85 results about "Mixture modeling" patented technology

A computerized annotation method achieves real-time operation and better optimization properties while preserving the architectural advantages of the generative modeling approach. A novel clustering algorithm for objects is represented by discrete distributions, or bags of weighted vectors, thereby minimizing the total within cluster distance, a criterion used by the k-means algorithm. A new mixture modeling method, the hypothetical local mapping (HLM) method, is used to efficiently build a probability measure on the space of discrete distributions. Thus, in accord with the invention every image is characterized by a statistical distribution. The profiling model specifies a probability law for distributions directly.

A system and method for performing modeling, prediction, optimization, and control, including an enterprise wide framework for constructing modeling, optimization, and control solutions. The framework includes a plurality of base classes that may be used to create primitive software objects. These objects may then be combined to create optimization and / or control solutions. The distributed event-driven component architecture allows much greater flexibility and power in creating, deploying, and modifying modeling, optimization and control solutions. The system also includes various techniques for performing improved modeling, optimization, and control, as well as improved scheduling and control. For example, the system may include a combination of batch and continuous processing frameworks, and a unified hybrid modeling framework which allows encapsulation and composition of different model types, such as first principles models and empirical models. The system further includes an integrated process scheduling solution referred to as process coordinator that seamlessly incorporates the capabilities of advanced control and execution into a real time event triggered optimal scheduling solution.

A method and apparatus for determining the best fit of a population mixture model to data. In the digital imaging area, the use of histogram data is employed. A plurality of sub-population functions are defined and then optimized to fit the data. An objective function is employed, which is based upon the parameters of the underlying functions. The number of underlying functions is added to the parameter mix, such that no a priori knowledge of the number of sub-populations is required. In an illustrative embodiment, a genetic algorithm is used to evolve the objective function to an optimal fit of the data. Once an optimal fit is found, through comparison with stopping criteria in a fitness function, the data is segmented according to threshold determined based of classification error in the data.