- Referenced in 493 articles
- optimization algorithms. Chapter 7 introduces implicit filtering, a technique due to the author ... group. Implicit filtering methods use finite difference approximations of the gradient, which are adjusted...
- Referenced in 269 articles
- iteration, the author applies a polynomial filter to the Arnoldi (Lanczos) vector on each iteration...
- Referenced in 162 articles
- EnKF-The Ensemble Kalman Filter The EnKF is a sophisticated sequental data assimilation method ... Meteorological Centers. See the article ”Ensemble Kalman Filters Bring Weather Models Up to Date...
- Referenced in 136 articles
- Implicit application of polynomial filters in a k-step Arnoldi method. The author describes ... iteration, the author applies a polynomial filter to the Arnoldi (Lanczos) vector on each iteration...
- Referenced in 107 articles
- system study Signal Processing: Visualize, analyze and filter signals in time and frequency domains. Application...
- Referenced in 63 articles
- makes sense to completely reconsider the filter design problem (as opposed to just re-using ... orthogonal wavelet filters in a redundant representation, as is done in cycle-spinning or undecimated...
- Referenced in 54 articles
- globally convergent primal-dual interior-point filter method for nonlinear programming The paper proposes ... algorithm which uses the filter technique of Fletcher and Leyffer to globalize the primal-dual ... region type parameter. Each entry in the filter is a pair of coordinates: one resulting...
- Referenced in 61 articles
- termination techniques include: approximated dependency graph, argument filtering, bounds, dependency pair method, Knuth-Bendix order...
- Referenced in 42 articles
- Eigentaste: A constant time collaborative filtering algorithm. Eigentaste is a collaborative filtering algorithm that uses...
- Referenced in 51 articles
- Sequential Quadratic Programming solver with a “filter” to promote global convergence. The solver runs with...
- Referenced in 49 articles
- landmarks present in real environments. Kalman filter-based algorithms, for example, require time quadratic...
- Referenced in 49 articles
- moving average models by means of Kalman filtering...
- Referenced in 47 articles
- general form is derived from control and filtering problems for systems in generalized (or implicit...
- Referenced in 43 articles
- space form. Basic functions are available for filtering, moment smoothing and simulation smoothing. Ready...
- Referenced in 17 articles
- Implicit filtering is a way to solve bound-constrained optimization problems for which derivative information ... function and its higher derivatives, implicit filtering builds upon coordinate search and then interpolates ... approximation of the gradient. Implicit Filtering describes the algorithm, its convergence theory...
- Referenced in 18 articles
- Sequential Importance Resampling and Annealed Particle Filtering. In the context of this baseline algorithm ... laboratory environment, where initialization is available, Bayesian filtering tends to perform well. The datasets...
- Referenced in 23 articles
- separate technique that applies a band-pass filter to the energy in each frequency subband...
- Referenced in 14 articles
- power of 2. Alternative marix- and vector-filter implementations of alternative truncated, circulant, and extended ... versions are discussed. Matrix- and vector-filter implementations yield identical results and enhance, respectively, didactic...
- Referenced in 11 articles
- Dynamic Linear Models Maximum likelihood, Kalman filtering and smoothing, and Bayesian analysis of Normal linear ... models and state space models, the Kalman filter for estimation and forecasting in dynamic linear ... dynamic linear models, state estimation and forecasting, filtering and the Kalman filter, and some specialized...
- Referenced in 19 articles
- sparsified matrix. ParaSails also uses a post-filtering technique to reduce the cost of applying...