Abstract: A computer implemented meta search engine and search method. In accordance with this method, a query is forwarded to one or more third party search engines, and the responses from the third party search engine or engines are parsed in order to extract information regarding the documents matching the query. The full text of the documents matching the query are downloaded, and the query terms in the documents are located. The text surrounding the query terms are extracted, and that text is displayed.

Abstract: An autonomous citation indexing system which can be used as an assistant agent automates and enhances the task of finding publications in electronic form, including publications located on the world wide web. The system parses citations from papers and identifies citations to the same paper that may differ in syntax. The system also extracts and provides the context of citations to a given paper, allowing a researcher to determine what is published in other papers about a given paper. Common citations and word or string vector distance similarity are used to find related articles in a search.

Abstract: An autonomous citation indexing system which can be used as an assistant agent automates and enhances the task of finding publications in electronic form, including publications located on the world wide web. The system parses citations from papers and identifies citations to the same paper that may differ in syntax. The system also extracts and provides the context of citations to a given paper, allowing a researcher to determine what is published in other papers about a given paper. Common citations and word or string vector distance similarity are used to find related articles in a search.

Abstract: An autonomous citation indexing system which can be used as an assistant agent automates and enhances the task of finding publications in electronic form, including publications located on the world wide web. The system parses citations from papers and identifies citations to the same paper that may differ in syntax. The system also extracts and provides the context of citations to a given paper, allowing a researcher to determine what is published in other papers about a given paper. Common citations and word or string vector distance similarity are used to find related articles in a search.

Abstract: A hybrid neural network system for object recognition exhibiting local image sampling, a self-organizing map neural network, and a hybrid convolutional neural network. The self-organizing map provides a quantization of the image samples into a topological space where inputs that are nearby in the original space are also nearby in the output space, thereby providing dimensionality reduction and invariance to minor changes in the image sample, and the hybrid convolutional neural network provides for partial invariance to translation, rotation, scale, and deformation. The hybrid convolutional network extracts successively larger features in a hierarchical set of layers. Alternative embodiments using the Karhunen-Loeve transform in place of the self-organizing map, and a multi-layer perceptron in place of the convolutional network are described.

Abstract: Based on the encoding of deterministic finite-state automata (DFA) in discrete-time, second-order recurrent neural networks, an algorithm constructs an augmented recurrent neural network that encodes a FFA and recognizes a given fuzzy regular language with arbitrary accuracy.

Abstract: A method and apparatus for the prediction of time series data, specifically, the prediction of a foreign currency exchange rate. The method disclosed transforms the time series data into a difference of a series, compresses the transformed data using a log transformation, converts the compressed data into symbols, and subsequently trains one or more neural networks on the symbols such that a prediction is generated. Alternative embodiments demonstrate the conversion by a self-organizing map and training by a recurrent neural network.

Abstract: Any deterministic finite-state automata (DFA) can be implemented in a sparse recurrent neural network (RNN) with second-order weights and sigmoidal discriminant functions. Construction algorithms can be extended to fault-tolerant DFA implementations such that faults in an analog implementation of neurons or weights do not affect the desired network performance. The weights are replicated k times for k-1 fault tolerance. Alternatively, the independent network is replicated 2k+1 times and the majority of the outputs is used for a k fault tolerance. In a further alternative solution, a single network with k.eta. neurons uses a "n choose k"encoding algorithm for k fault tolerance.

Abstract: An optical processor that can compute the moments of a two-dimensional image in parallel. The image is placed at the plane of a holographic mask which is disposed in the front focal plane of a Fourier-transforming lens and each of the desired moments is found at a respective one of a plurality of photodetectors arrayed in the back focal plane of the lens.