Many decoding algorithms for brain machine interfaces' (BMIs) estimate hand movement from binned spike rates, which do not fully exploit the resolution contained in spike timing and may exclude rich neural dynamics from the modeling. More recently, an adaptive filtering method based on a Bayesian approach to reconstruct the neural state from the observed spike times has been proposed. However, ...

Chaotic systems are characterized by long-term unpredictability. Existing methods designed to estimate and forecast such systems, such as Extended Kalman filtering (a “sequential” or “incremental” matrix-based approach) and 4Dvar (a “variational” or “batch” vector-based approach), are essentially based on the assumption that Gaussian uncertainty in the initial state, state disturbances, and mea...

Chaotic systems are characterized by long-term unpredictability. Existing methods designed to estimate and forecast such systems, such as Extended Kalman filtering (a “sequential” or “incremental” matrix-based approach) and 4DVar (a “variational” or “batch” vector-based approach), are essentially based on the assumption that Gaussian uncertainty in the initial state, state disturbances, and mea...

We discuss the detection of gravitational-wave backgrounds in the context of Bayesian inference and suggest a practical definition of what it means for a signal to be considered stochastic—namely, that the Bayesian evidence favors a stochastic signal model over a deterministic signal model. A signal can further be classified as Gaussian-stochastic if a Gaussian signal model is favored. In our a...

In this technical note, a geostatistical model was applied to explore the spatial distribution of source rock data in terms total organic carbon weight concentration. The median polish kriging method used approximate “row and column effect” generated array data, order for ordinary methodology be by means residuals. Moreover, sequential Gaussian simulation employed quantify uncertainty estimates...

This paper presents an efficient optimization procedure for solving the reliability-based design (RBDO) problem of structures under aleatory uncertainty in material properties and external loads. To reduce number structural analysis calls during process, mixture models Gaussian processes (MGPs) are constructed prediction responses. The MGP is used to expand application process model (GPM) large...

Truncated Gaussian Simulation (TGS) is a well-known method to generate realizations of the ore domains located in a spatial sequence. In geostatistical framework geological domains are normally utilized for stationary assumption. The ability to measure the uncertainty in the exact locations of the boundaries among different geological units is a common challenge for practitioners. As a simple a...