Abstract: A computer program product comprising at least one controller to enable a processor to perform incremental changes in storage and retrieval. The at least one controller comprises an incremental storage adaptor for enabling the processor to store a change associated with a base file, rather than modifying the base file by the change and storing the result as a new file. An incremental retrieval adaptor is included for enabling the processor to merge the change with the base file thereby forming a logical new file. The incremental retrieval adaptor can perform the merging in response to a call from an application running on the processor or another processor, and the incremental retrieval adaptor then provides or otherwise makes the logical new file available to the application.

Abstract: An evolutionary control for a subject such as an engine installed in a vehicle is conducted by the steps of: selecting coefficients, as genes, affecting the control characteristics of the control system; creating plural control units as chromosomes, each being constituted by plural genes; expressing the genes of each chromosome as control characteristics by conducting behavioral simulation on each chromosome; selecting at least one chromosome from the created chromosomes based on the result of the behavioral simulation; and causing the at least one chromosome to evolve using a genetic algorithm, thereby obtaining control characteristics suitable for the user. In this method, the characteristics of the product can easily be adjusted after its purchase.

Abstract: A family of novel multi-layer discrete-time neural net controllers is presented for the control of an multi-input multi-output (MIMO) dynamical system. No learning phase is needed. The structure of the neural net (NN) controller is derived using a filtered error/passivity approach. For guaranteed stability, the upper bound on the constant learning rate parameter for the delta rule employed in standard back propagation is shown to decrease with the number of hidden-layer neurons so that learning must slow down. This major drawback is shown to be easily overcome by using a projection algorithm in each layer. The notion of persistency of excitation for multilayer NN is defined and explored. New on-line improved tuning algorithms for discrete-time systems are derived, which are similar to e-modification for the case of continuous-time systems, that include a modification to the learning rate parameter plus a correction term. These algorithms guarantee tracking as well as bounded NN weights.

Abstract: A system and method for translating source code, comprising high level source code with embedded SQL statements, to p-code or machine-language instructions by a one-pass parsing mechanism. The one-pass parsing mechanism generates executable code without the need to generate an intermediate file. Additionally, the p-code or machine-language instructions are annotated with references to the line numbers of the corresponding source code, thereby allowing a source level debugger to debug the source code with embedded SQL statements.

Abstract: Artificial neural networks include a plurality of artificial neurons and a plurality of Boolean-complete compartments, a respective one of which couples a respective pair of artificial neurons. By providing Boolean-complete compartments, spurious complement memories can be avoided. A Boolean-complete compartment includes a collection of at least four Boolean functions that represent input vectors to the respective pair of artificial neurons. The collection of at least four Boolean functions are selected from sixteen possible Boolean functions that can represent input vectors to the respective pair of artificial neurons. A count for each of the at least four Boolean functions is also provided. The count represents a number of occurrences of each of the at least four Boolean functions in input vectors to the respective pair of artificial neurons.

Abstract: A system for building an artificial neural network is provided which precisely defines the network's structure of artificial neurons, and non-iteratively determines the synapse-weights and hard limiter threshold of each artificial neuron of the network. The system includes a computer for analyzing input data, which represents patterns of different classes of signals, to generate one or more data points in two or three dimensions representative of the signals in each of the different classes. A distribution of the data points is visualized on a map on an output device coupled to the computer. The data points are clustered on the map into clusters in accordance with the classes associated with the data points, and the map is then partitioned into regions by defining linear boundaries between clusters.

Abstract: A system and method for tracing device drivers using a computer is described. A memory is interconnected with a processor in the computer and configured into a user memory space and a kernel memory space. An application process executes on the processor within the user memory space. An operating system kernel executes on the processor within the kernel memory space with a traced device driver. A tracing device driver executes on the processor within the kernel memory space and is interposed between the application process and the traced device driver to trace interactions occurring between the traced device driver and the application process and the kernel operating system. A tracing process executes on the processor within the user memory space and interfaces with the tracing device driver. The tracing process controls the tracing device driver in accordance with user-specified parameters and includes a display for result sets generated by the tracing device driver.

Abstract: A generic anomaly detection engine is described which provides neural network technology to process information such as call detail records and detect anomalies in the information, such as mobile phone fraud. Information from call detail records is pre-processed to form signatures which represent the calling behavior of a subscriber. These signatures are formed in one of a plurality of predetermined formats. The generic anomaly detection engine is instantiated in order to create an anomaly detector which is suitable for a particular situation and during the instantiation process the topology of the neural network components is automatically adjusted to fit the required situation. The topology is adjusted to according to the format of the signatures.

Abstract: A system is disclosed that provides a goal based learning system utilizing a rule based expert training system to provide a cognitive educational experience. The system provides the user with a simulated environment that presents a business opportunity to understand and solve optimally. Mistakes are noted and remedial educational material presented dynamically to build the necessary skills that a user requires for success in the business endeavor. The system utilizes an artificial intelligence engine driving individualized and dynamic feedback with synchronized video and graphics used to simulate real-world environment and interactions. Multiple "correct" answers are integrated into the learning system to allow individualized learning experiences in which navigation through the system is at a pace controlled by the learner.

Abstract: A self-learning network with: (a) one or more sensor(s) in one or more sensor unit(s) with a plurality of memory cells that forward-select values of one or more intermediate variable(s) I.sub.1, J.sub.1, . . . according to their stored values and the conditions identified by its sensor(s) in a given sensing and action period, (b) with or without one or more intermediate units with a plurality of bidirectional memory cells that forward-select a value of one or more intermediate output variable(s) I.sub.2, J.sub.2, . . . according to their stored values and the value(s) of the intermediate input variable(s) I.sub.1, J.sub.1, . . . , and (c) one or more actuator(s) in one or more actuator unit(s) connected to one or more intermediate variable(s) I.sub.1, J.sub.1, . . . or I.sub.2, J.sub.2, . . . with a plurality of bidirectional memory cells that forward-select values of one or more actuators according to their stored values and the value(s) of its intermediate variable(s) I.sub.1, J.sub.1, . . . or I.sub.2, J.

Abstract: A system is disclosed that provides a goal based learning system utilizing a rule based expert training system to provide a cognitive educational experience. The system provides the user with a simulated environment that presents a business opportunity to understand and solve optimally. Mistakes are noted and remedial educational material presented dynamically to build the necessary skills that a user requires for success in the business endeavor. The system utilizes an artificial intelligence engine driving individualized and dynamic feedback with synchronized video and graphics used to simulate real-world environment and interactions. Multiple "correct" answers are integrated into the learning system to allow individualized learning experiences in which navigation through the system is at a pace controlled by the learner.

Abstract: A system is disclosed that provides a goal based learning system utilizing a rule based expert training system to provide a cognitive educational experience. The system provides the user with a simulated environment that presents a business opportunity to understand and solve optimally. Mistakes are noted and remedial educational material presented dynamically to build the necessary skills that a user requires for success in the business endeavor. The system utilizes an artificial intelligence engine driving individualized and dynamic feedback with synchronized video and graphics used to simulate real-world environment and interactions. Multiple "correct" answers are integrated into the learning system to allow individualized learning experiences in which navigation through the system is at a pace controlled by the learner. A website is linked to the presentation to provide context-sensitive information to assist the learner.

Abstract: In a telephone switching system, a method of performing a multiple release jump to a target program release for controlling the system. The system uses duplicate processors and disk file controllers. A new disk file is initialized with new program text and a target release version of office dependent data. This target release version is derived by upgrading the office dependent data one release at a time until office dependent data for the target release is derived. The new program text and target release version of office dependent data is inserted into one member of a duplicate disk file controller system which may either be a new disk file controller or one of the two disk file controllers currently in use in the system.