897 results about "Data vector" patented technology

A system and method for dynamically evaluating an electronic commerce business model through click stream analysis is disclosed. An electronic commerce business model is incorporated into a Web site. The Web site includes a plurality of related Web pages structured in a hierarchical manner. Each Web page includes one or more hyperlinks selectable by a user. A plurality of data vectors is stored. Each data vector represents a click stream path through the Web site. Each data vector includes a set of data entries that each corresponds to Web content selected via the hyperlinks in the related Web pages. Each click stream path is classified based on at least one such data entry in the data vector. The classified click stream path shares at least one common characteristic with one or more other click stream paths. The classified click stream paths are analyzed according to a pre-defined evaluation procedure directed at determining at least one of efficacy of presentation and shifts in demography. The electronic commerce business model is compared to the classified click stream paths analysis.

In some embodiments, a data processing system including an operation unit including circuitry configurable to perform any selected one of a number of operations on data (e.g., audio data) and a configuration unit configured to assert configuration information to configure the operation unit to perform the selected operation. When the operation includes matrix multiplication of a data vector and a matrix whose coefficients exhibit symmetry, the configuration information preferably includes bits that determine signs of all but magnitudes of only a subset of the coefficients. When the operation includes successive addition and subtraction operations on operand pairs, the configuration information preferably includes bits that configure the operation unit to operate in an alternating addition / subtraction mode to perform successive addition and subtraction operations on each pair of data values of a sequence of data value pairs. In some embodiments, the configuration information includes bits that configure the operation unit to operate in a non-consecutive (e.g., butterfly or bit-reversed) addressing mode to access memory locations having consecutive addresses in a predetermined non-consecutive sequence. Other aspects are audio encoders and decoders including any embodiment of, and configuration units and operation units for use in, any embodiment of the system, and methods performed during operation of any embodiment of the system or configuration or operation unit thereof.

A bidirectional signal processing method uses parallel transmission of digital transmitted data streams in a multiple input-multiple output system. Related art methods generate high bit error rates mostly in singular transmission channels. For this reason, the rank-adaptive signal processing method provides that the number nd of active subchannels are varied according to the actual channel behavior in order to effect a robust data transmission even in singular radio channels based on a transmit-side and receive-side channel knowledge and a modification of the data vector by a linear matrix vector multiplication while introducing a factor gamma for limiting the maximum transmit power. The maximum transmit power is then only distributed to the currently activated subchannels so that no transmit power remains unused. Another optimization of the number of subchannels nd occurs when selecting the modulation and encoding methods. During the optimal rank-adaptation according to the water-filling principle, another power is allocated to each subchannel. Another modulation and encoding method is accordingly selected for each data stream. During the suboptimal rank-adaptation according to the channel inversion principle, all subchannels have the same power whereby enabling the data streams to be modulated and encoded in a common source

A method, apparatus, and computer program device enabling a computer network switching device to inform an attached requesting device of switch ports affected by configuration changes during the period of time since the last query by the particular requesting device. The switch device is initialized with a change index and data vector, the latter indicative of an initial port configuration. The switch increments the index in response to subsequent port configuration change events, and stores in association with the incremented index a data vector indicating the ports changed during the corresponding event. The switch stores an array of associated index and vector values. The switch responds to a query from an attached requesting device by informing the requesting device of specific ports affected by one or more configuration changes since the index value held by the requesting device was the current index value in the switch.

An iterative image reconstruction method used with an imaging system that generates projection data, the method comprises: collecting the projection data; choosing a polar or cylindrical image definition comprising a polar or cylindrical grid representation and a number of basis functions positioned according to the polar or cylindrical grid so that the number of basis functions at different radius positions of the polar or cylindrical image grid is a factor of a number of in-plane symmetries between lines of response along which the projection data are measured by the imaging system; obtaining a system probability matrix that relates each of the projection data to each basis function of the polar or cylindrical image definition; restructuring the system probability matrix into a block circulant matrix and converting the system probability matrix in the Fourier domain; storing the projection data into a measurement data vector; providing an initial polar or cylindrical image estimate; for each iteration; recalculating the polar or cylindrical image estimate according to an iterative solver based on forward and back projection operations with the system probability matrix in the Fourier domain; and converting the polar or cylindrical image estimate into a Cartesian image representation to thereby obtain a reconstructed image.

A method and system for combining data for identifying compatibility, having the steps of accessing at least one data source to extract data from the at least one data source that substantially merges all user data, classifying the data using a classification system, generating a data vector for the data, storing the data vector in the classification system, assessing a user attribute vector to the user data, comparing the data vector and the user attribute vector to produce at least one relationship recommendation, and providing to the user the at least one relationship recommendation.

A system obtains neuro-response data as well as survey based data during discrete choice modeling to evaluate subject decision making processes. A discrete choice model evaluates a decision made by a subject as a function of multiple variables. Neuro-response data vectors and orthogonal survey based data vectors are weighted and combined to generate multi-dimensional vectors. The multi-dimensional vectors are used to estimate the effectiveness of changing particular variables in modifying subject behavior.

Apparatus and methods are disclosed for detecting anomalies in microwave penetrable material that may be used for locating plastic mines or pipes underneath the ground. A transmitter is positioned at a plurality of different positions above the ground. A microwave signal is transmitted that is stepped over a plurality of frequencies. At each position, a plurality of reflections are received corresponding to each of the plurality of frequencies that were transmitted. A complex target vector may be produced at each position that contains complex values corresponding to magnitude, phase, and time delay for each of the plurality of reflections received at that location. A complex reference data vector may be produced, either based on predetermined values or based on data from the received plurality of reflections. A comparison is made between the complex target vector and the complex reference data vector to produce a channel vector. In one embodiment, an operator may be applied to the channel vector such as a complex filter matrix or to add a complex conjugate. A response signal is produced and anomalies are detected by variations in the response signal with respect to the plurality of positions.

A system and method for processing operations that use data vectors each comprising a plurality of data elements, in accordance with the present invention, includes a vector data file comprising a plurality of storage elements for storing data elements of the data vectors. A pointer array is coupled by a bus to the vector data file. The pointer array includes a plurality of entries wherein each entry identifies at least one storage element in the vector data file. The at least one storage element stores at least one data element of the data vectors, wherein for at least one particular entry in the pointer array, the at least one storage element identified by the particular entry has an arbitrary starting address in the vector data file.

The invention discloses an estimation method of a co-prime array DOA (Direction Of Arrival) angle based on sparse reconstruction, and mainly solves the problems that a prior art is higher in operand, less in identification information source amount and large in passive location evaluated error, and needs more priori knowledge. The method comprises the realizing steps of forming a co-prime array by an antenna receiver; obtaining observation data to spatial signal sampling; receiving data vectors by a virtual array element obtained by observation data; dividing spatial grids to form over-complete bases; receiving a spare relationship between the data vectors and the over-complete bases by the virtual array element to build a spare restraint equation; resolving the spare restraint equation by adopting a convex optimization method to obtain sparest resolution; drawing a magnitude spectrogram by a relative relationship between the sparest resolution and the spatial angle to obtain a DOA angle value. According to the method provided by the invention, the passive direction-finding precision and operating speed can be improved under a condition of low priori knowledge, the number of the recognized information source can be improved, and the estimation precision of a signal direction angle can be improved in a low signal to noise ratio, therefore the estimation method can be used for target reconnaissance and passive location.

The invention discloses a method for mining data in construction regulation field based on associative regulation mining technology; 1. a construction regulation text vector space model is generated, 2. a construction regulation data vector space model is generated, 3. the construction regulation data vector space model is subject transposition to generate a construction regulation data feature vector space model, namely, a frequent feature set is generated, and 4. construction regulation data association degree is calculated and an association rule is output. The method can mine the data in construction regulation field, provides higher recall ratio for a user inquiring data, recommends associative query contents, and solves the technical problem that the existing association analysis technologies can not carry out association analysis on outlier data.

The invention provides a building method used for a knowledge obtaining model in a knowledge graph. The method comprises the steps of constructing a first training set consisting of multiple text sentences as input data and a relationship between any two entities in each sentence in the knowledge graph, as a classification result, and training a first neural network; constructing a second trainingset consisting of triples in multiple knowledge graphs, and training a second neural network; by taking input data vectors obtained in the second neural network as attention features of the first neural network, building a relationship extraction model; by taking input data vectors obtained in the first neural network as attention features of the second neural network, building a knowledge representation model; and fusing the relationship extraction model and the knowledge representation model to obtain the knowledge obtaining model in the knowledge graph. According to the method provided bythe invention, the two task models of knowledge representation and relationship extraction are integrated at the same time, and the features of the knowledge graph and free texts can be comprehensively extracted, so that the model stability and accuracy are improved.

A method and apparatus for coding positions of data such as coefficients are described. In one embodiment, the method comprises coding data in a vector of data based on indications of whether the data is zero or non-zero identified using a tree data structure and producing a bit stream based on coded data.

The invention relates to a method of reducing Peak-to-Average. Power Ratio in a transmitting device of a filter-hank multi-carrier system, which includes the steps of: performing constellation modulation (210) on data to be transmitted; performing K-point Discrete Fourier Transform (220) on a vector composed of K constellation symbols resulting from the constellation modulation: and performing Offset-Quadrature Amplitude Modulation (230) on a data vector resulting from the Discrete Fourier Transform, wherein the parameter K represents the number of subcarriers allocated for transmission of the data to be transmitted. With the solution proposed by the invention. PAPR of a signal can be significantly reduced without adding a large number of operations to thereby improve the efficiency of a power amplification circuit, to improve effective transmission, power and to alleviate nonlinear distortion of the signal during a power amplification.

A time division duplex using code division multiple access user equipment receives a plurality of data signals in a time slot. Each data signal experiences a similar channel response. The user equipment receives a combined signal over the shared spectrum in a time slot. The combined signal comprises the plurality of data signals. The combined signal is sampled at a multiple of a chip rate of the combined signal. The similar channel response is estimated. A channel response matrix or a channel correlation matrix is constructed based on in part the estimated channel response. A spread data vector is determined based on in part a fast fourier transform (FFT) decomposition of a circulant version of the channel response or channel correlation matrix. The spread data vector is despread to recover data from the matrix.

The invention relates to a method and a system of fault diagnosis of a rail transit based on an SVM (Support Vector Machine). The method comprises the following steps of collecting historical monitoring data and real-time monitoring data of the rail transit and transmitting the historical monitoring data and the real-time monitoring data to a data analysis server to carry out preprocessing, feature selection, data vectoring and model training, computing, analyzing and classifying the real-time monitoring data according to a classification model which is obtained through the historical monitoring data, judging whether a fault exists and obtaining a reason for generating the fault. The system comprises a data collection component, a data storage component, a data preprocessing component, a feature selection component, a data vectoring component, a model training component and a real-time data analysis component. According to the method and the system, manual judgment and analysis of the fault in mass monitoring signals can be replaced by an automatic monitoring manner, so that a large amount of labor cost and the time for analyzing the reason of the fault can be reduced for providing a time guarantee for subsequent jobs, such as maintenance and rescue.

A method and apparatus are provided for forming a measure of difference between two data vectors, in particular for use in a trainable data classifier system. An association coefficient determined for the two vectors is used to form the measure of difference. A geometric difference between the two vectors may advantageously be combined with the association coefficient in forming the measure of difference. A particular application is the determination of conflicts between items of training data proposed for use in training a neural network to detect telecommunications account fraud or network intrusion.

An adaptive radar processing system includes an antenna array for transmitting a radar signal and for receiving a return radar signal, and a signal processor programmed with an enhanced FRACTA algorithm (FRACTA.E). The basic FRACTA algorithm is enhanced to FRACTA.E with (any or all of) five enhancements, versions 1–5. Version 1 is a stopping criterion, for censoring samples, that is adaptive to a radar return data set. The inclusion of a stopping criterion improves the computational speed of FRACTA.E thereby improving its efficiency. Version 2 uses global censoring. Version 3 uses fast reiterative censoring. Version 4 uses segmenting of data vectors for AMF application. Version 5 uses Knowledge-aided covariance estimation (KACE) to reduce the required sample support that may be necessary in non-homogeneous environments, providing substantially the same level of detection performance with considerably less training data.

The invention provides a progressive health monitoring method for a cable system based on hybrid monitoring during generalized displacement of a support. Whether a mechanics calculation benchmark model of the structure requires to be updated against is decided by monitoring of a generalized coordinates of the structural support; considering the similar linear relationship among the current data vector of the monitored quantity and the initial value vector of the monitored quantity, the unit damage monitored quantity change matrix and the current nominal damage vector, in order to overcome the defects, a method using the linear relationship to approach the nonlinear relationship by section is adopted so that a large section is divided into a plurality of continuous small sections; the linear relationship in each small section is sufficiently accurate; and suitable algorithms such as a multi-objective optimization algorithm and the like can be utilized in each small section so as to calculate the non-inferior solution of the damage vector of the current cable, thus exactly determining the position and the damage degree of a damaged cable.

The present invention relates to a real-time wideband compressor for multi-dimensional data. The compressor comprises a plurality of compression engines for simultaneously compressing a plurality of data subsets of a set of input data vectors and providing compressed data thereof using one of SAMVQ or HSOCVQ data compression. Each compression engine comprises an along spectral vectors codevector trainer as well as an across spectral bands codevector trainer. The compression engines are programmable to perform either along spectral vectors codevector training or across spectral bands codevector training in combination with one of the SAMVQ or HSOCVQ techniques without changing hardware. The compressor further comprises a network switch for partitioning the set of input data vectors into the plurality of data subsets, for providing each of the plurality of data subsets to one of the plurality of compression engines, and for transmitting the compressed data. The real-time wideband compressor is highly advantageous in, for example, space applications by programmable enabling performance of different techniques of codevector training as well as different techniques of VQ. Furthermore, after the compression process is started the compression process is performed autonomously without external communication.

The present invention relates to a real-time wideband compressor for multi-dimensional data. The compressor comprises a plurality of compression engines for simultaneously compressing a plurality of data subsets of a set of input data vectors and providing compressed data thereof using one of SAMVQ or HSOCVQ data compression. Each compression engine comprises an along spectral vectors codevector trainer as well as an across spectral bands codevector trainer. The compression engines are programmable to perform either along spectral vectors codevector training or across spectral bands codevector training in combination with one of the SAMVQ or HSOCVQ techniques without changing hardware. The compressor further comprises a network switch for partitioning the set of input data vectors into the plurality of data subsets, for providing each of the plurality of data subsets to one of the plurality of compression engines, and for transmitting the compressed data. The real-time wideband compressor is highly advantageous in, for example, space applications by programmable enabling performance of different techniques of codevector training as well as different techniques of VQ. Furthermore, after the compression process is started the compression process is performed autonomously without external communication.

The invention discloses a heavy vehicle weight real-time identification method based on CAN information and a function principle. According to the method, when a vehicle runs, vehicle wheel speed, engine rotating speed, engine practical torque percentage, a gear position, accelerating pedal opening degree, a clutch pedal signal and a braking pedal signal are acquired through a vehicle CAN bus; engine torque, accelerated speed and a rotating weight conversion coefficient are obtained by computing; a vehicle longitudinal kinetic equation based on the function principle is established, on the basis of the kinetic equation, the work done by equivalent outer force generated by driving force and air resistance is regarded as system input quantity, the work done by the equivalent accelerated speed generated by the sum of rolling resistance, slope resistance and acceleration resistance is regarded as an observable data vector, and heavy vehicle weight is estimated in real time through a recursive least-squares method with which a forgetting factor is selected according to the feature of the vehicle weight.

The invention provides a method for predicting the service life of a screw pair of a numerical control machine on the basis of a performance degradation model. The method comprises the following steps of: acquiring vibration signals, carrying out time-frequency domain analysis, extracting the sensitive characteristic data vectors of the performance degradation of the screw pair, and forming a sensitive characteristic matrix in a time-sequence manner; calculating the load Pi of the screw pair and recording the operating time ti at the same time; calculating the rated life time Lhi, the total time t' that the screw pair has run under the current working condition, and the expected residual life LDi according to Pi, and forming an expected residual life vector T of the expected residual life in a time-sequence manner; and fitting the mapping relation between the inputted sensitive characteristic matrix and the expected residual life vector by using a degradation model formed by a double-layer dynamic fuzzy neural network, and outputting the prediction result of the service life. By taking the impact on the performance degradation of the screw pair caused by the load change thereof under various working conditions of the numerical control machine into consideration, the method of the invention can achieve the prediction of the residual life when the screw pair is used, and ensure the high prediction accuracy and high value in actual application.

The present invention provides a diversity transmission system. The diversity transmission system includes a method and system of diversity transmission through a wireless channel formed between multiple transmission antennae of a transceiver and a subscriber unit. The method includes forming a stream of symbols from an incoming data stream. A plurality of the symbols are selected forming a data vector. A maximum delay spread through the wireless channel is determined. The maximum delay spread is generally determined as a multiple of a sample time spacing between elements of the data vector. A plurality of diversity vectors are generated based upon the data vector and the maximum delay spread, each diversity vector includes a plurality of elements. Corresponding elements of the diversity vectors are simultaneously transmitted, each diversity vector transmitted from at least one corresponding antenna of a plurality of spatially separate antennae. This embodiment can further include repeatedly simultaneously transmitting corresponding elements of the diversity vectors until all elements of the diversity vectors have been transmitted, each diversity vector transmitted from at least one corresponding antenna of a plurality of spatially separate antennae.

The present invention provides a method of processing information prior to an emission from a multi-antenna device in a multi-user network having at least one user, said emission comprising transmission of a plurality of subcarriers comprising pilot symbols and data symbols, and said information being a data vector, the method comprising arranging said pilot symbols and said data symbols such that at least one of said plurality of subcarriers comprises at least one of said pilot symbols and at least one of said data symbols, wherein said data vector corresponds to said at least one of said plurality of subcarriers such that said data vector comprises data elements corresponding to said at least one of said pilot symbols and said at least one of said data symbols, precoding said data vector prior to transmission, and the precoding comprising applying a perturbation to said data vector in order to generate a perturbed data vector in which data elements corresponding to the pilot symbol remain unperturbed, and scaling said data vector by means of a precoding matrix.

A recognition system (10) incorporates a filterbank analyser (16) producing successive data vectors of energy values for twenty-six frequency intervals in a speech signal. A unit (18) compensates for spectral distortion in each vector. Compensated vectors undergo a transformation into feature vectors with twelve dimensions and are matched with hidden Markov model states in a computer (24). Each matched model state has a mean value which is an estimate of the speech feature vector. A match inverter (28) produces an estimate of the speech data vector in frequency space by a pseudo-inverse transformation. It includes information which will be lost in a later transformation to frequency space. The estimated data vector is compared with its associated speech signal data vector, and infinite impulse response filters (44) average their difference with others. Averaged difference vectors so produced are used by the unit (18) in compensation of speech signal data vectors.