Abstract: Generating a high-level, bit-accurate and cycle-accurate simulation model. The various embodiments generate the simulation model from a functional description of a module and an HDL description of the module. The functional description may be un-timed and specified in a high-level language. The HDL description is realizable in hardware. The simulation model is created by obtaining the control specification from the HDL description and combining the control specification with the data path description from functional description.

Abstract: Determination of a connectivity-metrics for graphs representative of networks of interest. A graph that represents a network of interest is accessed. The graph includes nodes representing points in the network of interest, and edges corresponding to the nodes. Bit-vectors are generated corresponding to the nodes and/or edges, wherein individual bits in the bit-vectors respectively provide a logical indication of connectedness. The connectivity-metric is then determined by applying a logical bit operation to the plurality of bit-vectors. Examples of connectivity metrics include a connected components, shortest paths, betweenness, clustering, and tree-based determinations.

Abstract: An object recognition system is described that incorporates swarming classifiers. The swarming classifiers comprise a plurality of software agents configured to operate as a cooperative swarm to classify an object group in a domain. Each node N represents an object in the group having K object attributes. Each agent is assigned an initial velocity vector to explore a KN-dimensional solution space for solutions matching the agent's graph. Further, each agent is configured to search the solution space for an optimum solution. The agents keep track of their coordinates in the KN-dimensional solution space that are associated with an observed best solution (pbest) and a global best solution (gbest). The gbest is used to store the best solution among all agents which corresponds to a best graph among all agents. Each velocity vector thereafter changes towards pbest and gbest, allowing the cooperative swarm to classify of the object group.

Abstract: Artificial neurons and processing elements for artificial neurons are disclosed. One processing element generates a continuous value signal based on the first plurality of inputs and generates a responsiveness based on a second plurality of inputs. An output value determining portion generates an output signal that is equal to a predetermined value when the responsiveness signal corresponds to a non-responsive and equal to the continuous value signal when the responsiveness signal corresponds to a responsive state. Another processing element produces an output signal having a magnitude equal to zero except during a fixed time after an event when the output signal has a magnitude based on an event time.

Abstract: A method for creating hierarchical classifiers of software components in a learning system, each software component comprising an identifier and a rule for processing an input message, the method comprising the steps of: receiving an input message by a first software component; parsing the input message to identify an input value; seeking a second software component having an identifier matching the identified input value; in the event that the seeking step fails to locate a match, creating a second software component and assigning an identifier to the created second software component, the identifier matching the identified input value.

Abstract: Systems, methodologies, media, and other embodiments associated with external virtualization are described. One exemplary system embodiment includes an emulation logic located external to an integrated circuit to which it may be operably connected. The example emulation logic may include a virtualization logic that is configured to virtualize a portion of a function performed by the integrated circuit. The portion may be identifiable by an address associated with the portion. The example emulation logic may also include a data store that is operably connected to the virtualization logic and that is configured to store a state data associated with virtualizing the portion of the function.

Abstract: Architecture for analyzing pattern shifts in data patterns of data mining models and outputting the results. This allows comparing and describing differences between two semantically similar sets of patterns (or mining models), and for analyzing historical changes in versions of the same model or differences in patterns found by two or more different algorithms applied to the same data. The architecture can also facilitate explaining data patterns that shift over time and over different data populations, and between versions of the same model that use different algorithms. A model component is employed for storing data mining models have respective sets of data patterns obtained from a dataset, and an analysis component analyzes the sets of the data patterns for difference data therebetween. The dataset can be a subsample of a larger set of data and can be analyzed by the analysis component over a time period.

Abstract: The present invention relates to a system, method, and computer program product for recognition objects in a domain which combines feature-based object classification with efficient search mechanisms based on swarm intelligence. The present invention utilizes a particle swarm optimization (PSO) algorithm and a possibilistic particle swarm optimization algorithm (PPSO), which are effective for optimization of a wide range of functions. PSO searches a multi-dimensional solution space using a population of “software agents” in which each software agent has its own velocity vector. PPSO allows different groups of software agents (i.e., particles) to work together with different temporary search goals that change in different phases of the algorithm. Each agent is a self-contained classifier that interacts and cooperates with other classifier agents to optimize the classifier confidence level.

Abstract: Techniques enable the reduction of bandwidth requirements for peer-to-peer gaming architectures. In some embodiments, these techniques allow differentiation among players to decide which players should receive continuous updates and which should receive periodic updates. For those gaming systems receiving periodic updates, guided artificial intelligence is employed to simulate activity of a game object based on guidance provided by the periodic updates. Conversely, for those gaming systems receiving continuous updates, the continuous updates may be employed to update the activity of the game object rather than simulating the activity.

Abstract: An object recognition system is described that incorporates swarming classifiers with attention mechanisms. The object recognition system includes a cognitive map having a one-to-one relationship with an input image domain. The cognitive map records information that software agents utilize to focus a cooperative swarm's attention on regions likely to contain objects of interest. Multiple agents operate as a cooperative swarm to classify an object in the domain. Each agent is a classifier and is assigned a velocity vector to explore a solution space for object solutions. Each agent records its coordinates in multi-dimensional space that are an observed best solution that the agent has identified, and a global best solution that is used to store the best location among all agents. Each velocity vector thereafter changes to allow the swarm to concentrate on the vicinity of the object and classify the object when a classification level exceeds a preset threshold.

Abstract: Systems and methods are provided for graphically representing uncertainty in an assisted decision-making application. A database contains a class vector for each of a plurality of objects of interest. A given class vector includes a plurality of possible classes for its associated object of interest and a corresponding set of confidence values. The database also contains a set of assumptions associated with each confidence value. A user interface displays a plurality of graphics representing the objects of interest. A given graphic includes a set of at least two class icons, each corresponding to one of the plurality of classes associated with its corresponding object of interest. The graphic also includes a qualitative indication of the confidence values associated with the set of classes. The assumptions associated with a given confidence value are retrievable by a user by selecting the class icon associated with the confidence value.

Abstract: An object recognition system is described that incorporates swarming classifiers. The swarming classifiers comprise a plurality of software agents configured to operate as a cooperative swarm to classify an object in a domain as seen from multiple view points. Each agent is a complete classifier and is assigned an initial velocity vector to explore a solution space for object solutions. Each agent is configured to perform an iteration, the iteration being a search in the solution space for a potential solution optima where each agent keeps track of its coordinates in multi-dimensional space that are associated with an observed best solution (pbest) that the agent has identified, and a global best solution (gbest) where the gbest is used to store the best location among all agents. Each velocity vector changes towards pbest and gbest, allowing the cooperative swarm to concentrate on the vicinity of the object and classify the object.

Abstract: A system and method for allocating computing resources among a plurality of units in a distributed network. A system is provided that includes: a relational fuzzy modeling system for providing a relational fuzzy model based on historical resource parameter data and historical system parameter data, and for predicting and allocating resource requirements for each unit based on the relational fuzzy model; a normalization system for ensuring that a sum of the predicted resource requirements is no more than a total available amount of actual resources available on the plurality of units; and an extra resource allocation system for allocating extra resources when the sum of the predicted resource requirements is less than the total available amount of resources available on the plurality of units.

Abstract: A method of producing a model for use in predicting time to an event includes obtaining multi-dimensional, non-linear vectors of information indicative of status of multiple test subjects, at least one of the vectors being right-censored, lacking an indication of a time of occurrence of the event with respect to the corresponding test subject, and performing regression using the vectors of information to produce a kernel-based model to provide an output value related to a prediction of time to the event based upon at least some of the information contained in the vectors of information, where for each vector comprising right-censored data, a censored-data penalty function is used to affect the regression, the censored-data penalty function being different than a non-censored-data penalty function used for each vector comprising non-censored data.

Abstract: A method for determining an array space of an array antenna by using a genetic algorithm and an array antenna having a soft structure with irregular array spacing are disclosed. The array antenna having a sofa structure with irregular array spacing, includes: a plurality of radiation elements having an inclined angle based on a horizontal plane and arranged with irregular array spacing for radiating and receiving an radio wave; a plurality of phase shifters for amplifying radiation signals radiated from the plurality of radiation elements and receiving signals received from the plurality of radiation elements, and controlling phases of the radiation signals and the receiving signals; and a radio wave signal coupler for dividing a transmitting signal to the radiation signals, transferring the divided radiation signals to the plurality of phase shifters and coupling the receiving signals from the plurality of phase shifters.

Abstract: An information processing apparatus includes a first learning unit adapted to learn a first SOM (self-organization map), based on a first parameter extracted from an observed value, a winner node determination unit adapted to determine a winner node on the first SOM, a searching unit adapted to search for a generation node on a second SOM having highest connection strength with the winner node, a parameter generation unit adapted to generate a second parameter from the generation node, a modification unit adapted to modify the second parameter generated from the generation node, a first connection weight modification unit adapted to modify the connection weight when end condition is satisfied, a second connection weight modification unit adapted to modify the connection weight depending on evaluation made by a user, and a second learning unit adapted to learn the second SOM based on the second parameter obtained when the end condition is satisfied.

Abstract: A general purpose processor architecture (methods and apparatuses) that can discern all subsets of a serial data stream which fulfill an arbitrarily complex reference pattern. The invention comprises an ordered set of Detection Cells conditionally interconnected according to the reference pattern and operationally controlling one another's states through the network. The invention preferably includes a Host Interface to enable reporting of Results from a search session as well as the input and control of reference patterns and source data.

Abstract: This invention relates to a method of determining stability of unstable equilibrium point (UEP) computed by using BCU method, comprising selecting UEP computed by using BCU method, obtaining a test vector Xtest for the selected UEP, say XUEP using the following equation: Xtest=Xspost+0.99(XUEP?Xspost) where Xspost is the SEP, and checking boundary condition of XUEP by simulating system trajectory of post-fault original system starting from Xtest.

Abstract: An integrated intelligent environment provides responses to incoming user requests for information. Aspects of the integrated intelligence environment allow information to be efficiently gathered from past solutions, and/or new information to be collected from multiple information sources. The integrated intelligence may include learning agents, mobile objects, and optimizer components that allow for the efficient gathering of information across multiple platforms. The learning agents facilitate providing a response to the user request by determining how similar requests were handled in the past. The mobile objects are configured to seek information from the multiple information sources, and may utilize a publish and subscribe framework. The optimizer determines whether a cost associated with a possible solution justifies use of that solution. A feedback mechanism allows users to rate the provided responses to their requests for information.

Abstract: Methods and systems for reducing finite element simulation time for acoustic response analysis are disclosed. In one embodiment, a method includes analytically creating a finite element model, the finite element model including a plurality of subdivisions. A plurality of cross-correlations between respective pairings of the subdivisions is then specified. A portion of the cross-correlations are then eliminated to provide a reduced set of cross-correlations between respective pairings of the subdivisions. The elimination includes determining a spatial distance value between at least two subdivisions, and discarding at least one of the cross-correlations for which the spatial distance value is greater than a specified threshold value. The finite element simulation is then performed using the reduced set of cross-correlations.