Class / Patent application number | Description | Number of patent applications / Date published |
706017000 | Approximation | 20 |
20080243735 | ACTIVE SAMPLING COLLABORATIVE PREDICTION METHOD FOR END-TO-END PERFORMANCE PREDICTION - Active sample collaborative prediction method, system and program storage device are provided. A method in one aspect may include determining approximation X for matrix Y using collaborative prediction, said matrix Y being sparse initially and representing pairwise measurement values; selecting one or more unobserved entries from said matrix Y representing active samples using said approximation X and an active sample heuristic; obtaining values associated with said unobserved entries; inserting said values to said matrix Y; and repeating the steps of determining, selecting, obtaining and inserting until a predetermined condition is satisfied. | 10-02-2008 |
20080275829 | SYSTEM AND METHOD FOR OBFUSCATION OF DATA ACROSS AN ENTERPRISE - A system for obfuscating data across an enterprise, comprising a rule evaluator; an active rule editor; and an active rule editor repository; wherein the rule evaluator evaluates active rules and optimizes its behavior based on both user-specified guidance and properties learned during system execution; wherein the active rule editor provides functionality for specifying, examining, maintaining, simulating and testing active rule behavior and for documenting rules that are bound to any named and typed data spaces of the enterprise that are accessible through connectors to the data systems of the enterprise; and wherein the active rule editor and repository provide functionality for promoting a candidate rule to an active rule and managing the rule in its active state. A method for obfuscating data across an enterprise using the system described above. | 11-06-2008 |
20090030858 | Methods and apparatus to perform downhole fluid analysis using an artificial neural network - Apparatus and methods to perform downhole fluid analysis using an artificial neural network are disclosed. A disclosed example method involves obtaining a first formation fluid property value of a formation fluid sample from a downhole fluid analysis process. The first formation fluid property value is provided to an artificial neural network, and a second formation fluid property value of the formation fluid sample is generated by means of the artificial neural network. | 01-29-2009 |
20090055333 | SELF-ADAPTIVE DATA PRE-FETCH BY ARTIFICIAL NEURON NETWORK - When a patient enters a medical situation, healthcare professionals can use various amounts of information in evaluating the situation. However, different information can be beneficial dependent on the medical situation. Moreover, personnel can historically use specific information types regardless of the situation. An artificial neuron network is employed to pre-fetch information that personnel likely will want prior to a request from the personnel. In addition, the artificial neuron network can be trained based on results of presented information. | 02-26-2009 |
20090055334 | IDENTIFYING AND RECOMMENDING POTENTIAL USES OF COMPUTING SYSTEMS BASED ON THEIR PATTERNS OF USE - Techniques for identifying potential uses of computing systems are disclosed. A potential use of a computing system can be identified by considering the context that effectively represents a situation for the computing system and further considering a known situation to be a match for the situation. A known situation can be associated with a known corresponding state of use of the computing system. As such, a potential state of use of the computing system can be identified based on one or more known states of use of the computing system. A matching situation can, for example, be determined, based on pattern of use data that effectively associates a state of use with a situation in which the use may or has occurred. Identifying a potential state of use, among other things, allows making various applications, tasks, and/or services more accessible and/or effectively recommending what is likely to be used for a given situation. As a result, computing systems and the manner in which they can be used can be enhanced. In particular, a much better user experience can be achieved for mobile systems. | 02-26-2009 |
20090125465 | SYSTEM FOR AND METHOD OF CAPTURING APPLICATION CHARACTERISTICS DATA FROM A COMPUTER SYSTEM AND MODELING TARGET SYSTEM - A system for, method of and computer program product captures performance-characteristic data from the execution of a program and models system performance based on that data. Performance-characterization data based on easily captured reuse distance metrics is targeted, defined as the total number of memory references between two accesses to the same piece of data. Methods for efficiently capturing this kind of metrics are described. These data can be refined into easily interpreted performance metrics, such as performance data related to caches with LRU replacement and random replacement strategies in combination with fully associative as well as limited associativity cache organizations. Methods for assessing cache utilization as well as parallel execution are covered. | 05-14-2009 |
20110022554 | RISK ASSESSMENT FOR TOOLS - A method for creating a risk estimate for a tool includes creating a plurality of source patterns from tool data and maintenance data related to a plurality of tools. The method also includes creating a risk model from the plurality of source patterns, the risk model including a plurality of example stressors each having an associated risk value. The method also includes creating at least one stress pattern from tool data related to the tool and comparing the at least one stress pattern to the risk model to create a risk estimate for the tool. | 01-27-2011 |
20110153533 | PRODUCING SPIKE-TIMING DEPENDENT PLASTICITY IN AN ULTRA-DENSE SYNAPSE CROSS-BAR ARRAY - Embodiments of the invention relate to producing spike-timing dependent plasticity in an ultra-dense synapse cross-bar array for neuromorphic systems. An aspect of the invention includes when an electronic neuron spikes, an alert pulse is sent from the spiking electronic neuron to each electronic neuron connected to the spiking electronic neuron. When the spiking electronic neuron sends the alert pulse, a gate pulse is sent from the spiking electronic neuron to each electronic neuron connected to the spiking electronic neuron. When each electronic neuron receives the alert pulse, a response pulse is sent from each electronic neuron receiving the alert pulse to the spiking electronic neuron. The response pulse is a function of time since a last spiking of the electronic neuron receiving the alert pulse. In addition, the combination of the gate pulse and response pulse is capable increasing or decreasing conductance of a variable state resistor. | 06-23-2011 |
20110161266 | SYSTEM, METHOD AND DEVICE FOR SOLVING PROBLEMS IN NP WITHOUT HYPER-POLYNOMIAL COST - System, method and device for reducing the time required for solution of problems in the NP complexity class to polynomial time. Within satisfaction problems or problems reducible to a satisfaction problem, the invention tracks the sources of implications and identifies proximal parameterizations of conditional contradictions and subsequently avoids those contradictory conditions. The action is completed in less time than is incurred by existing methods and thus provides a performance improvement to the devices, software, or processes which address such problems. | 06-30-2011 |
20110191278 | SYSTEM AND METHOD FOR ESTIMATING LONG TERM CHARACTERISTICS OF BATTERY - A system for estimating long term characteristics of a battery includes a learning data input unit for receiving initial characteristic learning data and long term characteristic learning data of a battery to be a learning object; a measurement data input unit for receiving initial characteristic measurement data of a battery to be an object for estimation of long term characteristics; and an artificial neural network operation unit for receiving the initial characteristic learning data and the long term characteristic learning data from the learning data input unit to allow learning of an artificial neural network, receiving the initial characteristic measurement data from the measurement data input unit and applying the learned artificial neural network thereto, and thus calculating long term characteristic estimation data from the initial characteristic measurement data of the battery and outputting the long term characteristic estimation data. | 08-04-2011 |
20110276526 | POSITION RESOLVED MEASUREMENT APPARATUS AND A METHOD FOR ACQUIRING SPACE COORDINATES OF A QUANTUM BEAM INCIDENT THEREON - The position calculation of prior art position sensitive detector systems relies on a known geometry pattern of individual electrodes and the distribution of the charge parts. A heuristic estimation is made in order to calculate an initial coordinate of irradiation. In contrast, the present invention allows one to calculate the position of an incident particle in terms of direct mapping of the measured detector response into position coordinates detector surface. The device for estimating the space coordinates of an irradiation position onto a detector comprises a position sensitive detector; an irradiation source; means for measuring the response of detector generated upon irradiation by irradiation source; and an artificial neural network structure provided such that the measured detector response is the input to the artificial neural network structure and the initial space coordinates of irradiation are the output of the artificial neural network structure. | 11-10-2011 |
20110307431 | STANDARDIZING DATA USED FOR MONITORING AN AEROENGINE - A method and a system for standardizing data used for monitoring an aeroengine, and including: operating over time to collect time-series measurements from the aeroengine; calculating from the time-series measurements a set of indicators Y=(y | 12-15-2011 |
20120166375 | POWER PLANT CONTROL DEVICE WHICH USES A MODEL, A LEARNING SIGNAL, A CORRECTION SIGNAL, AND A MANIPULATION SIGNAL - A gas concentration estimation device of a coal-burning boiler adapted to estimate the concentration of the gas component included in an exhaust gas emitted from a coal-burning boiler using a neural network, including: a process database section adapted to store process data of a coal-burning boiler; a filtering processing section adapted to perform filtering processing for extracting data suitable for learning of a neural network from the process data stored in the process database section; a neural-network learning processing section adapted to perform learning processing of the neural network based on the data extracted by the filtering processing section and suitable for learning of the neural network; and a neural-network estimation processing section adapted to perform estimation processing of the CO concentration or the NOx concentration in the exhaust gas emitted from the coal-burning boiler based on the learning processing of the neural-network learning processing section. | 06-28-2012 |
20130024408 | ACTION EXECUTION BASED ON USER MODIFIED HYPOTHESIS - A computationally implemented method includes, but is not limited to: selecting at least one hypothesis from a plurality of hypotheses relevant to a user, the selection of the at least one hypothesis being based, at least in part, on at least one reported event associated with the user; and presenting one or more advisories related to the hypothesis. In addition to the foregoing, other method aspects are described in the claims, drawings, and text forming a part of the present disclosure. | 01-24-2013 |
20130268471 | SIGNAL MONITORING SYSTEM AND METHODS OF OPERATING SAME - A system for estimating a strain of a component and method of estimating strain is provided. The system includes a signal generator configured to transmit a signal toward the component. A sensor is coupled to the component and configured to receive the signal and to generate a reflected signal. The system includes a fiber Bragg grating filter coupled to the sensor and configured to filter the reflected signal and to generate a filtered signal. A detector is coupled to the filter and configured to convert the filtered signal to a time domain signal. The system includes an artificial neural network coupled to the detector and configured to process the time domain signal to facilitate estimating the strain of the component. | 10-10-2013 |
20140304203 | SIGNAL MONITORING SYSTEM AND METHODS OF OPERATING SAME - A system for estimating a strain of a component and method of estimating strain is provided. The system includes a signal generator configured to transmit a signal toward the component. A sensor is coupled to the component and configured to receive the signal and to generate a reflected signal. The system includes a fiber Bragg grating filter coupled to the sensor and configured to filter the reflected signal and to generate a filtered signal. A detector is coupled to the filter and configured to convert the filtered signal to a time domain signal. The system includes an artificial neural network coupled to the detector and configured to process the time domain signal to facilitate estimating the strain of the component. | 10-09-2014 |
20140317033 | PREDICTIVE AND DESCRIPTIVE ANALYSIS ON RELATIONS GRAPHS WITH HETEROGENEOUS ENTITIES - A system, method and computer program product provides a random walk model with heterogeneous graphs to leverage multiple source data and accomplish prediction tasks. The system and method components include: 1) A heterogeneous graph formulation including heterogeneous instances of abstract objects as graph nodes and multiple relations as edges connecting those nodes. The different types of relations, such as client-vendor relation and client-product relation, are often quantified as the weights of edges connecting those entities; 2) To accomplish prediction tasks with such information, launching a multi-stage random walk model over the heterogeneous graph. The random walk within a subgraph with homogenous nodes usually produces the relevance between entities of the same type. The random walk across different type of nodes provides the prediction of decisions, such as a client purchasing a product. | 10-23-2014 |
20160019455 | DECOMPOSING CONVOLUTION OPERATION IN NEURAL NETWORKS - A method of operating a neural network includes determining a complexity, such as a number) of separable filters approximating a filter. The method further includes selectively applying a decomposed convolution to the filter based on the determined number of separable filters. | 01-21-2016 |
20160162782 | CONVOLUTION NEURAL NETWORK TRAINING APPARATUS AND METHOD THEREOF - An apparatus and method of training a convolutional neural network (CNN) are provided. A method of training a CNN including a plurality of convolution layers stored in a memory involves approximating, using a processor, a convolution layer among the plurality of convolution layers using a low-rank approximation; reducing the number of output reconstruction filters of the approximated convolution layer; and modifying a structure of the CNN based on an approximation result and the reduced number of output reconstruction filters. | 06-09-2016 |
20160189027 | AUGMENTING NEURAL NETWORKS TO GENERATE ADDITIONAL OUTPUTS - Methods, systems, and apparatus, including computer programs encoded on computer storage media, for augmenting neural networks to generate additional outputs. One of the systems includes a neural network and a sequence processing subsystem, wherein the sequence processing subsystem is configured to perform operations comprising, for each of the system inputs in a sequence of system inputs: receiving the system input; generating an initial neural network input from the system input; causing the neural network to process the initial neural network input to generate an initial neural network output for the system input; and determining, from a first portion of the initial neural network output for the system input, whether or not to cause the neural network to generate one or more additional neural network outputs for the system input. | 06-30-2016 |