Abstract: Methods and systems for learning, recognition, classification and analysis of real-world cyclic patterns using a model having n oscillators, with primary frequency ?1, ?2, . . . , ?n. The state of the oscillators is evolved over time using sensor observations, which are also used to determine the sensor characteristics, or the sensor observation functions. Once trained, a set of activity detection filters may be used to classify a sensor data stream as being associated with an activity.

Abstract: Methods and systems for learning, recognition, classification and analysis of real-world cyclic patterns using a model having n oscillators, with primary frequency ?1, ?2, . . . , ?n. The state of the oscillators is evolved over time using sensor observations, which are also used to determine the sensor characteristics, or the sensor observation functions. Once trained, a set of activity detection filters may be used to classify a sensor data stream as being associated with an activity.

Abstract: Methods and systems for learning, recognition, classification and analysis of real-world cyclic patterns using a model having n oscillators, with primary frequency ?1, ?2, . . . , ?n. The state of the oscillators is evolved over time using sensor observations, which are also used to determine the sensor characteristics, or the sensor observation functions. Once trained, a set of activity detection filters may be used to classify sensor data as being associated with an activity.

Abstract: Methods for estimating a conditional probability distribution for signal states of a non-linear random dynamic process. The filter is based on multiple particles, each defined by a state space model similar to the dynamic process. Each particle is updated on the basis of a control input derived by proportional gain feedback on an innovation process. The innovation process is the difference between an increment in an observed quantity measured by one or more sensors and an average of a function of the particles. The particle filter of the invention may also be applied to filtering problems with data association uncertainty where multiple measurements are obtained, of which at most one originates from a specified target.

Abstract: A method for controlling a temperature distribution within a combustor having a plurality of chamber sections comprising controlling a fuel-to-air ratio in the chamber sections. At least two chamber sections have different fuel-to-air ratios to create a non-uniform temperature distribution within the combustor to reduce thermoacoustic instabilities.

Abstract: A method for controlling a temperature distribution within a combustor having a plurality of chamber sections comprising controlling a fuel-to-air ratio in the chamber sections. At least two chamber sections have different fuel-to-air ratios to create a non-uniform temperature distribution within the combustor to reduce thermoacoustic instabilities.