Abstract: A method is provided for calculating the change in level which is output from a multivariable power series as a separate variable, where this change out put signal is the change in level which is output when supply input is from two different data points. This method requires defining a structure of a change-variable and modifying the arithmetic operations so this structure can be processed. A similar procedure is followed to calculate the derivative of the parameters used in the construction of the multivariable power series with this change output signal. Given an error in the change output signal and the existents of appropriate derivatives, it is possible to train the power series using the change-variable. As with any training algorithm, a matrix technique can be used to increase the training rate.

Abstract: The present invention relates to the field of computer science and can be used for neural network emulation and digital signal processing. Increasing of the neural processor performance is achieved using the ability to change word lengths of results in program mode. The neural processor includes six registers, a shift register, a AND gate, two FIFOs, a switch, a multiplexer, two saturation units, a calculation unit and a adder circuit to execute operations over vectors of programmable word length data. Increasing of the saturation unit performance is achieved using the ability to process vector of input operands with programmable word length at a time. Increasing of the adder circuit performance is achieved using ability to sum two vectors of input operands of programmable word lengths.

Abstract: A method and system for determining document content based actions. A rule engine is provided with a document to be acted on, preferably in XML format. The rule engine is also provided with a set of rules and associated actions to be taken upon special conditions. The document is evaluated according to the rules and the document contents; each of the rules is parsed into a parse tree, the document is further evaluated, including, for the provided document, populating the parse tree with at least a portion of the document contents, to create a content-populated parse tree. The portion of the actions to be initiated is selected based on the content-populated parse tree. Actions could include, by way of example, security control or further routing of the document.

Abstract: A fuzzy controller (130) for use in target detection systems. The fuzzy controller (130) includes a first circuit (132) for determining a number of false alarms in a frame of data. A second circuit (136) determines a desired number of false alarms for the frame of data. A third circuit (134-152) computes a threshold multiplier factor based on the number of false alarms, the desired number of false alarms, and one or more fuzzy rules. In a specific embodiment, the first circuit (132) includes a target detection system for providing addresses of pixels whose values are within a predetermined range relative to a detection threshold. The second circuit (136) includes an input device (136) for accepting the desired number of false alarms as input to the fuzzy controller (130). The third circuit (138-152) includes a fuzzifier input calculation circuit (134) that computes a fuzzifier input value based on the number of false alarms detected in a frame and the desired number of false alarms.

Abstract: A method and apparatus for communicating accumulated state information between internal and external tasks in a supervised learning system. A supervised learning system encodes state information for a hypothetical learning task on initialization. This hypothetical learning task state information indicates that no training instances have been received. During the supervised learning, training instances are presented to the supervised learner. The training instances are encoded with feature vector and target value information. For each task name paired with a non-default target value, the learner initializes a new learning task by copying the hypothetical learning task state representation for use as the state representation for the new learning task. Predictors are then produced for all learning tasks, except the hypothetical learning task. The new training instance is used to update all learning tasks as specified in the target vector. The new training instance is then used.

Abstract: A method to automatically categorize messages or documents containing text. The method of solution fits in the general framework of supervised learning, in which a rule or rules for categorizing data is automatically constructed by a computer on the basis of training data that has beforehand been categorized, i.e., each training data item has been labeled with the categories to which it belongs. More specifically, the method for rule induction involves the novel combination of (1) inducing from the training data a decision tree for each category, (2) automated construction from each decision tree of a simplified symbolic rule set that is logically equivalent overall to the decision tree, and which is to be used for categorization instead of the decision tree, and (3) determination of a confidence level for each rule.

Abstract: A number of consecutive samples in unit distance code (here Gray code) are effectively stacked and supplied to respective sum and threshold devices 20 corresponding to each bit position, to determine the bulk property or “generic result” of the consecutive samples. This filtered output is converted back to binary and analogue if required. The digital filter may be used in any of the above applications to “clean” data.

Abstract: A system and method for classifying unknown data patterns in a multi-variate feature space. An observer 12 evaluates the closeness of the data to any one of a plurality of known classes in a multi-variate feature space. A classifier 14 classifies the evaluated data into one of the plurality of known classes. A flagger 16 flags data having an unknown classification. A label requester 18 requests that the flagged data be interpreted into either a new class or one of the plurality of known classes. If the interpretation is a new fault, then a new class adder 22 sets up a new cluster representative of the fault and inputs the new class to the classifier 14. Alternatively, if the interpretation is that the flagged data belongs to one of the plurality of known classes, then a class resetter 24 resets the boundaries of this class and informs the classifier 14 of the change.

Abstract: A multi-dimensional Gaussian distribution generating portion obtains one vector from a multi-dimensional Gaussian probability distribution and outputs it as an initial momentum. An approximated energy function differential generating portion generates a gradient of an approximated energy function. A Hamilton equation integral portion integrates a Hamilton equation using a gradient of an approximated energy function for a predetermined integral period with initial conditions of an initial state and an initial momentum. The result of the integration as the state of the next alternative is output from a next alternative generating apparatus. The state is used with a high probability corresponding to the difference of approximated energy calculated by an approximated energy difference calculating portion and the difference between a value of an original energy in the present state and that in the next state.

Abstract: A neuron circuit including means for synaptic modification is described. The circuit emulates the electrical behaviors of the neuron membrane, dendrite, and synapse, using principles based on the actual biology. In one embodiment, the circuit is implemented as an analog very large scale integrated (VLSI) circuit which utilizes CMOS integrated circuit technology. The analog VLSI circuit includes a synapse circuit having a circuit portion which models a mechanism for the modification of the synaptic conductance.

Abstract: A modem to improve communication system performance that uses multiple modulation schemes comprising modulation technique and encoder combinations. As communication system performance and objectives change, different modulation schemes may be selected. Modulation schemes may also be selected upon the communication channel scattering function estimate, and the modem estimates the channel scattering function from measurements of the channel's frequency (doppler) and time (multipath) spreading characteristics.

Abstract: A knowledge modeling and delivery system combines pre-configured, parameterized models of human resource knowledge with organization-specific and employee-specific data. It delivers personalized answers to employee and manager questions about benefit plans, payroll, human resource (HR) policies, procedures, and practices. The pre-configured, parameterized models can be created and maintained outside the organization, the organizational data are created and maintained by the organization, and personal data are accessed or read from existing human resource management systems (HRMS's). This threefold partitioning yields a system that can be quickly customized to an individual organization, yields detailed and accurate information for individuals within the organization, and can be maintained in a cost-effective manner.

Abstract: A system and method are taught for transforming complex data sets into compact, rule-based data structures comprised of synthetic gene-like sequences, and the lossless retrieval of such encoded information. Also taught are a system and method for non-replicative information data set encryption utilizing rule-based, synthetic gene sequences wherein information extraneous to the data set, such as encryption keys, may be embedded within the synthetic gene sequence, providing the lossless retrieval of the original, unencrypted information.

Abstract: Detection is implemented by a multiplier, a lookup table or other apparatus with two inputs, one of which typically receives an input signal from a sensor, and the other a reference or weighting factor W stored or generated locally. The detected value is added to the contents of a memory location A after the previous contents of memory locations A have been modified by a loss or gain factor Q. Memory location A is one of several such memory locations in a shared memory simultaneously accessible by an external user. In a neural engine the memory locations represent neurons. For each cycle of operation of the neural engine a new value of W, Q and A are provided.

Abstract: A fuzzy-logic based overload control for packet switches wherein a distribution curve is developed regarding the overload possibility versus receive packet stream processing rate. The transmit packet stream is measured and a processing rate of the receive packet stream is measured. An overload possibility value is manipulated according to the measured bursts of the transmit packet stream and a location on the distribution curve of the measured processing rate. Packets are dropped from the transmit stream if the overload possibility value is above a threshold.

Abstract: The invention relates to an apparatus for receiving a multitude of programs which may be classified by a first and a second attribute. For example, a program may be classified by a channel name and a program category. The apparatus is capable of defining one or more user profiles which comprise ratings for some or all combinations of values of the first and the second attribute. Thus, a user can supply preferences in a very precise way. The user profile influences the behavior of various components, such as the zap function and the electronic program guide.

Abstract: Prediction methods that anticipate the outcome of a detailed optimization step are used in lieu of or in conjunction with actual optimization to improve response time and reduce required computational resources for optimization problems having a hierarchical structure. Decomposition of the optimization problem into sub-problems and sub-sub-problems is, itself, an optimization process which is iteratively performed while preferably guided by prediction of the quality of solutions to the problems into which the “master” optimization problem may be decomposed. Prediction also reduces the requirements for computational resources and allows more decompositions to be examined within the available time in order to arrive at a more nearly optimal decomposition as well as a more nearly optimal solution. Prediction is selectively used when it is determined that such a benefit is probable.

Abstract: A knowledge catalog includes a plurality of independent and parallel static ontologies to accurately represent a broad coverage of concepts that define knowledge. The actual configuration, structure and orientation of a particular static ontology is dependent upon the subject matter or field of the ontology in that each ontology contains a different point of view. The static ontologies store all senses for each word and concept. A knowledge classification system, that includes the knowledge catalog, is also disclosed. A knowledge catalog processor accesses the knowledge catalog to classify input terminology based on the knowledge concepts in the knowledge catalog. Furthermore, the knowledge catalog processor processes the input terminology prior to attachment in the knowledge catalog. The knowledge catalog further includes a dynamic level that includes dynamic hierarchies.

Abstract: A method of knowledge-based engineering cost and weight estimation of an HVAC air-handling assembly for a climate control system on a vehicle includes the steps of selecting a parametric model of an HVAC air-handling assembly design using a knowledge-based engineering library stored in a memory of a computer system. The method also includes the steps of selecting a component part from the parametric model of the HVAC air-handling assembly, determining a cost estimate of the component part using the knowledge-based engineering library and using a summation of the component part cost as the cost estimate of the HVAC air-handling assembly. The method further includes the steps of determining a weight estimate of the component part using the knowledge-based engineering library and using a summation of the component part weight as the weight estimate of the HVAC air-handling assembly. The method further includes the steps of using the cost and weight estimate in the HVAC air-handling assembly design.

Abstract: A method of knowledge-based engineering design of an instrument panel for a vehicle includes the steps of defining a parameter of the instrument panel using a knowledge-based engineering library stored in a memory of a computer system, generating a model of the instrument panel based on the parameter and analyzing the model of the instrument panel. The method also includes the steps of comparing a result of the analysis of the model of the instrument panel to a predetermined criteria from the knowledge-based engineering library, and varying the parameter so that the model of the instrument panel meets the predetermined criteria.