An artificial neuron includes an aggregator that combines a plurality of input signals. The value state of each of the input signals is encoded in a phase thereof. The artificial neuron also includes an actuator in communication with the aggregator. The actuator is configured to provide an output signal having a value state encoded in a phase thereof. The value state of the output signal may be selected on the basis of the value states of the input signals. The value state of each of the input s...

A system and method for automatically creating performance models of complex information technology (IT) systems. System components and elements are subject to periodic monitoring associated with performance thresholds. A continuity analysis is performed by synchronizing testing functions associated with the predetermined system performance thresholds. Resulting data is accumulated and data mined for component and functional relations within the IT system. Models of the system may then be adapte...

A user initially judges whether each of pieces of information input as learning information is necessary or unnecessary, matrix elements of an affirmative metric signal indicating the records of the necessary information and matrix elements of a negative metric signal indicating the records of the unnecessary information are calculated in a learning unit from a plurality of keywords attached to the necessary information and the unnecessary information. Thereafter, a plurality of keywords attache...

A method for teaching an anomaly detecting mechanism in a system comprising observable elements (302), at least one of which has a periodic time-dependent behaviour, the anomaly detecting mechanism comprising a computerized learning mechanism (314). The method comprises assembling indicators (304) indicating the behaviour of the elements (302) and arranging the assembled indicators such that each observable element's indicators are assigned to the same input data component. The learning mechanis...

A compact neural network architecture is trainable to sense and classify an optical image directly projected onto it. The system is based upon the combination of a two-dimensional amorphous silicon photoconductor array and a liquid-crystal spatial light modulator. Appropriate filtering of the incident optical image upon capture is incorporated into the net work training rules, through a modification of the standard backpropagation training algorithm. Training of the network on two image classifi...

A computer implemented method, data processing system, and computer program product for monitoring system events and providing real-time response to security threats. System data is collected by monitors in the computing system. The expert system of the present invention compares the data against information in a knowledge base to identify a security threat to a system resource in a form of a system event and an action for mitigating effects of the system event. A determination is made as to whe...

A system and method of computer data analysis using neural networks. In one embodiment of the invention, the system and method includes generating a data representation using a data set, the data set including a plurality of attributes, wherein generating the data representation includes: modifying the data set using a training algorithm, wherein the training algorithm includes growing the data set; and performing convergence testing, wherein convergence testing checks for convergence of the tra...

Systems and methods are provided for training neural networks and other systems with heterogeneous data. Heterogeneous data are partitioned into a number of data categories. A user or system may then assign an importance indication to each category as well as an order value which would affect training times and their distribution (higher order favoring larger categories and longer training times). Using those as input parameters, the ordered training generates a distribution of training iteratio...

A system and a method are disclosed for automatic question classification and answering. A multipart artificial neural network (ANN) comprising a main ANN and an auxiliary ANN classifies a received question according to one of a plurality of defined categories. Unlabeled data is received from a source, such as a plurality of human volunteers. The unlabeled data comprises additional questions that might be asked of an autonomous machine such as a humanoid robot, and is used to train the auxiliary...

Developmental systems (1/11) are provided with an autotelic mechanism for driving their development. An autotelic component (1) in the system uses a mapping mechanism (2) to produce an output based on a set of inputs. The mapping mechanism (2) implements a mapping that is dependent upon a state associated therewith. The content of the state is changed by a learning/repair module (3) based on interactions between the system and the environment, and so reflects knowledge gained by this component a...