localization of quantized DFT codes. The propagator method requires only linear operations and does not require any eigendecomposition of syndrome covariance matrix as in conventional subspace method such as MUSIC etc. Th...

Identifying acoustic sources in terms of their relative location is an important factor in active noise control. Traditional source localization measurements uses scalar pressure sensors which proved to be less accurate. Nehorai et al. proposed a different approach for source localization using vector natured acoustic intensity sensors. Four-dimensional (4-D) intensity based algorithm and three...

Ensemble Kalman filter techniques are widely used to assimilate observations into dynamical models. The dimension of phase is typically much larger than the number of ensemble members which leads to inaccurate results in the computed covariance matrices. These inaccuracies lead, among others, to spurious long range correlations which can be eliminated by Schur-product-based localization techniq...