A process control system is described using a plurality of autonomous process cells. Each process cell has data inputs, data outputs, processing logic, state variable, and link data specifying the other cells that provides its inputs. A scheduler triggers the plurality of cells as a whole to update their state. Cell may be recursive and contain child cells, at least some of which are linked to the parent cell. The cells can be subject to mutation and a non-brittle program language is provided fo…

A computer-implemented method and apparatus that adapts class parameters, classifies data and separates sources configured in one of multiple classes whose parameters (i.e. characteristics) are initially unknown. The data set may be generated in a dynamic environment where the sources provide signals that are mixed, and the mixing parameters change without notice and in an unknown manner. A mixture model is used in which the observed data is categorized into two or more mutually exclusive classe…

System and method for improving the performance of learning agents such as neural networks, genetic algorithms and decision trees that derive prediction methods from a training set of data. In part of the method, a population of learning agents of different classes is trained on the data set, each agent producing in response a prediction method based on the agent’s input representation. Feature combinations are extracted from the prediction methods produced by the learning agents. The input repr…

A reference pattern producing apparatus includes a data storage section, a learning coefficient storage section and a reference pattern producing section. The data storage section stores learning data of a content and a time series of features for each of a plurality of samples groups. The learning coefficient storage section stores learning coefficients to the plurality of sample groups. The reference pattern producing section repetitively learns the learning data using the learning coefficient…

A control system for an actuator employs a number of discrete feedback controllers each tuned to different operating conditions or parameters. The competing outputs of the feedback controllers are combined using fuzzy logic which dynamically effects a combination depending on the output values. One set of rules in the preferred embodiment gives greater weighting to the output having relatively lower effect on the control process.

Behavior of a device is modified based on the device’s experience. The device includes: (i) a sensing unit for sensing signals; (ii) a concern-generating unit programmed to generate concern-parameters; (iii) an actuating unit for actuating the device; and (iv) a memory storing a spreadsheet composed of multiple sets of data, each set corresponding to an event defined by signals received by the device, variations in its concern-parameters, and behavior of the device. When the device has variation…

An apparatus (10) may implement a method (160) for creating (162) a data-domain sampled network (206). In certain embodiments, a method in accordance with the invention may define (166) a data domain, provide (172) points in a data-domain space or sub-space, followed by analyzing (174) data in the data domain (100). Analysis (174) may involve selecting (175) the dimensions or variables of interest, evaluating (176) or determining (176) the cycles per dynamic range, selecting (177) an interpolati…

A boosting and pruning system and method for utilizing a plurality of neural networks, preferably those based on adaptive resonance theory (ART), in order to increase pattern classification accuracy is presented. The method utilizes a plurality of N randomly ordered copies of the input data, which is passed to a plurality of sets of booster networks. Each of the plurality of N randomly ordered copies of the input data is divided into a plurality of portions, preferably with an equal allocation o…

An efficient neural network computing technique capable of synthesizing two sets of output signal data from a single input signal data set. The method and device of the invention involves a unique integration of autoassociative and heteroassociative neural network mappings, the autoassociative neural network mapping enabling a quality metric for assessing the generalization or prediction accuracy of the heteroassociative neural network mapping.

A technique is used in embodiments of the invention such that backtracking programs can be written in a general purpose computer language (e.g., C++ or Java) without requiring the control structure of the program to reflect the structure of the decision tree. A data state and a control state are restored during backtracking. For restoring the data state, embodiments of the invention keep track of the changes made to variables and the point in execution at which the changes are made. When backtra…