94 results about "Correlation ratio" patented technology

A method for correlating or finding similarity between two data sets. The method can be used for correlating two images with common scene content in order to find correspondence points between the data sets. These correspondence points then can be used to find the transformation parameters which when applied to image 2 brings it into alignment with image 1. The correlation metric has been found to be invariant under image rotation and when applied to corresponding areas of a reference and target image, creates a correlation surface superior to phase and norm cross correlation with respect to the correlation peak to correlation surface ratio. The correlation metric was also found to be superior when correlating data from different sensor types such as from SAR and EO sensors. This correlation method can also be applied to data sets other than image data including signal data.

A DSP checks the traffic on a control channel transmitted to each terminal, and obtains a total of traffic on the control channel for each remote radio unit. The DSP transforms a correlation matrix calculated in an analysis section to a partial orthogonal matrix subjected to partial orthogonalization. The DSP divides one or more remote radio units into the groups in accordance with the sequence of rows or columns of the partial orthogonal matrix so that the total traffic for each group in which the total of traffic is added for one or more remote radio units within the group may be less than or equal to a predetermined threshold, and stores the identification number of the remote radio unit for each group in a memory.

An engine ECU executes a program including a step of calculating coefficient of correlation K that is a value related to a deviation between a vibration waveform and a knock waveform model by comparing the engine's vibration waveform with the knock waveform model stored in advance at a plurality of timings, a step of calculating a knock intensity N as based on a largest coefficient of correlation K among the calculated coefficient of correlation Ks, a step of determining that the engine knocks if knock intensity N is larger than a predetermined reference value (YES at S108), and a step of determining that the engine does not knock if knock intensity N is not larger than a predetermined reference value (NO at S108).

A cell search timing synchronization method includes: performing cross-correlation operation for main synchronous signals kept by UE (user equipment) and received signals so as to obtain correlation sequences; segmenting the correlation sequences to obtain sequence segments corresponding to the correlation sequences; and computing a peak-to-average value of the sequence segment corresponding to each correlation sequence, and obtaining a timing synchronization position according to the maximum peak-to-average value of the correlation sequences. After application of the cell search timing synchronization method in the embodiment, cell search is accurately timed and completed in the presence of strong uplink interference signals.

Methods, searchers, base stations are provided which search for known codes contained in signals received over wireless channels, from mobile units for example. A coherent correlation is performed between an expected known code, and portions of the received signal during periods which are separated in time. Advantageously, by making the correlation periods separated in time, time diversity is realized such that if one or more of the correlation periods exist while the signal is of poorer quality, for example due to a fade, the remaining correlation periods may still yield a meaningful search statistic. Searching is done during time slots defined with reference to system time, not mobile unit time. Advantageously, this makes the searcher design simpler and more efficient. By performing time diversity searching in this manner, search tasks for one mobile unit(s) can be performed between the search task periods for another mobile unit resulting in a more efficient utilization of searcher resources.

The present invention discloses a low frequency oscillation identification method for accessing of wind power to a power grid in the technical field of wind power integration monitoring. The low frequency oscillation identification method comprises the steps that the system-wide linearized state matrix of a power system without a winder turbine generator is corrected, and a corrected system-wide linearized state matrix is obtained; eigenvalues and eigenvectors of the corrected system-wide linearized state matrix are figured out; the frequency, attenuation damping ratio and electromechanical circuit correlation ratio of the eigenvalues are worked out according to the eigenvalues and eigenvectors; and the eigenvalues are analyzed according to the frequency, attenuation damping ratio and the electromechanical circuit correlation ratio of the eigenvalues, and the low frequency oscillation mode of the accessing of the wind power to the power grid is determined. The low frequency oscillation identification method for the accessing of the wind power to the power grid solves the problems that an existing low frequency oscillation identification method does not take large-scale wind power accessing into consideration and cannot identity the system-leaded oscillation mode automatically.

The invention discloses a frequency domain weighting correlation method for image registration, which comprises the following steps of: windowing two images to be registered to acquire images for inhibiting frequency spectra from leaking; performing discrete Fourier transform on the images to acquire the frequency spectra and removing a high-frequency part from the frequency spectra of the images by using a low-pass filter; substituting the remaining frequency spectra into a phase weighting correlation expression to obtain a correlation peak frequency domain expression, performing inverse discrete Fourier transform to obtain the correlation peak of a pixel domain and finding coordinates with a maximum value to obtain the displacement value of the whole pixel; and performing binary quartic surface fitting on the periphery of a peak value, performing interpolation calculation to obtain the displacement value of a sub-pixel and adding the displacement value of the whole pixel and the displacement value of the sub-pixel to obtain the registration displacement of sub-pixel accuracy between the two images. The frequency domain weighting correlation method for the image registration has high registration accuracy on digital images and high robustness on scenes and signal-to-noise ratio, and is suitable for the field of the processing of various digital images.

The invention discloses an ultrasonic transit time calculation method based on envelope feature points of a cross-correlation function. The traditional ultrasonic transit time adopts the cross-correlation method, and calculates the transit time by using the maximum value of the cross-correlation function as the feature points. However, as the gas flow rate increases, the ultrasonic wave receivingwaveform will be distorted, causing the position of the maximum value of the cross-correlation function to drift at the same flow rate, and it is difficult to obtain an accurate transit time value. The invention proposes a new transit time calculation method by analyzing a large number of cross-correlation function waveforms. The method comprises: performing extremum extraction and normalization of each cross-correlation function waveform; finding the two maximum points where the difference between adjacent maxima is the largest; determining a feature point between two maximum points; calculating the transit time value by the feature point in the calculation. The experimental results show that the method overcomes the problem of small amplitude difference between the maximum value and theadjacent maximum value of the traditional cross-correlation algorithm, and improves the accuracy of the transit time calculation.

The invention discloses a large antenna directional diagram measuring method based on a correlation method, particularly for a rotatable large single antenna such as a radio parabolic telescope. By utilizing a correlation operation mode and an auxiliary antenna, a reasonable receiving manner is designed for measuring the directional diagram of an antenna to be measured, and the antenna directional diagram with high precision and wide angle range is obtained by utilizing the correction between the receiving signal of the antenna to be measured and the receiving signal of the auxiliary antenna. Appropriate measured parameters can be selected according to actual measurement conditions, so that the purposes of reducing the cost as much as possible, facilitating the measurement, improving the measurement accuracy and widening the measurement range are reached under the condition that the normal use of the antenna is not influenced. Directional diagram measurement is carried out on a large antenna rotatable in an external field, on one hand, the complicated measuring processes are eliminated, and on the other hand, the directional diagram of the antenna to be measured can be quickly measured under the condition of guaranteeing the measurement accuracy.

The invention provides an amphibious detector seismic data scaling factor retrieval method which includes: collecting and preprocessing water detector seismic data and land detector seismic data; calculating the weighted sum of root mean square amplitudes, self-correlation functions and cross-correlation functions of water detector seismic data and land detector seismic data; calculating the product of correlation functions and the product of the product of correlation functions according to the weighted sum; calculating the maximum variance modular equation coefficient according to the product of correlation functions and the product of the product of correlation functions; calculating the maximum variance module according to the maximum variance modular equation coefficient and scaling factors; determining the optimum scaling factor according to the maximum variance module; calculating the reflection coefficient according to the optimum scaling factor; drawing the optimum scaling factor and the profile of sub-bottom reflection coefficients and storing the optimum scaling factor and the sub-bottom reflection coefficients in a seismic data trace header.

The invention relates to a topological reconstruction method for a three-phase low voltage distribution network. The invention acquires the timing sequence voltage from a smart meter on the user sideon the basis of low voltage distribution network timing sequence voltage data. Firstly, the correlation analysis method is used to solve a correlation coefficient between each bus bar voltage data andthe reference voltage, and is identified as a phase with the largest correlation coefficient; a phase identification process is completed, phase connection information of each bus bar is acquired; all the bus bars are divided into three groups: A phase, B phase, and C phase according to different phases; the Chow-Liu algorithm is used to acquire cross correlation information (shown in the description) matrix among the three groups of bus bars; and then the cross-correlation information is used to complete the topology reconstruction of the three groups of undirected networks; and finally, thethree groups of reconstructed undirected networks are integrated to obtain a complete topology network structure.

The invention discloses a failure mode recognition method of an epicyclic gearbox using a mixed domain feature vector and grey correlation analysis. The method comprises the steps that (1) the feature parameters ft, ff, fs and ftf of the time domain, the frequency domain, the order domain and the time-frequency domain are extracted to constitute the mixed domain feature vector Fm, and the weighted values of wt, wf, ws and wtf of all the feature parameters are calculated; (2) the vibration monitoring health state of the epicyclic gearbox and the historical data of various failure mode states are acquired, and the corresponding mixed domain feature vector value mj(k) is calculated to be used as a reference state matrix; (3) the feature vector t of a signal to be detected and the row vector of the reference state matrix m are both used as the input of a grey correlation analysis algorithm; (4) the correlation vector of the feature vector t of the signal to be detected and the standard mode matrix m is calculated to be used as an output vector of the grey correlation analysis algorithm. The failure mode recognition method of the epicyclic gearbox using the mixed domain feature vector and grey correlation analysis has the advantages of being simple in principle, simple and convenient to operate, stable and reliable, high in precision, suitable for high interference and varied working conditions and the like.

Improved correlation techniques employ data from forward (template-to-reference) and reverse (reference-to-template) correlation to identify valid correlation peaks, enforce symmetry in correlation peaks, and/or combine forward and reverse correlation data. In embodiments, these techniques eliminate or reduce rms noise in a recovered signal peak location by enforcing correlation peak symmetry. The forward and reverse correlation methods described herein may be used for validation of correlation peaks, detection of outlier data points and improved interpolation, such as for higher accuracy localization of a peak center with sub-pixel resolution.

It is an aim image automatic identifying and rapid tracing method, which comprises the following steps: first to establish aim image valve grey scale grade; second to establish error and correlation index; then to form mode image and spot image characteristics matrix on the base of valve value grey scale and to form correlation functions under the condition of discreteness, such as variance, normalization correlation index, inner product operation in the linear space of all two-dimension matrix; to get the correlation definition according to norm and angle in the Euclidean space starting from the linear space; then to get a judge formula by use of inner product definition to realize the rapid identification of the aim.

The invention discloses a mass small file access optimization method based on Ceph. When a user stores files, correlation groups of small files are obtained through utilization of a K-means clusteringalgorithm. The files in each group are sequenced according to a descending order. Correlation files in the correlation groups are combined and then are stored to the Ceph. When the user initiates anaccess request, a system checks whether requested files are in a cache or not. If the requested files are in the cache, the requested files are directly read and returned. If the requested files are not in the cache, request information is sent to a Ceph cluster. The small files are read. The small files are pre-obtained and cached according to a utilization rate and a correlation ratio among fileblocks, the requested files are returned, and the small files are pre-obtained. According to the method, the interaction between the user and the cluster is reduced, the user access time is reduced,the access efficiency of the mass small files is improved, and the integrated performance of the system is improved.

Techniques are provided for fine-tuning estimates of a delay value for a sampled signal. One aspect of the invention is to perform, for the sampled signal, coarse-grained calculations of the In Phase and Quadrature (I and Q) correlation integrals at a limited number of points, wherein the calculations are performed over a range of hypothesized delay values. A range of delay values of interest are then determined from the coarse-grained calculations of the I and Q correlation integrals. A subset of I and Q values based on the coarse granularity calculations of the I and Q correlation functions is used to perform a time-domain interpolation to obtain fine-grained values of the I and Q integrals in the range of the delay values of interest. Magnitude calculations are performed based on the fine-grained values of the I and Q integrals. Fine-tuned estimates of delay value are based on the magnitude calculations. Alternatively, fine-tuned estimates of delay value are based on the template-matching approach.

The invention discloses an energy-saving control method, comprising the steps of constructing a model, and constructing a thermodynamic model of a device group. Data receiving step of receiving operation data of a device group and obtaining a corresponding unit time load rate data group according to the operation data; Policy generation steps, EER load rate data set and power consumption are obtained by that thermodynamic model, the EER load rate data set is the correlation ratio data of the refrigeration energy efficiency ratio and the load rate, and each unit time load rate in the unit timeload rate data set and the EER load rate data set or power consumption are optimized and matched to obtain the energy-saving control strategy of the equipment set. The EER load rate data set is the correlation ratio data of the refrigeration energy efficiency ratio and the load rate. The invention also discloses an electronic device, a computer-readable storage medium, an energy-saving control device and a system. The invention collects the big data of the running equipment connected with the system, and makes concrete analysis on the data of the actual running situation of the collected running equipment, so as to adjust the running strategy in time to achieve the energy-saving control effect.

A detection and synchronization device of IEEE 802.11a or HiperLan2 frame head is featured as utilizing match filter to carry out inter-correlation operation on short Preamble series for obtaining a correlation series, determining that standard signal consistent to IEEE 802.11a or HiperLan2 is detected out and seeing that synchronous position can be confirmed preliminarily according to it if specific correlation peak value situation is obtained i.e. wave peak appeared in equal distance continuously and then no wave peak exceeding threshold in the same distance.

The invention discloses a method for predicting the futures price of rapeseed oil, which relates to the technical field of data mining and price prediction. The invention comprises the following steps: selecting factors affecting the futures price of rapeseed oil according to relevant prior knowledge; collecting time series of relevant factors information to obtain the original data; process the original data to obtain the transaction behavior sequence of the relevant main contract; carry out gray correlation analysis on the original data of the main contract, and discard the influencing factors with a lower degree of correlation; divide the reserved influencing factor sequence into training set and The test set is input to the BP neural network for training steps; the trained BP neural network model is used for prediction. The invention introduces other price influencing factors except trading behavior into the rapeseed oil futures price prediction, so that the rapeseed oil futures price prediction is more credible and stable, and can make short-term predictions on the closing price of the rapeseed oil futures.