Abstract: A method and device for extracting information from data representing a signal is disclosed. A set of data comprising a plurality of measurements of the signal generated at a first sampling rate is received from a sensor. A subset of the plurality of measurements is selected. A plurality of feature variables, each of which corresponds to a particular feature in a set of features that may be present in the signal are determined by deriving an underdetermined system of equations based on a selected basis function, the subset of the plurality of measurements, and the plurality of feature variables and corresponding features. The underdetermined system of equations is solved to determine a value for each feature variable using a non-linear optimization technique to minimize an L1 norm of the set of features. Feature information is stored in a storage medium.

Abstract: An automated constraint-based scheduler that uses condition-based information is disclosed. A scheduler module generates a maintenance schedule for one or more components. The scheduler module receives time-based maintenance information associated with a component and condition-based maintenance information that identifies a determined condition of the component. A plurality of constraints associated with performing maintenance on the component is determined. The scheduler module uses a constraint-based scheduler to generate a maintenance schedule for the component based on the time-based maintenance information, the condition-based maintenance information, and the plurality of constraints.