Abstract:
A multi-dimensional processing and display system that is used with textual data to provide a system by which large volumes of such textual data may be efficiently sorted and searched. Textual data that is input to the multi-dimensional processing and display system is from one or more documents that are reformatted and translated into one or more numeric matrices. The matrices are modified to enhance and/or suppress certain words, phrases, subjects, etc. Thereafter, a single two-dimensional data is formed by concatenating the numeric matrices. The multi-dimensional processing and display system creates and maintains a historical database which is also concatenated in the two-dimensional matrix. Once the textual data is in the form of a two-dimensional matrix, the data can be analyzed efficiently, for example, using singular value decomposition (SVD). In doing so, the two-dimensional concatenated matrix is decomposed to obtain a compressed form of the numeric matrix. Certain data elements in the two-dimensional matrix may be enhanced, while certain other data elements may be suppressed. After data enhancement and/or suppression, the two-dimensional matrix is partitioned and rearranged to form an enhanced multi-dimensional matrix. All or portions of the enhanced multi-dimensional matrix are then visually displayed. Lexical, semantic, and/ or textual constructs of interest may be displayed as opaque objects within a three-dimensional transparent cube, enabling a user to review many documents quickly and easily.
Abstract:
A medical processing and display system that may be used with a medical monitoring device. This system enhances the medical data it receives. Once received, the medical data is reformatted into a two-dimensional matrix, X. A history database and other information are concatenated with the two-dimensional matrix. The concatenated matrix is decomposed using singular value decomposition ("SVD") to obtain corresponding left and right singular vectors, L and R, respectively, and singular values D. Selected singular vectors are transformed to their autocorrelation matrix form, which are concatenated, then decomposed using SVD to their corresponding singular vectors P, P.sup.t, and singular values D. Certain of the singular vectors P are selected to filter out signal components of interest. The singular values D of the autocorrelation matrix are modified and used to adjust the weights of the associated singular vectors P. The weighted singular vectors are then combined and the resulting coefficients are used as a FIR filter to enhance the original singular vectors L and/or R.sup.t to enhance singular values L.sub.e, R.sub.e. Enhanced medical data containing the features of interest X.sub.e is generated from the enhanced original matrix singular values L.sub.e and R.sub.e, and modified singular values D.sub.e, and the results may be displayed to a diagnotician in various formats.
Abstract:
The multidimensional ECG processing and display system of the present invention is used with an electrocardiographic (ECG) monitoring system. Input ECG data from multiple, sequential time intervals is collected and formatted into a two-dimensional matrix. The two-dimensional matrix is decomposed using singular value decomposition (SVD) to obtain its corresponding singular values and singular vectors, a compressed form of the matrix. The singular vectors are analyzed and filtered to identify and enhance signal components of interest. Selected singular vectors are transformed into their frequency domain representations by the Fast Fourier Transform (FFT), or related techniques. Certain data elements in the two-dimensional matrix are enhanced or diminished by modifying the singular values within groups of singular vectors to enhance certain objects that are associated with the ECG data and to diminish other features within the data. The enhanced data is expanded back into its original form and features in the ECG data are displayed as opaque objects within a transparent data cube.
Abstract:
The multidimensional ECG processing and display system of the present invention is used with an electrocardiographic (ECG) monitoring system. Input ECG data from multiple, sequential time intervals is collected and formatted into a two-dimensional matrix. The two-dimensional matrix is decomposed using singular value decomposition (SVD) to obtain its corresponding singular values and singular vectors, a compressed form of the matrix. The singular vectors are analyzed and filtered to identify and enhance signal components of interest. Selected singular vectors are transformed into their frequency domain representations by the Fast Fourier Transform (FFT), or related techniques. Certain data elements in the two-dimensional matrix are enhanced or diminished by modifying the singular values within groups of singular vectors to enhance certain objects that are associated with the ECG data and to diminish other features within the data. The enhanced data is expanded back into its original form and features in the ECG data are displayed as opaque objects within a transparent data cube.
Abstract:
A multi-dimensional acoustic, data processing and display system arranges acoustic data in a three-dimensional matrix. The three-dimensional matrix is compressed using singular value decomposition into singular vectors and singular values. A historical database is created and maintained and is also concatenated with the three-dimensional data. This database allows reverberation and noise to be diminished and other, weaker features in the data to be enhanced. Once the data is compressed, the data can be analyzed efficiently. The singular vectors are partitioned into one or more groups on the basis of their singular values or other criteria. Certain of the compressed data elements are enhanced or diminished by modifying the singular values within each of the groups of singular vectors. Selected singular vectors are processed further by other techniques for further enhancement, detection, isolation, feature extraction and classification. The compressed and enhanced data is then expanded back into three-dimensional form for display or for other processing.
Abstract:
An enhancer receives, combines, and correlates at least two sets of data from different imaging sources, such as a mammographic imaging system and an ultrasound imaging system, for imaging bodily tissue, such as breast tissue. The processed data can then be displayed. The enhancer embeds sets of data in matrixes and uses singular value decomposition to compress the data into singular vectors and singular values. The compressed data can be altered to enhance or suppress desired features.
Abstract:
A multi-dimensional processing and display system is used with a sonar tracking system to monitor ocean-going vessels. The system arranges data in a three-dimensional matrix, which is then reformatted into a two-dimensional matrix. The two-dimensional matrix is decomposed into singular vectors and singular values. Certain data elements in the two-dimensional matrix are enhanced or diminished by modifying selected angular values. A history database is maintained by saving certain of the singular vectors, which is concatenated with the two-dimensional matrix. An enhanced two-dimensional matrix is generated by multiplying the two-dimensional concatenated matrix by the modified singular values and the singular vectors. After data enhancement, the two-dimensional enhanced matrix is reformatted back into a three-dimensional matrix. All or portions of the enhanced three-dimensional matrix can then be displayed.
Abstract:
A multi-dimensional acoustic data processing and display system arranges acoustic data in a three-dimensional matrix. The three-dimensional matrix is compressed using singular value decomposition into singular vectors and singular values. A historical database is created and maintained and is also concatenated with the three-dimensional data. This database allows reverberation and noise to be diminished and other, weaker features in the data to be enhanced. Once the data is compressed, the data can be analyzed efficiently. The singular vectors are partitioned into one or more groups on the basis of their singular values or other criteria. Certain of the compressed data elements are enhanced or diminished by modifying the singular values within each of the groups of singular vectors. Selected singular vectors are processed further by other techniques for further enhancement, detection, isolation, feature extraction and classification. The compressed and enhanced data is then expanded back into three-dimensional form for display or for other processing.
Abstract:
A multi-dimensional processing and display system that is used with equal data to provide a system by which large volumes of such textual data may be efficiently sorted and searched. Textual data that is input to the multi-dimensional processing and display system is from one or more documents that are reformatted and translated into one or more numeric matrices. The matrices are modified to enhance and/or suppress certain words, phrases, subjects, etc. Thereafter, a single two-dimensional data is formed by concatenating the numeric matrices. The multi-dimensional processing and display system creates and maintains a historical database which is also concatenated in the two-dimensional matrix. Once the textual data is in the form of a two-dimensional matrix, the data can be analyzed efficiently, for example, using singular value decomposition (SVD). In doing so, the two-dimensional concatenated matrix is decomposed to obtain a compressed form of the numeric matrix. Certain data elements in the two-dimensional matrix may be enhanced, while certain other data elements may be suppressed. After data enhancement and/or suppression, the two-dimensional matrix is partitioned and rearranged to form enhanced multi-dimensional matrix. All or portions of the enhanced multi-dimensional matrix are then visually displayed. Lexical, semantic, and/or textual constructs of interest may be displayed as opaque objects within a three-dimensional transparent cube, enabling a user to review many documents quickly and easily.
Abstract:
A multi-dimensional acoustic data processing and display system arranges acoustic data in a three-dimensional matrix. The three-dimensional matrix is compressed using singular value decomposition into singular vectors and singular values. A historical database is created and maintained and is also concatenated with the three-dimensional data. This database allows reverberation and noise to be diminished and other, weaker features in the data to be enhanced. Once the data is compressed, the data can be analyzed efficiently. The singular vectors are partitioned into one or more groups on the basis of their singular values or other criteria. Certain of the compressed data elements are enhanced or diminished by modifying the singular values within each of the groups of singular vectors. Selected singular vectors are processed further by other techniques for further enhancement, detection, isolation, feature extraction and classification. The compressed and enhanced data is then expanded back into three-dimensional form for display or for other processing.