735 results about "Linear correlation" patented technology

A method for recognizing an audio sample locates an audio file that most closely matches the audio sample from a database indexing a large set of original recordings. Each indexed audio file is represented in the database index by a set of landmark timepoints and associated fingerprints. Landmarks occur at reproducible locations within the file, while fingerprints represent features of the signal at or near the landmark timepoints. To perform recognition, landmarks and fingerprints are computed for the unknown sample and used to retrieve matching fingerprints from the database. For each file containing matching fingerprints, the landmarks are compared with landmarks of the sample at which the same fingerprints were computed. If a large number of corresponding landmarks are linearly related, i.e., if equivalent fingerprints of the sample and retrieved file have the same time evolution, then the file is identified with the sample. The method can be used for any type of sound or music, and is particularly effective for audio signals subject to linear and nonlinear distortion such as background noise, compression artifacts, or transmission dropouts. The sample can be identified in a time proportional to the logarithm of the number of entries in the database; given sufficient computational power, recognition can be performed in nearly real time as the sound is being sampled.

The present invention provides an improved method and system for real-time monitoring, validation, optimization and predictive fault analysis in a process control system. The invention monitors process operations by continuously analyzing sensor measurements and providing predictive alarms using models of normal process operation and statistical parameters corresponding to normal process data, and generating secondary residual process models. The invention allows for the creation of a fault analyzer directly from linearly independent models of normal process operation, and provides for automatic generation from such process models of linearly dependent process models. Fuzzy logic is used in various fault situations to compute certainty factors to identify faults and / or validate underlying assumptions. In one aspect, the invention includes a real-time sensor data communications bridge module; a state transition logic module; a sensor validation and predictive fault analysis module; and a statistical process control module; wherein each of the modules operates simultaneously.

The present invention provides means to improve the chemical stability of aqueous, parenteral pharmaceutical compositions comprising a polypeptide and glycerin. Reactive aldehydes are identified in commercial glycerins, and means for reducing such are provided. Convenient means are provided to assay for reactive aldehydes in glycerin, and a strong linear correlation between the level of reactive aldehydes in glycerin and chemical stability of compositions comprising a polypeptide and glycerin is demonstrated. The invention includes aqueous compositions comprising a polypeptide and glycerin having improved chemical stability compared to compositions previously known.

A method for recognizing an audio sample locates an audio file that most closely matches the audio sample from a database indexing a large set of original recordings. Each indexed audio file is represented in the database index by a set of landmark timepoints and associated fingerprints. Landmarks occur at reproducible locations within the file, while fingerprints represent features of the signal at or near the landmark timepoints. To perform recognition, landmarks and fingerprints are computed for the unknown sample and used to retrieve matching fingerprints from the database. For each file containing matching fingerprints, the landmarks are compared with landmarks of the sample at which the same fingerprints were computed. If a large number of corresponding landmarks are linearly related, i.e., if equivalent fingerprints of the sample and retrieved file have the same time evolution, then the file is identified with the sample. The method can be used for any type of sound or music, and is particularly effective for audio signals subject to linear and nonlinear distortion such as background noise, compression artifacts, or transmission dropouts. The sample can be identified in a time proportional to the logarithm of the number of entries in the database; given sufficient computational power, recognition can be performed in nearly real time as the sound is being sampled.

The invention discloses a vibration and audio signal-based high-speed train track damage detecting method, belongs to the field of signal detection and processing as well as safety monitoring, and solves the problems of low detection speed and single detection method in the conventional train track damage detection. The method comprises the following steps: 1, acquiring vibration signals and audio signals of a train track through sensors arranged at train track detection points; 2, respectively extracting information characteristics included in the vibration signals and the audio signals; 3, respectively obtaining a nonlinear correlation curve of the vibration signals and a nonlinear correlation curve of the audio signals by using a nonlinear correlation analysis method; 4, respectively analyzing the information of the two nonlinear correlation curves obtained in the step 3 so as to respectively obtain minimum values of the two nonlinear correlation curves; and 5, carrying out data fusion on the two minimum values and corresponding information thereof so as to obtain a damage coefficient, and looking up a table to obtain the damage degree according to the coefficient. The method is suitable for detecting the damage on railway train tracks and monitoring the safety operation of trains.

A method is disclosed for the automated synthesis of phase shifters. Phase shifters comprise circuits used to remove effects of structural dependencies featured by pseudo-random test pattern generators driving parallel scan chains. Using a concept of duality, the method relates the logical states of linear feedback shift registers (LFSRs) and circuits spacing their inputs to each of the output channels. The method generates a phase shifter network balancing the loads of successive stages of LFSRs and satisfying criteria of reduced linear dependency, channel separation and circuit complexity.

The invention discloses a method for automatically detecting a three-dimensional television (3DTV) video program format, which comprises the following steps of: 1, acquiring a frame image and judging whether the entropy of the frame image is greater than a first preset threshold value in the preset interval, if so, continuously executing, otherwise, returning; 2, equally dividing the frame image into n blocks; 3, respectively calculating linear correlation coefficients among the n blocks; 4, respectively judging whether a correlation coefficient of any two adjacent images in the n blocks is greater than a second preset threshold value, if so, adding one to a first counter, otherwise, adding one to a second counter; and 5, repeating 1 to (4m-1) times, if the first counter is m, the left and right three-dimensional format is obtained, if the second counter is m, the upper and lower three-dimensional format is obtained, otherwise, a two-dimensional format is obtained. In the method, whether the color is rich is judged according to the entropy of the image and the similarity between the images is judged according to the correlation coefficients between the image blocks, so the method is accurate and rapid.

The present invention provides an improved method and system for real-time monitoring, validation, optimization and predictive fault analysis in a process control system. The invention monitors process operations by continuously analyzing sensor measurements and providing predictive alarms using models of normal process operation and statistical parameters corresponding to normal process data, and generating secondary residual process models. The invention allows for the creation of a fault analyzer directly from linearly independent models of normal process operation, and provides for automatic generation from such process models of linearly dependent process models. Fuzzy logic is used in various fault situations to compute certainty factors to identify faults and / or validate underlying assumptions. In one aspect, the invention includes a real-time sensor data communications bridge module; a state transition logic module; a sensor validation and predictive fault analysis module; and a statistical process control module; wherein each of the modules operates simultaneously.

State estimation of a system having multidimensional parameters, which are unknown, arbitrarily time-varying, but bounded, in addition to state variables, is performed by initializing the state estimate and matrices representing its covariance and bias coefficients which linearly relate initial state estimation errors to the parameter errors. System matrices Φ, Γ, F, G and the mean value λ of unknown, time-varying, but bounded parameters λ are determined. A matrix Λ is generated, representing their physical bounds. The state estimate {circumflex over (x)}(k|k) and matrices M(k|k) and D(k|k), characterizing the effects of measurement errors and parameter uncertainty, are extrapolated to generate {circumflex over (x)}(k+1|k), M(k+1|k), and D(k+1|k). The measurement noise covariance N is determined. The filter gain matrix K is calculated. The state estimate is updated with the filter gain matrix K weighting the measurement z(k+1) and the extrapolated state estimate {circumflex over (x)}(k+1|k) to generate the current system estimate {circumflex over (x)}(k+1|k+1), by minimizing its total mean square error due to measurement errors and parameter uncertainty. The matrices M(k+1|k) and D(k+1|k) are updated with the filter gain matrix K to generate M(k+1|k+1) and D(k+1|k+1).

A monitoring device may include logic to receive arterial blood pressure data associated with a patient and receive tissue hemoglobin data associated with the patient. The logic may also calculate a linear correlation between the arterial blood pressure data and the tissue hemoglobin data. The correlation may be used to assess vascular reactivity.

An LDPC unit decoder included in a signal decoding device is provided with a parity checking unit that is a multiplier for performing multiplication of a check matrix (parity check matrix) and temporary estimated values of an encoded signal, computed by a temporary estimated value computation unit. A check matrix (parity check matrix) holding unit holds the check matrix (parity check matrix). If s and t are natural numbers, s≧t≧2, among s columns extracted from this check matrix (parity check matrix), t columns or less have a linearly independent relationship. These s columns are multiplied at locations where error occurrence frequency is relatively high, with regard to the temporary estimated values. According to this mode, the matrix is composed to include t columns that are linearly independent, that is, t columns that are not linearly dependent. In this way, in a decoded signal series, when errors occur at t locations, since it is possible to avoid multiplying all the linear dependent columns at locations where errors occur, errors with a relatively high frequency of occurrence can be preferably detected.

The invention relates to a new face-iris combination identifying method-characteristic layer extraction and combination. A face-iris characteristic extraction layer combining system is established according to nerve network, evolution calculation and fuzzy theory. For structure design, full and local geometry topological structure is adopted. A particle-group optimizing arithmetic is utilized to optimize network control parameters. When the characteristics of the face and the iris image are extracted, techniques of a super-resolution image reinforcing arithmetic, an illumination compensating arithmetic based on improved spherical harmonic function, gesture estimation based on linear relevant filters, Candide model based on a three-dimensional face and expression analysis based on an ASM arithmetic, etc., are adopted to robustly extract the eigenvectors of the face and the iris, and a self-developed double face-iris collecting device is also adopted to collect images of the face and the iris image. The method not only can establish a new system which is provided with learning capability and can automatically choose optimal network topological structure and automatically regulate net control parameters, but also can overcome and reduce the bad impacts of factors of environment and physiology, etc., during the extraction process to the independent characteristics of the face and the iris, thus effectively enhancing the identifying rate of the face-iris combination identification and promoting the system performance based on the face-iris combination identification to develop towards practical, reliable and acceptable directions.

Computer simulation of the dynamics of rigid bodies interacting through collisions, stacks and joints is performed using a constraint-based system in which constraints are defined in terms of the positions of the bodies. Displacements caused by reaction forces necessary to ensure that the bodies comply with the position constraints can be calculated and can be done iteratively by updating equations defining the reaction forces and the displacements such that the computation time and memory resources required to perform the calculations is linearly dependent upon the number of bodies and the number of contacts and joints between the bodies. Computational requirements and memory requirements are reduced further by performing the calculations using vector operations.

The method sets up sensing optical fiber on surface of prefabricated foundation pile to be measured. Both dependent variable and temperature sensed of the fiber are based on Brillouin backscattering. At incidence end of pulsed light, the method measures received light power of Brillouin backscattering so as to accomplish function of measuring and positioning Brillouin frequency shift on each points of optical fiber. In procedure of sinking pile, strain distribution is as basic parameter to reflect impaired character and degree of foundation pile. Based on linear correlation between Brillouin frequency shift and strain, temperature, the method carries out temperature compensation based on measured strain distribution and temperature distribution so as to obtain actual strain distribution on surface of foundation pile to be measured.

A channel estimation method and system using linear correlation based interference cancellation combined with decision-feedback-equalization (LCIC-DFE) are provided. The channel estimation method includes generating a first correlation sequence by calculating a linear correlation between a baseband sampled complex signal and a locally stored pseudo-noise signal and obtaining a second correlation sequence by iteratively removing inter-path interference from the first correlation sequence and generating a first channel impulse response (CIR) sequence based on the second correlation sequence. And, obtaining a third correlation sequence by removing random-data interference from the second correlation sequence based on the first CIR sequence and a feedback signal and generating a second CIR sequence based on the third correlation sequence.

A method and apparatus for compacting test responses containing unknown (X) values in a scan-based integrated circuit using an X-canceling multiple-input signature register (MISR) to produce a known (non-X) signature. The known (non-X) signature is obtained by selectively exclusive-ORing (XORing) together combinations of MISR bits which are linearly dependent in terms of the unknown (X) values using a selective XOR network.

The invention discloses a distributed optical fiber testing method for porous medium structure seepage. The method comprises the steps of: (1) constructing a porous medium structure model groove; (2) forming a uniform and steady seepage field; (3) conducting temperature monitoring on the target optical fiber embedded in the model groove; (4) carrying out ohmic heating operation on the target optical fiber; (5) measuring the temperature rise curves of different heating power under the steady seepage condition; (6) constructing a heat transfer equation of a total heat transfer coefficient of the optical cable; (7) representing the heat transfer between optical fiber and a seepage containing saturated porous medium by the total heat transfer coefficient; (8) measuring the temperature rise curves of different heating power under the condition of different seepage rates; and (9) monitoring the seepage rate. The method provided in the invention establishes an empirical relationship mathematical model of the seepage rate total heat transfer coefficient, accurately pinpoints the linear correlation between the seepage rate and an average total heat transfer coefficient, and reliably guarantees the monitoring precision.

The invention provides a multi-image encryption and authentication method based on sparse constraint and a system. The method comprises steps that multiple colorful images are respectively expressed as multiple quaternion matrixes; quaternion Gyrator transformation is employed to carry out double random phase encryption of the multiple quaternion matrixes to acquire multiple cryptograph data; according to the sparse matrixes, sparse expression of the multiple cryptograph data is carried out respectively to acquire multiple sparse cryptograph data; and components comprise real and imaginary components; the multiple sparse cryptograph data are superposed to acquire a final cryptograph; the final cryptograph is decrypted; and according to the decryption result and the to-be-detected images, non-linear correlation distribution is calculated to carry out authentication. The multi-image encryption and authentication method based on sparse constraint is advantaged in that relatively high security is realized, the cryptograph space and the operation time can effectively saved, and the method is suitable for being applied to image secret communication and authentication fields.

The invention relates to a quality evaluation model for natural ageing of redried strips and a building method thereof and belongs to the technical field of tobacco processing and quality evaluation. The building method includes: according to factors influencing quality changes during natural ageing of tobacco, determining a major quality evaluation index, performing screening by means of quantitative characteristic analysis, factor analysis, linear correlation and canonical correlation analysis to obtain quality evaluation indexes highly related to tobacco sensory evaluation quality, subjecting the quality evaluation indexes to factor analysis to obtain factor score coefficient matrixes, subjecting scores of common factors and the sensory evaluation quality to principal component regression to obtain a standard equation, substituting the score coefficient matrixes obtained by factor analysis, to the standard equation so as to obtain the equality evaluation model for the natural ageing of the redried strips. The method and the model are scientific and effective and good in stability, and index detection related is simple and fast and has small errors.

Computer simulation of the dynamics of rigid bodies interacting through collisions, stacks and joints is performed using a constraint-based system in which constraints are defined in terms of the positions of the bodies. Displacements caused by reaction forces necessary to ensure that the bodies comply with the position constraints can be calculated and can be done iteratively by updating equations defining the reaction forces and the displacements such that the computation time and memory resources required to perform the calculations is linearly dependent upon the number of bodies and the number of contacts and joints between the bodies.

The embodiment of the present invention provides a method and device of constructing a building energy consumption predication model. The method comprises the steps of obtaining an energy consumptioninfluence factor set; dividing the energy consumption influence factor set into a linear correlation influence factor set and a nonlinear correlation influence factor set; separately constructing thecorresponding Bayes network models; based on the corresponding Bayes network models, grouping into the first primary influence factors, the first secondary influence factors, the second primary influence factors and the second secondary influence factors; constructing the BP neural network training models; based on the training sample data, training the BP neural network training models separately; based on the preset test sample data, separately predicting and verifying the trained BP neural network training models, and outputting the prediction result values; if an error of the prediction result values is within a preset error range, outputting an energy consumption predication model of the linear correlation influence factors and an energy consumption predication model of the nonlinearcorrelation influence factors.

The invention relates to the technical field of data systems, in particular to a distributed data device, method and system based on the spatial correlation. The storage method includes the steps of dividing data with spatial characteristics into a plurality of grids, wherein the grids are provided with data of space where the grids are located; storing the data in the grids into a plurality of storage nodes according to the correlation relationship of the positions of the space of the grids. The distributed data device, method and system have the advantages that as for huge spatial data in various types, high-parallelism-degree data writing and reading can be achieved, and it is guaranteed that the data divided according to spatial attributes can be safely stored into the nodes in a balanced and spatial-correlation kept mode; meanwhile, the distributed data system has the high expanding capacity, the system expansion and the performance are linearly correlated, a large number of idler nodes or I / O bottle neck nodes can not appear in the system, and the original design intention of the distributed data system is achieved.

The invention discloses a method for forecasting public building air conditioner short-time base wire load with consideration of real-time weather factors. The method comprises the following steps: S1, calculating correlation between temperature, humidity, air speed, rainfall amount and the air conditioner load by using a Pearson correlation coefficient formula, and selecting strong linear correlation parameters as the real-time weather factors considered during forecasting of the public building air conditioner short-time load base wire; S2, respectively calculating the daily temperature-humidity index THI and a weighed temperature-humidity index THI of the forecasting date and two months before the forecasting date and selecting a typically-similar date of the forecasting date; and S3, calculating the air conditioner load value of 24 hours of the forecasting date by using a BP neural network method. The method can be used for forecasting the public building air conditioner short-time base wire load on a national scale and can also be used for providing theoretical support and data support for applying the typical public building air conditioner load to the regulation of power grid load.

An LDPC unit decoder included in a signal decoding device is provided with a parity checking unit that is a multiplier for performing multiplication of a check matrix (parity check matrix) and temporary estimated values of an encoded signal, computed by a temporary estimated value computation unit. A check matrix holding unit holds the check matrix. If s and t are natural numbers, s≧t≧2, among s columns extracted from this check matrix, t columns or less have a linearly independent relationship. These s columns are multiplied at locations where error occurrence frequency is relatively high, with regard to the temporary estimated values. According to this mode, the matrix is composed to include t columns that are linearly independent, that is, t columns that are not linearly dependent.

The method is suitable for the technical field of computer application, and provides a cloud platform resource utilization prediction method, terminal equipment and a computer readable storage medium.The method comprises the steps of obtaining historical use data of a cloud platform, determining the historical resource usage amount and the correlation between the usage moments; according to the correlation, adjusting the weight of a preset linear regression model and the weight of a preset neural network model; filing the acquired historical use data according to the monthly maximum value; determining whether the time and the usage amount are in linear correlation or not according to the calculated linear correlation coefficient; adjusting The weight of the two prediction models accordingto related conditions, and finally, predicting the usage amount of future preset time according to the two prediction models and the adjusted weight, so that the number of values participating in prediction and the number and types of the predicted values are simplified, and the efficiency and accuracy of the cloud platform resource usage amount prediction process are improved.

The invention discloses a device for monitoring and testing the seepage speed of a porous medium structural body. The device comprises a heating system (1), a distributed optical fiber temperature sensing system (2), a porous medium structural body model slot (3) and a water outlet system (4), wherein a monitoring optical fiber is buried in the porous medium structural body model slot (3), and the heating system (1), the distributed optical fiber temperature sensing system (2) and the water outlet system (4) are connected with the porous medium structural body model slot (3) respectively. The invention further discloses a method for monitoring and testing the seepage speed of the porous medium structural body. The method breaks the mode that in a conventional method for monitoring optical fiber seepage, the motoring period is the heating temperature rise period of the whole optical fiber, the linear dependence of the seepage speed and the average heat conduction coefficient is accurately located, and monitoring accuracy is reliably guaranteed.

The invention discloses a sea-sky-line detection method based on high gradient key points, and the method is suitable for ocean ship object identification and positioning devices. The method is characterized in that: based on a high efficiency attention mechanism of visual information, obtaining a statistical set of high gradient key points of an image column through employing a recursion optimization algorithm and a variable resolution sampling technique, subjecting the statistical set to least squares straight line fitting, rejecting outliers which do no satisfy a distance threshold condition in the statistical set and obtaining a selected set of the high gradient key points, subjecting the selected set to least squares straight line fitting, determining a selected set of the high gradient key points which satisfies an adaptive quantity threshold and a linear correlation threshold simultaneously as sea-sky-line. A problem of effective, accurate and real-time detection of sea-sky-line in a complex sea surface environment is solved by the sea-sky-line detection method based on high gradient key points, and the method has the characteristics of strong anti-interference capability and high calculating efficiency.

The invention relates to a method for judging abnormal electricity consumption behaviors of users based on an EEMD method. The method comprises the following steps of S1, carrying out cluster on electrical loads of the users by adopting a self-organizing map neural network method; S2, selecting one cluster from the clustering results of the step S1 at random and selecting any user in the cluster at random to obtain load data on any two identical time periods; S3, decomposing data in the step S2 into an IMF component and residual trend terms by adopting an empirical mode decomposition method; S4, carrying out linear correlation analysis on load residual terms of the two time periods respectively to obtain rho1 and rho2; S5, analyzing the rho1 and the rho2. The method for judging the abnormal electricity consumption behaviors of the users based on the EEMD method enables power supply enterprises to detect the abnormal behaviors in the electricity consumption process of the users, corresponding measures can be taken, and better services can be supplied to the users.