112 results about "Matrix manipulation" patented technology

A matrix of execution blocks form a set of rows and columns. The rows support parallel execution of instructions and the columns support execution of dependent instructions. The matrix of execution blocks process a single block of instructions specifying parallel and dependent instructions.

Image data processing techniques utilizing multiple processes operating on one or more processors of one or more computer systems can be used to efficiently rearrange or reparameterizing image data to form hologram element (hogel) images which can then be used to produce holographic stereograms. These techniques utilize matrix manipulation of portions of image data both within a single process, and across multiple processes typically executing on different processors, and each utilizing a subset of the overall set of image data.

The contamination level estimation method for high voltage insulators collects samples of naturally contaminated insulators and builds an image data set for the collected insulators. Flashover voltages of several insulators samples are measured. ESDD levels of the collected insulators are estimated. Images are input to image processing algorithms to extract representative features. The images are segmented. Transforming the image from RGB color space into grayscale model excludes the background from the image. Subsequently, the segmented images are transferred back to RGB color space model using matrix manipulation. Since contaminants on the insulator surface affect the color of the insulator, the segmented image is transformed from RGB to HSV color space which is used for extracting statistical and linear algebraic features from the hue image. A trained artificial neural network correlates the extracted features to the contamination levels enabling testing of other contaminated insulators.

This invention discloses a group of instructions, block4 and block4v, in a matrix processor 16 that rearranges data between vector and matrix forms of an A×B matrix of data 120 where the data matrix includes one or more 4×4 sub-matrices of data 160-166. The instructions of this invention simultaneously swaps row or columns between the first 140, second 142, third 144, and fourth 146 matrix registers according to the instructions that perform predefined matrix tensor operations on the data matrix that includes one of the following group of operations: swapping rows between the different individual matrix registers, or swapping columns between the different individual matrix registers. Additionally, successive iterations or combinations of the block4 and or block4v instructions perform standard tensor matrix operations from the following group of matrix operations: transpose, shuffle, and deal.

This invention is an innovative solution to antiquated paper coupons. It overcomes deficiencies of couponing systems by using electronic data systems to process a plurality of discount transactions in parallel with the consumers purchase via real-time discounting matrix. This consumer focused system comprises a business related process possessing the means of: transceiving consumer purchase data; managing databases related to discount available items, consumer purchase performance, history, preferences, transaction history, etc.; accessing discount matrix. Individual consumers use a variety of technologies to initiate the discounting transaction during the purchase process, to perform the real-time connection, to quarry, and to reporting on matrix transactions for discount authorizations simultaneously for a plurality of retail and Internet based point of sale locations. This discount process provides a means of better determining the consumer's intent to receive discounts on desired retail goods and services through a plurality of measured definitions in the purchase process.

A method, system, and apparatus are directed towards detecting unauthorized modification of software, such as virtual smart card software. An analysis is performed on the software to generate a unique pattern that is based on the integrity of the software. The pattern is generated using various portions of the software code. In one embodiment, matrix manipulations that involve a sequence of randomly selected matrix operations are performed on extracted portions of the software code. Sample sizes of the software code, sizes of the matrices, and other initialization parameters may be selected based on a desired security level. The resulting pattern may then be compared to a known normal pattern for the software to detect unauthorized modification. In one embodiment, however, the resulting pattern may be algorithmically combined with another value. The resulting combination may be used to decrypt content, if the software has not been modified.

In accordance with a parallel matrix processing method adopted in a shared-memory scalar computer, a matrix to be subjected to LU factorization is divided into a block D of the diagonal portion and blocks beneath the D diagonal block such as L1, L2 and L3. Then, D+L1, D+L2 and D+L3 are assigned to 3 processors respectively for processing them in parallel. Next, a block U is updated by adopting an LU-factorization method and C1 to C3 are updated with L1 to L3 and U. By carrying out this processing on the inner side gradually decreasing in size as blocks, finally, a portion corresponding to the D diagonal block remains to be processed. By applying the LU factorization to this D portion, the LU factorization for the entire matrix can be completed.

The invention discloses a method for improving the data resolution ratio of a silica-based optical matrix processor and the processor. The method includes the steps that laser signals are output by a laser array and received and modulated by an optical modulator array to an N*1 vector A; a modulator matrix is formed by a micro-ring optical modulator matrix, wherein modulation depths form an M*N matrix B; optical modulation is carried out respectively by dividing the vector A into k subvectors and dividing the matrix B into k submatrixes so as to obtain the product of the k subvectors and the k submatrixes; the obtained product of the subvectors and the k submatrixes is detected by a detector linear array formed by k detectors, and then the product of the vector A and the matrix B is obtained; the element bit wide of each subvector and each submatrix is m, m bit vectors and m bit matrixes are formed after bitwise separation, and the product of the subvectors and the submatrixes is obtained by multiplying the bit vectors by the bit matrixes respectively.

The invention discloses a method and a device of extracting features for identifying a human face. When the identification features of a human face are extracted, a plurality of sample images undergo the matrixing processing instead of the vectorization processing. Furthermore, when the projection matrix is constructed, the dimension of matrix manipulation is reduced, therefore, the average required time for extracting the feature assembly from a plurality of sample images of each human facial type is reduced so as to improve the efficiency for extracting features.

The invention relates to a modal parameter recognizing method based on multi-input multi-output signal noise reduction. The method is characterized by comprising the steps of step 1, performing block-Hankel matrix conversion on noise-containing multi-point pulse responding signals to obtain a first block-Hankel matrix; step 2, processing the first matrix by utilizing structural low rank approximating according to the rank of the first matrix to obtain a first non-block-Hankel matrix after the low rank approximating; step 3, replacing the elements of each block in a second matrix with math average values of the block elements on a back-diagonal to obtain a second block-Hankel matrix; step 4, repeating the steps 2 and 3 until convergence, thus obtaining the noise-reduced multi-point pulse responding signal; and step 5, performing modal parameter recognizing. The modal parameter recognizing method based on multi-input multi-output signal noise reduction can save machine time and improve recognizing accuracy.

The present invention discloses an estimation method and device of space arrival direction used in wireless communication system which applies the technique of intelligent antenna; an up-link time slot M and a renewal cycle T included in the calibration cycle are set; a time slot comprises one or more than one renewal cycle T; when the DOA estimation of space arrival direction is started, the counting unit calculates the up-link time slot in the calibration cycle and the renewal cycle in every up-link time slot; the calculation is carried out by a controller, based on the above calculating value, in the first renewal cycle of the first time slot of every calibration cycle, activating the searching machine of maximum power value to work out the DOA calibration value which is considered as the primary value or calibration value of DOA calibration; in other time of the calibration cycle, activating the arbiter of optimal demodulation signal to work out the DOA calibration value, realizing the follow of the DOA calibration value; the selector of DOA output value chooses the final DOA calibration value. The invention can lessen the complicated matrix manipulation, providing a much precise DOA calibration value.

A system that offers a method of capturing, analyzing, and visualizing a matrix of data for object and feature extraction. This is accomplished by reading a matrix of data represented by a plurality of data types into a processor via a data capture system. The matrix of data is overlaid by a control grid to form a regular matrix having a plurality of cells. A data search spatial radius is created from a point in each cell. Data is then processed from the matrix and certain characteristics are captured and represent each variable in each cell of the matrix, and then output, respectively.

The invention relates to an adaptive side-lobe cancellation weight value method based on FPGA. The adaptive side-lobe cancellation weight value method based on FPGA utilizes an FPGA hardware platform to accelerate processing and shorten processing delay. In the algorithm, an autocorrelation matrix of auxiliary beams and a cross-correlation matrix of the auxiliary beams and target beams are estimated according to disturbance data, auxiliary beam weight values and target beam weight values, and operations such as a matrix inversion, matrix multiplication are performed in an FPGA device to obtain the adaptive side-lobe cancellation weight value. The delay of the whole processing is determined by matrix estimation and matrix manipulation. The calculation amount of the matrix estimation is relatively small, the processing delay is less, and the operating time is affected by the number of sampling points. The calculation amount of the matrix manipulation is relatively large and is mainly affected by the number of the auxiliary beams; for n auxiliary beams (n<60), the processing delay of the portion is about 60N+N (N-1) clock periods.

Image data processing techniques utilizing multiple processes operating on one or more processors of one or more computer systems can be used to efficiently rearrange or reparameterizing image data to form hologram element (hogel) images which can then be used to produce holographic stereograms. These techniques utilize matrix manipulation of portions of image data both within a single process, and across multiple processes typically executing on different processors, and each utilizing a subset of the overall set of image data.

A computerized method provides for an in-place transformation of matrix A data including a New Data Structure (NDS) format and a transformation T having a compact representation. The NDS represents data of the matrix A in a format other than a row major format or a column major format, such that the data for the matrix A is stored as contiguous sub matrices of size MB by NB in an order predetermined to provide the data for a matrix processing. The transformation T is applied to the MB by NB blocks, using an in-place transformation processing, thereby replacing data of the block A1 with the contents of T(A1).

The invention discloses an amplitude-phase error correction method for a phased array three-dimensional camera shooting sonar system energy converter array. The method comprises the following steps: utilizing two-dimensional fast Fourier transform to acquire original estimation of normalization angular frequency for two-dimensional compound sampling array of a kth sampling snapshot; based on the original estimation, acquiring the estimation value of the normalization angular frequency with higher precision in various sampling snapshots; conducting arithmetic mean on the estimation value of the normalization angular frequency of K times sampling snapshots so as to acquire the robust estimation of the orientation of a corrected source; utilizing the robust estimation and the spatial matched filtering algorithm to estimate amplitude-phase error factors of various energy converter passages in an energy converter array; utilizing the amplitude-phase error factors to compensate compound sampling signals in various energy converter passages, and finally utilizing the number wave beam forming algorithm to acquire three-dimensional camera shooting sonar wave beams going through amplitude-phase error correction. The amplitude-phase error correction method avoids heavy and complicated iteration and matrix manipulation and is small in calculated amount and suitable for on-site correction of large energy converter array in a three-dimensional sonar system.