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James D Keeler, Eric J Hartman, Kadir Liano, Ralph B Ferguson: Residual activation neural network. Pavilion Technologies, Ross Howison Clapp & Korn, October 4, 1994: US05353207 (114 worldwide citation)

A plant (72) is operable to receive control inputs c(t) and provide an output y(t). The plant (72) has associated therewith state variables s(t) that are not variable. A control network (74) is provided that accurately models the plant (72). The output of the control network (74) provides a predicte ...


2
James D Keeler, Eric J Hartman, Steven A O Hara, Jill L Kempf, Devendra B Godbole: Method and apparatus for preprocessing input data to a neural network. Pavilion Technologies, Gregory M Howison, March 17, 1998: US05729661 (103 worldwide citation)

A preprocessing system for preprocessing input data to a neural network includes a training system for training a model (20) on data from a data file (10). The data is first preprocessed in a preprocessor (12) to fill in bad or missing data and merge all the time values on a common time scale. The p ...


3
James D Keeler, Eric J Hartman, Kadir Liano, Ralph B Ferguson: Residual activation neural network. Pavilion Technologies, Gregory M Howison, September 24, 1996: US05559690 (87 worldwide citation)

A plant (72) is operable to receive control inputs c(t) and provide an output y(t). The plant (72) has associated therewith state variables s(t) that are not variable. A control network (74) is provided that accurately models the plant (72). The output of the control network (74) provides a predicte ...


4

5
James D Keeler, Eric J Hartman: Neural network with semi-localized non-linear mapping of the input space. Microelectronics and Computer Technology Corporation, Ross Howison Clapp & Korn, May 12, 1992: US05113483 (63 worldwide citation)

A neural network includes an input layer comprising a plurality of input units (24) interconnected to a hidden layer with a plurality of hidden units (26) disposed therein through an interconnection matrix (28). Each of the hidden units (26) is a single output that is connected to output units (32) ...


6
James D Keeler, Eric J Hartman, Steven A O Hara, Jill L Kempf, Devandra B Godbole: Predictive network with learned preprocessing parameters. Pavilion Technologies, Gregory M Howison, December 26, 1995: US05479573 (55 worldwide citation)

A predictive network is disclosed for operating in a runtime mode and in a training mode. The network includes a preprocessor (34') for preprocessing input data in accordance with parameters stored in a storage device (14') for output as preprocessed data to a delay device (36'). The delay device (3 ...


7
James D Keeler, Eric J Hartman, Steven A O Hara, Jill L Kempf, Devendra B Godbole: Predictive network with learned preprocessing parameters. Howison Chauza Handley & Arnott L, November 7, 2000: US06144952 (52 worldwide citation)

A predictive network is disclosed for operating in a runtime mode and in a training mode. The network includes a preprocessor (34') for preprocessing input data in accordance with parameters stored in a storage device (14') for output as preprocessed data to a delay device (36'). The delay device (3 ...


8
Ralph Bruce Ferguson, Eric J Hartman, William Douglas Johnson, Eric S Hurley: System and method for historical database training of support vector machines. Pavilion Technologies, Meyertons Hood Kivlin Kowert & Goetzel P C, Jeffrey C Hood, September 13, 2005: US06944616 (51 worldwide citation)

A system and method for historical database training of a support vector machine (SVM). The SVM is trained with training sets from a stream of process data. The system detects availability of new training data, and constructs a training set from the corresponding input data. Over time, many training ...


9
James D Keeler, Eric J Hartman, Ralph B Ferguson: Method and apparatus for operating neural network with missing and/or incomplete data. Pavilion Technologies, Gregory M Howison, March 18, 1997: US05613041 (38 worldwide citation)

A neural network system is provided that models the system in a system model (12) with the output thereof providing a predicted output. This predicted output is modified or controlled by an output control (14). Input data is processed in a data preprocess step (10) to reconcile the data for input to ...


10
James D Keeler, Eric J Hartman, Devendra B Godbole, Steve Piche, Laura Arbila, Joshua Ellinger, R Bruce Ferguson II, John Krauskop, Jill L Kempf, Steven A O Hara, Audrey Strauss, Jitendra W Telang: Automated method for building a model. Pavilion Technologies, Howison & Arnott, April 12, 2005: US06879971 (37 worldwide citation)

A method for determining an output value having a known relationship to an input value with a predicted value includes the step of first training a predictive model with at least one output for a given set of inputs that exist in a finite dataset. Data is then input to the predictive model that is w ...