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David Helsper, Clayton Wilkinson, Robert Zack, John T Tatum, Robert J Jannarone, Bernd Harzog: Enhanced computer performance forecasting system. Netuitive, Michael J Mehrman, Mehrman Law Office P C, April 5, 2005: US06876988 (73 worldwide citation)

A method and system for computing a performance forecast for an e-business system or other computer architecture to proactively manage the system to prevent system failure or slow response time. The system is adapted to obtain measured input values from a plurality of internal data sources and exter ...


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John T Tatum, W Clayton Wilkinson IV, Robert J Jannarone: Automatic data extraction, error correction and forecasting system. Netuitive, Michael J Mehrman, Mehrman Law Office PC, July 8, 2003: US06591255 (50 worldwide citation)

A “Rapid Learner Client Service” (RLCS) system that allows a large number of end-users to obtain the benefits of a sophisticated neural-network forecasting system. Rather than purchasing or developing a forecasting system of their own, RLCS clients subscribe to a forecasting service performed by for ...


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Robert J Jannarone: Concurrent learning and performance information processing system. Morris Manning & Martin L, November 10, 1998: US05835902 (41 worldwide citation)

The present invention provides a system for learning from and responding to regularly arriving information at once by quickly combining prior information with concurrent trial information to produce useful learned information. At the beginning of each time trial a vector of measurement values and a ...


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Robert J Jannarone, J Tyler Tatum, Jennifer A Gibson: Efficient processing in an auto-adaptive network. Brainlike, Stephen C Beuerle, Procopio Cory Hargreaves & Savitch, May 5, 2009: US07529721 (5 worldwide citation)

Feature values, which may be multi-dimensional, collected over successive time slices, are efficiently processed for use, for example, in known adaptive learning functions and event detection. A Markov chain in a recursive function to calculate imputed values for data points by use of a “nearest nei ...


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Robert J Jannarone, John Tyler Tatum, Thuy Xuan Cox, Leronzo Lidell Tatum: System and method for auto-adaptive network. Brainlike, Stephen C Beuerle, Procopio Cory Hargreaves & Savitch, July 24, 2012: US08229879

An auto-adaptive system is provided that includes a template builder that allows weighted templates to be created for computing auto-adaptive features, an auto-adaptive event locator that analyzes a data set to identify events, an event extractor that locates and extracts identified events and provi ...


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Robert J Jannarone, J Tyler Tatum, Jennifer A Gibson: Auto-adaptive network for sensor data processing and forecasting. Brainlike, Stephen C Beuerle, Procopio Cory Hargreaves & Savitch, January 25, 2011: US07877337

In an auto-adaptive system, efficient processing generates predicted values in an estimation set in at least one dimension for a dependent data location. The estimation set comprises values for a dependent data point and a preselected number of spatial nearest neighbor values surrounding the depende ...


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Robert J Jannarone: Multi-kernel neural network concurrent learning, monitoring and forecasting system. Robert J Jannarone, ma gao, January 26, 2000: CN97181204

A multi-kernel neural network computing architecture configured to learn correlations among feature values (34, 38) as the network monitors and imputes measured input values (30) and also predicts future output values (46). This computing architecture, referred to as a concurrent-learning informatio ...


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Robert J Jannarone: Concurrent learning and performance information processing system. Robert J Jannarone, jian wei, September 22, 1999: CN95196552

At the beginning of each time trial a vector of measurement values and a vector of measurement plausibility values are supplied to a system (10), and a learning weight is either supplied to or generated by the system (10). The system (10) then performs the following operations during each time trial ...