Abstract: A method of calibrating transceiver positions inside an acoustic pyrometry measuring vessel that contains a plurality of transceivers, includes determining (40) a speed of sound in the acoustic pyrometry measuring vessel from a temperature and gas composition of a gas inside the acoustic pyrometry measuring vessel, acquiring (41) time-of-flight (TOFs) ?ti,j measurements from a plurality of pairs i,j of transceivers inside the acoustic pyrometry measuring vessel, estimating (42) a radius of the acoustic pyrometry measuring vessel from an average of the acquired TOF measurements, and using (43) an estimated radius of the acoustic pyrometry measuring vessel to estimate errors ??j of displacement angles of the transceivers.

Abstract: Systems and methods are provided to create an acoustic map of a space containing multiple acoustic sources. Source localization and separation takes place by sampling an ultra large microphone array containing over 1020 microphones. The space is divided into a plurality of masks, wherein each masks represents a pass region and a complementary rejection region. Each mask is associated with a subset of microphones and beamforming filters that maximize a gain for signals coming from the pass region of the mask and minimizes the gain for signals from the complementary region according to an optimization criterion. The optimization criterion may be a minimization of a performance function for the beamforming filters. The performance function is preferably a convex function. A processor provides a scan applying the plurality of masks to locate a target source. Processor based systems to perform the optimization are also provided.

Abstract: Methods related to Generalized Mutual Interdependence Analysis (GMIA), a low complexity statistical method for projecting data in a subspace that captures invariant properties of the data, are implemented on a processor based system. GMIA methods are applied to the signal processing problem of voice activity detection and classification. Real-world conversational speech data are modeled to fit the GMIA assumptions. Low complexity GMIA computations extract reliable features for classification of sound under noisy conditions and operate with small amounts of data. A speaker is characterized by a slow varying or invariant channel that is learned and is tracked from single channel data by GMIA methods.

Abstract: Systems and methods are provided for modeling and simulating a communication network operating under at least one communication protocol, which supports a Smart Grid electricity network. Communication performance data of the communication network are generated by a processor based on operating behavior of the Smart Grid with a plurality of assets under a first condition. Devices in the Smart grid are grouped in bins for rapid modeling. One or more different configurations of the communication network are entered into the processor and related performance data is also generated. Network configurations are compared based on the generated performance data which may include end-to-end delay and reception rate. Processor based systems to perform modeling methods are also provided.

Abstract: Systems and methods are provided for modeling and simulating a communication network operating under at least one communication protocol, which supports a Smart Grid electricity network. Communication performance data of the communication network are generated by a processor based on operating behavior of the Smart Grid with a plurality of assets under a first condition. Devices in the Smart grid are grouped in bins for rapid modeling. One or more different configurations of the communication network are entered into the processor and related performance data is also generated. Network configurations are compared based on the generated performance data which may include end-to-end delay and reception rate. Processor based systems to perform modeling methods are also provided.

Abstract: A method and apparatus for operating a gas turbine engine including determining a temperature of a working gas at a predetermined axial location within the engine. An acoustic signal is encoded with a distinct signature defined by a set of predetermined frequencies transmitted as a non-broadband signal. Acoustic signals are transmitted from an acoustic transmitter located at a predetermined axial location along the flow path of the gas turbine engine. A received signal is compared to one or more transmitted signals to identify a similarity of the received signal to a transmitted signal to identify a transmission time for the received signal. A time-of-flight is determined for the signal and the time-of-flight for the signal is processed to determine a temperature in a region of the predetermined axial location.

Abstract: Systems and methods to monitor a signal from an apparatus are disclosed. A feature extracted from the signal is automatically defined. Signals are received over a period of time wherein the apparatus is in a normal operational mode. Features are classified in a learning mode and are applied to create a reference model that defines a within-normal operational mode. In a testing mode a signal generated by the apparatus is received, a feature is extracted and classified. Instantaneous data generated in operational mode by the apparatus is classified by the system as abnormal if it does not lie within boundaries of the reference model or contains information/structure in an orthogonal subspace. A learned reference model is augmented by a user or automatically. In one illustrative example the apparatus is a power generation equipment and the signal is an acoustic signal.

Abstract: Systems and methods are provided to determine a subset of D microphones in a set of N microphones on a perimeter of a space to monitor a target location. The space is divided into L interference locations. An equation is solved to determine microphone weights for the N microphones by minimizing the maximum gain for signals related to the target location and interference locations, further optimized over an l1 penalty by applying a Lagrange multiplier to an l1 norm of the microphone weights in a manner that determines a set of D non-zero microphones weights and a set of (N?D) microphone weights that are zero or close to zero. Microphone weights are determined for at least 2 different frequencies.

Abstract: A system and a method for a blind direction of arrival estimation is provided for a nonlinear 1-dimensional array of M receivers of J<M unknown signals transmitted through an unknown channel and subject to Gaussian noise. The method overcomes the conditions of that signals be disjoint in the time-frequency domain and/or statistically independent. A likelihood function evaluates a probability for the directions of arrivals. A weighting and regularization scheme selects relevant frequency components. A joint likelihood function of all frequencies is interpreted as a cost or objective function. The time domain is included into the estimation procedure by using a particle filter that operates on the constructed likelihood function and a simple transition kernel for the directions.

Abstract: A method for measuring degree of packet congestion on a channel of a packet communication network. The method includes: during a training mode, generating an mathematical relationship between the degree of packet congestion on the channel and a plurality of measurable features of the network over a plurality of network conditions; and, during a subsequent normal operating mode, periodically measuring the plurality of measurable features and applying the generated mathematical relationship to such periodically measured plurality of measurable features to determine actual degree of congestion on the channel; and comparing the actual degree of congestion on the channel with a predetermined channel congestion threshold level. The degree of packet congestion on the channel is saturation level. The measurable features include: time delay between transmission starts and terminations of the previously transmitted packet; the fraction of time the channel is busy; and, average number of packet transmission retries.

Abstract: Systems and methods are provided to create an acoustic map of a space containing multiple acoustic sources. Source localization and separation takes place by sampling an ultra large microphone array containing over 1020 microphones. The space is divided into a plurality of masks, wherein each masks represents a pass region and a complementary rejection region. Each mask is associated with a subset of microphones and beamforming filters that maximize a gain for signals coming from the pass region of the mask and minimizes the gain for signals from the complementary region according to an optimization criterion. The optimization criterion may be a minimization of a performance function for the beamforming filters. The performance function is preferably a convex function. A processor provides a scan applying the plurality of masks to locate a target source. Processor based systems to perform the optimization are also provided.

Abstract: An acoustic signal traversing a hot gas is sampled at a source and a receiver and is represented in overlapping windows that maximize useable signal content. Samples in each window are processed to represented in different sparsified bins in the frequency domain. Determining a signal delay between the source and the receiver from a summation of maximum smoothed coherence transform cross-correlation values of different data windows wherein a sparseness of a mean smoothed coherence transform cross-correlation of windows is maximized. Determining a set of delay times wherein outliers are deleted to estimate a time of flight from which a temperature of the hot gas is calculated.

Abstract: A system and methods to deblend seismic data from a plurality of sources and received by a plurality of sensors as shot gathers are disclosed. The deblending is performed by a Mutual Interdependence Analysis Method to separate contributions of different shots. Deblending is also performed by applying a measure of coherence in parallel data domains such as Common Shot Gather and Common Midpoint. Deblending is also achieved by using the hyperbolic nature of seismic data in the common midpoint domain. Deblended signals are estimated and are applied to create a seismic image. Also, Bergman iteration based migration is applied directly on the blended seismic shot gathers without first deblending as an alternative method. The methods are applied in seismic imaging for exploration of natural resources.

Abstract: Methods related to Generalized Mutual Interdependence Analysis (GMIA), a low complexity statistical method for projecting data in a subspace that captures invariant properties of the data, are implemented on a processor based system. GMIA methods are applied to the signal processing problem of voice activity detection and classification. Real-world conversational speech data are modeled to fit the GMIA assumptions. Low complexity GMIA computations extract reliable features for classification of sound under noisy conditions and operate with small amounts of data. A speaker is characterized by a slow varying or invariant channel that is learned and is tracked from single channel data by GMIA methods.

Abstract: A patient monitoring and intervention system, comprises an interface for receiving data representing multiple different parameters from multiple different sensors, comprising sensors in a patient bed and attached to a patient including, a heart rate sensor, a respiration sensor and a pressure sensor indicating bed pressure points. A learning processor determines a normal range for a set of the different received patient parameters for the patient by recording the patient parameter values over a time period and analyzing the recorded parameter values to determine their range. A data processor determines if the set of different received patient parameters exceeds the determined normal range and in response to this determination and in response to the type of parameters in the set and medical record information of the patient, initiates adjustment of a patient bed and at least one of, (a) changes medication administered to a patient and (b) alerts a worker of the patient parameter change.

Abstract: Methods and systems based on Dedicated Short Range Communications (DSRC) determine that a vehicle occupies a parking spot. A road-side system checks in the vehicle having an on-board DSRC system into a parking system. The system provides the on-board DSRC system with a parking rate and the on-board DSRC system provides the road-side system with payment data. A final parking fee is determined and is charged after the vehicle has left the parking spot. Parking rates are determined dynamically based on existing and/or expected conditions. A planning system provides a vehicle with a parking spot at a scheduled time. Navigation data is provided to the vehicle to reach the scheduled parking spot. Traffic and environmental policies are enforced by applying the methods and systems.

Abstract: Methods for one-class learning using support vector machines from a plurality of data batches are provided. A first support vector machine is learned from the plurality of data batches by a processor. A new data batch is received by the processor and is classified by the first support vector machine. If a non-zero loss classification occurs a new support vector machine is trained using the first support vector machine and the new data batch only. Data batches can be discarded if they are represented by the current support vector machine or after being used for training an updated support vector machine. Weighing factors applied to update the first support vector machine depend upon a parameter which is optimized iteratively. Support vectors do not need to be recalculated. A classifier is learned in a number of stages equal to the number of data batches processed on-line.

Abstract: Own voice recognition (OVR) for hearing aids, detects time instances where the person wearing the device is speaking. Classification of the own voice is performed dependent on a fixed or adaptive detection threshold. Automatic tuning in a real-time system depends on general noise statistics in the input signals. The noise is removed from the received signal and is characterized by signal-to-noise ratio and noise color. An optimal detection threshold for own voice recognition is determined based on the noise characteristics. A noise detection model is created by smoothed Voronoi tessellation. Own voice detection is performed by a processor.

Abstract: Systems and methods are provided for modeling and simulating a communication network operating under at least one communication protocol, which supports a Smart Grid electricity network. Communication performance data of the communication network are generated by a processor based on operating behavior of the Smart Grid with a plurality of assets under a first condition. Devices in the Smart grid are grouped in bins for rapid modeling. One or more different configurations of the communication network are entered into the processor and related performance data is also generated. Network configurations are compared based on the generated performance data which may include end-to-end delay and reception rate. Processor based systems to perform modeling methods are also provided.

Abstract: Systems and methods are provided for modeling and simulating a communication network operating under at least one communication protocol, which supports a Smart Grid electricity network. Communication performance data of the communication network are generated by a processor based on operating behavior of the Smart Grid with a plurality of assets under a first condition. Devices in the Smart grid are grouped in bins for rapid modeling. One or more different configurations of the communication network are entered into the processor and related performance data is also generated. Network configurations are compared based on the generated performance data which may include end-to-end delay and reception rate. Processor based systems to perform modeling methods are also provided.