Abstract: A solution for managing information using an identification tag is provided. For example, information relating to an item and/or one or more transfers of the item can be managed using an identification tag associated with the item. The identification tag can store and transmit an item identifier, such as an electronic product code (EPC), corresponding to the item, which can be obtained and stored in a data store. Access information for retrieving the item identifier and identification information for a party to the transfer can be used to generate a custom identifier that can be provided for storage on the identification tag in place of the item identifier. The custom identifier can subsequently be used to acquire information on the item and/or the transfer event.

Abstract: A method is disclosed for dynamically creating encapsulation and decapsulation chains and segmenting the packet-forwarding plane. A distributed router may comprise multiple cards, each exposing a subset of the router's physical interfaces. Some physical interfaces may be configured to send/receive only certain types and destinations of data packets. Some cards might not expose any physical interfaces configured to send/receive a particular type and destination of packet, making encapsulation and/or decapsulation chains for virtual interfaces that process data packets of the particular type useless on those cards. Therefore, instead of always creating both encapsulation and decapsulation chains for a virtual interface on a card, an aspect of the method dynamically determines which of the encapsulation and decapsulation chains are useful for a virtual interface on that card, and creates only those chains that are useful on that card.

Abstract: A solution for managing information using an identification tag is provided. For example, information relating to an item and/or one or more transfers of the item can be managed using an identification tag associated with the item. The identification tag can store and transmit an item identifier, such as an electronic product code (EPC), corresponding to the item, which can be obtained and stored in a data store. Access information for retrieving the item identifier and identification information for a party to the transfer can be used to generate a custom identifier that can be provided for storage on the identification tag in place of the item identifier. The custom identifier can subsequently be used to acquire information on the item and/or the transfer event.

Abstract: A method is provided for automatically characterizing data sets containing data points described by d-dimensional vectors obtained by measurements, such as with sonar arrays, as either random or non-random. The data points are located by the d-dimensional vectors in a d-dimensional Euclidean space which may comprise any number d of dimensions and may comprise more than three dimensions. Large or small sets of data may be analyzed. A virtual volume is determined which contains data points from the maximum and minimums of the d-dimensional vectors. The virtual volume is then partitioned. The probability of each partition containing at least one data point for a random distribution is compared to a measurement of the number of partitions actually containing at least one data point whereby the data set is characterized as either random or non-random.

Abstract: Disclosed is a system, method, and program for generating a compiler to map a code set to object code capable of being executed on an operating system platform. At least one neural network is trained to convert the code set to object code. The at least one trained neural network can then be used to convert the code set to the object code.

Abstract: A signal processing system provides and processes a digital signal, converted from to an analog signal, which includes a noise component and possibly also an information component comprising small samples representing four mutually orthogonal items of measurement information representable as a sample point in a symbolic Cartesian four-dimensional spatial reference system. An information processing sub-system receives said digital signal and processes it to extract the information component. A noise likelihood determination sub-system receives the digital signal and generates a random noise assessment of whether or not the digital signal comprises solely random noise, and if not, generates an assessment of degree-of-randomness. The information processing system is illustrated as combat control equipment for undersea warfare, which utilizes a sonar signal produced by a towed linear transducer array, and whose mode operation employs four mutually orthogonal items of measurement information.

Abstract: Disclosed is a an integrated circuit method and system for generating a compiler to map a code set to object code capable of being executed on an operating system platform. The integrated circuit is encoded with logic including at least one neural network. The at least one neural network in the integrated circuit is trained to convert the code set to object code. The at least one trained neural network is then used to convert the code set to object code.

Abstract: A method and apparatus are provided for automatically characterizing the spatial arrangement among the data points of a three-dimensional time series distribution in a data processing system wherein the classification of said time series distribution is required. The method and apparatus utilize grids in Cartesian coordinates to determine (1) the number of cubes in the grids containing at least one input data point of the time series distribution; (2) the expected number of cubes which would contain at least one data point in a random distribution in said grids; and (3) an upper and lower probability of false alarm above and below said expected value utilizing a discrete binomial probability relationship in order to analyze the randomness characteristic of the input time series distribution.

Abstract: A method for finding a probability density function (PDF) and its statistical moments for a chosen one of four newly derived probability models for an arbitrary exponential function of the forms g(x)=&agr;xme−&bgr;xn, −∞<x<∞; g ⁡ ( x ) = α ⁢   ⁢ x m ⁢ ⅇ - βx n , 0 ≤ x < ∞ ; g ⁢ ( x ) = α ⁡

Abstract: A method and apparatus are provided for automatically characterizing the spatial arrangement among the data points of a time series distribution in a data processing system wherein the classification of said time series distribution is required. The method and apparatus utilize a grid in Cartesian coordinates to determine (1) the number of cells in the grid containing at least-one input data point of the time series distribution; (2) the expected number of cells which would contain at least one data point in a random distribution in said grid; and (3) an upper and lower probability of false alarm above and below said expected value utilizing a discrete binomial probability relationship in order to analyze the randomness characteristic of the input time series distribution. A labeling device also is provided to label the time series distribution as either random or nonrandom, and/or random or nonrandom.

Abstract: The present invention relates to a system and a method for signal classification. The system comprises a sensor array for receiving a series of input signals such as acoustic signals, pixel-based image signal (such as from infrared images detectors), light signals, temperature signals, etc., a wavelet transform module for transforming the input signals so that characteristics of the signals are represented in the form of wavelet transform coefficients and an array of hybrid neural networks for classifying the signals into multiple distinct categories and generating a classification output signal.

Abstract: A system and a method for recognizing patterns comprises a first stage for xtracting features from inputted patterns and for providing topological representations of the characteristics of the inputted patterns and a second stage for classifying and recognizing the inputted patterns. The first stage comprises two one-layer neural networks and the second stage comprises a feedforward two-layer neural network. Supplying signals representative of a set of inputted patterns to the input layers of the first and second neural networks, training the first and second neural networks using a competitive learning algorithm, and generating topological representations of the input patterns using the first and second neural networks The method further comprises providing a third neural network for classifying and recognizing the inputted patterns and training the third neural network with a back-propagation algorithm so that the third neural network recognizes at least one interested pattern.

Abstract: A signal processing system provides and processes a digital signal, generd in response to an analog signal, which includes a noise component and possibly also an information component representing four mutually orthogonal items of measurement information representable as a sample point in a symbolic four-dimensional hyperspatial reference system. An information processing and decision sub-system receives said digital signal and processes it to extract the information component. A noise likelihood determination sub-system receives the digital signal and generates a random noise assessment of whether or not the digital signal comprises solely random noise, and if not, generates an assessment of degree-of-randomness. The noise likelihood determination system controls whether or not the information processing and decision sub-system is used, in response to one or both of these generated outputs.

Abstract: A system and method for signal processing using wavelets are disclosed. The method includes the steps of generating a wavelet decomposition tree modeling the signal. The tree includes a plurality of levels of wavelet coefficients representative of the signal. The method further includes determining the actual number of wavelet coefficients available at each of the plurality of levels; measuring mean energy for each of the plurality of levels; and determining a desired number of wavelet coefficients for each of the plurality of levels based on the mean energy determined in the step of measuring. The mean energy in the step of measuring for each of the plurality of levels is indicative of the desired number of wavelet coefficients selected from each of the plurality of level. The method further includes the step of retaining the desired number of wavelet coefficients and forming a compressed representation of the signal.

Abstract: A method for finding a probability density function (PDF) and its statistical moments for an arbitrary exponential function of the form g(x)=.alpha.x.sup.m e.sup.-.beta.x.spsp.n,0<x<.infin., where .alpha., .beta., n>0, m>-1 are real constants in one-dimensional distributions and g(x.sub.1,x.sub.2, . . . ,x.sub.l) in the hyperplane. Non-linear regression analyses are performed on the data distribution and a root-mean-square (RMS) is calculated and recorded for each solution set until convergence. The basis function is reconstructed from the estimates in the final solution set and a PDF is obtained. The moment generating function (MGF), which characterizes any statistical moment of the distribution, is obtained using a novel function derived by the inventors and the mean and variance are obtained in standard fashion.

Abstract: A chaotic signal processing system receives an input signal provided by a nsor in a chaotic environment and performs a processing operation in connection therewith to provide an output useful in identifying one of a plurality of chaotic processes in the chaotic environment. The chaotic signal processing system comprises an input section, a processing section and a control section. The input section is responsive to input data selection information for providing a digital data stream selectively representative of the input signal provided by the sensor or a synthetic input representative of a selected chaotic process. The processing section includes a plurality of processing modules each for receiving the digital data stream from the input means and for generating therefrom an output useful in identifying one of a plurality of chaotic processes. The processing section is responsive to processing selection information to select one of the plurality of processing modules to provide the output.

Abstract: A signal processing system provides and processes a digital signal, generd in response to an analog signal, which includes a noise component and possibly also an information component representing three mutually orthogonal items of measurement information representable as a sample point in a symbolic Cartesian three-dimensional spatial reference system. A noise likelihood determination sub-system receives the digital signal and generates a random noise assessment of whether or not the digital signal comprises solely random noise, and if not, generates an assessment of degree-of-randomness. The noise likelihood determination system controls the operation of an information processing sub-system for extracting the information component in response to the random noise assessment or a combination of the random noise assessment and the degree-of-randomness assessment.

Abstract: A signal processing system and computer-implemented method for processing a igital data sequence representing an input signal to generate a fractal dimension value. The system includes a correlation integral value generation module, correlation plot generation module, a segmentation module, correlation dimension generation module, and a control module. The correlation integral value generation module generates a series of correlation integral values for points w.sub.n (k) in "N"-dimensional space corresponding to vectors of said digital data sequence, and in particular generates inter-point distance values within each of a plurality of volume elements of said "N"-dimensional space. The correlation plot generation module generates a correlation integral plot comprising a plot of the correlation integral values as a function of said "N"-dimensional space volume elements. The segmentation module generates, from the plot, a series of correlation integral plot segments.

Abstract: The present invention comprises a method for filling in missing data intels in a quantized time-dependent data signal that is generated by, e.g., an underwater acoustic sensing device. In accordance with one embodiment of the invention, this quantized time-dependent data signal is analyzed to determine the number and location of any intervals of missing data, i.e., gaps in the time series data signal caused by noise in the sensing equipment or the local environment. The quantized time-dependent data signal is also modified by a low pass filter to remove any undesirable high frequency noise components within the signal. A plurality of mathematical models are then individually tested to derive an optimum regression curve for that model, relative to a selected portion of the signal data immediately preceding each previously identified data gap.