121 results about "Recursive computation" patented technology

Estimating remaining capacity and remaining time of a battery device during discharging of the battery device includes determining initial state of charge of the battery device, determining discharge current of the battery device, utilizing a shooting end of discharge process to determine final state of charge corresponding to the discharge current, and determining the remaining capacity and the remaining time according to the final state of charge, the method in the invention compared with the prior art, is advantaged by less influence of estimation result of remaining capacity and run-time by discharge current, smaller estimation error, and less required recursive computation amount, namely, quicker and more accurate estimation operation.

The detection of electromechanical oscillations in power systems and the estimation of their parameters (frequency ƒ and damping ξ) is based on a linear time-varying model. The parameters of the linear model are on-line adapted by means of Kalman filtering techniques to approximate the measured signal y (representing the behaviour of the power system) optimally in the sense of a quadratic criterion. The estimated model parameters are then the basis for the calculation of parameters of the oscillations. Adaptive algorithms are based on a recursive calculation of the estimated parameter vector for each time-step based on the new value of the measured signal and the old values of the estimated parameters. As opposed to the collection of data over a time window and then performing the parameter identification at once, any change in the system can thus be detected much faster.

A fault detection method in a continuous annealing process based on a recursive kernel principal component analysis (RKPCA) is disclosed. The method includes: collecting data of the continuous annealing process including roll speed, current and tension of an entry loop (ELP); building a model using the RKPCA and updating the model, and calculating the eigenvectors {circumflex over (p)}. In the fault detection of the continuous annealing process, when the T2 statistic and SPE statistic are greater than their confidence limit, a fault is identified; on the contrary, the whole process is normal. The method mainly solves the nonlinear and time-varying problems of data, updates the model and calculates recursively the eigenvalues and eigenvectors of the training data covariance by the RKPCA. The results show that the method can not only greatly reduce false alarms, but also improve the accuracy of fault detection.

The method of predicting tag detection probability for RFID framed slotted ALOHA anti-collision protocols is uses recursive calculations to accurately estimate the probability of discovering RFID tags in a multiple rounds discovery system. First, the method estimates the probability of detecting a given number of tags in a single round. Then, using a probability map, the method estimates the probability of detecting the given number of tags in multiple rounds. The probabilities are used to adjust the number of slots in a frame and the number of interrogation rounds used by the RFID tag reader to minimize collisions and optimize tag reading time.

The invention relates to the communication field and provides a method and a device for requesting a computing path in multiple-domain networks. The method for requesting a computing path in multiple-domain networks, which is provided by the embodiment of the invention, comprises the following steps: receiving a path computing request message, wherein the path computing request message carries PCE information and domain information of a path computing unit, and the domain information corresponds to the PCE information; acquiring the information of a boundary route device according to the domain information; and implementing PCE-based backward recursive computation by using the information of the boundary route device. By using the method and the device provided by the embodiment of the invention, the path computing request message received by PCE carries the PCE information and the domain information, so the information of the boundary route device, which is needed for BRPC computation, can be acquired, and BRPC can be used for realizing the computation of cross-domain paths.

The invention relates to a penicillin fermentation process failure monitoring method based on recursive kernel principal component analysis (RKPCA), which belongs to the technical field of failure monitoring and diagnosis. The method comprises the following steps: acquiring the ventilation rate, stirrer power, substrate feed rate, substrate feed temperature, generated heat quantity, concentrationof dissolved oxygen, pH value and concentration of carbon dioxide; and establishing an initial monitoring model by using the first N numbered standardized samples, updating the model by a RKPCA method, and computing the characteristic vectors to detect and diagnose the failure in the process of continuous annealing, wherein when the T2 statistics and SPE statistics exceed the respective control limit, judging that a failure exists, and otherwise, judging that the whole process is normal. The method mainly solves the problems of data nonlinearity and time variability; and the RKPCA method is used for updating the model by carrying out recursive computation on the characteristic values and characteristic vectors of the training data covariance. The result indicates that the method can greatly reduce the false alarm rate and enhance the failure detection accuracy.

The invention discloses an EKF-based rotating speed control method of a sensorless ultra-high speed permanent magnet synchronous motor. The method comprises the following steps of building a mathematical model of the motor and converting the mathematical model into a state equation; carrying out linearization and discretization, substituting the discrete linear state equation into an extended Kalman filter (EKF) for recursive computation, updating a variance matrix P and a gain K in the EKF in real time to update a state variable; and finally estimating the rotating speed of the motor in the dynamic operation process in real time. The rotating speed estimation method is applied to an SVPWM-based ultra-high speed motor direct torque control system; the adaptivity of the system is improved by a fuzzy PID controller; and fast, stable and reliable rotating speed control on the ultra-high speed permanent magnet synchronous motor is effectively achieved.

A processor executes a mask update instruction to perform updates to a first mask register and a second mask register. A register file within the processor includes the first mask register and the second mask register. The processor includes execution circuitry to execute the mask update instruction. In response to the mask update instruction, the execution circuitry is to invert a given number of mask bits in the first mask register, and also to invert the given number of mask bits in the second mask register.

The invention relates to a fault detection method of an unmanned aerial vehicle flight control system. Online detection of the fault of the actuator and the sensor of the fixed-ring unmanned aerial vehicle flight control system can be realized by the method. An unmanned aerial vehicle flight control system continuous nonlinear fault model is established on the basis of the unmanned aerial vehiclekinetic equation and the fault type; and then the unmanned aerial vehicle flight control system continuous nonlinear fault model is converted into an unmanned aerial vehicle flight control discrete time-varying fault model with the help of a nonlinear observer, and unmanned aerial vehicle flight control system fault detection is realized by using an equivalent space method. The robustness indicator is designed by aiming at the problem of poor robustness of the conventional equivalent space method under unknown interference so as to enhance the robustness of system fault detection. The extendedKalman filtering equation is utilized in the Krein space to realize recursive computation of the residual evaluation function to reduce the computational burden by aiming at the problem of high computational burden of online fault detection of the conventional equivalent space method. According to the method, quick alarm of the fault of the sensor and the actuator of the unmanned aerial vehicle can be realized so as to provide an effective basis for fault detection of the unmanned aerial vehicle flight control system.

The invention relates to a power system harmonic state estimation method, in particular, a distributed correlation Kalman filtering-based power system harmonic estimation method. The method includes the following steps of: (1) acquiring response signal data z(n) of a power system; (2) establishing a state space model of power system response sampling signals; (3) determining the value of the correlation coefficient zeta ij of neighbor nodes; (4) obtaining a state vector estimation value X^(K) at a time point k based on recursive computation through adopting a distributed correlation Kalman filtering algorithm; and (5) extracting the amplitude and phase of harmonics at the time point k. According to the distributed correlation Kalman filtering-based power system harmonic estimation method provided by the invention, the characteristics of the harmonic state of the power system are fully considered, and therefore, compared with traditional Kalman filtering communication, the distributed correlation Kalman filtering-based power system harmonic estimation method has the advantages of low communication cost, excellent anti-disturbance performance and higher estimation accuracy, and thus, a better data base can be provided for the elimination of harmonic components. The method provided by the invention can be conveniently applied to the harmonic state estimation of the power system.

Compile-time recognition of graph structure where graph has arbitrary connectivity and is constructed using recursive computations is provided. In one aspect, the graph structure recognized at compile time may be duplicated at runtime and can then operate on runtime values not known at compile time.

The invention discloses a method for mining enterprise data in supply chain finance. The method comprises the following steps of: acquiring tax involved data of enterprises in a tax bureau system; respectively determining an upstream and downstream enterprise list of each enterprise in N enterprises, wherein the N enterprises belong to a same industry; respectively carrying out recursive computation on transaction data between each enterprise in the N enterprises and tax payers in the respective upstream and downstream enterprise list, so as to obtain transaction information corresponding to the N enterprises, wherein the transaction information of each enterprise comprises upstream transaction data and downstream transaction data of the enterprise; and determining all the core enterprises by utilizing the transaction information corresponding to the N enterprises. According to the method, the core enterprise data obtaining efficiency is improved, and the finally obtained core enterprise data is more correct and objective. Moreover, the invention correspondingly discloses an enterprise data mining system.

In one aspect, the present invention provides a dynamic super-resolution technique that is computationally efficient. A recursive computation takes as input a previously computed super-resolved image derived from a sequence of low-resolution input frames. Combining this super-resolved image with a later low-resolution input frame in the sequence, the technique produces a new super-resolved image. By recursive application, a sequence of super-resolved images is produced. In a preferred embodiment, the technique uses a computationally simple and effective method based on adaptive filtering for computing a high resolution image and updating this high resolution image over time to produce an enhanced sequence of images. The method may be implemented as a general super-resolution software tool capable of handing a wide variety of input image data.

The invention discloses a single phase locking device. In the device, a Kalman filter is used for combing a zero crossing point detection phase locker and a DQ coordinate system phase locker and performing Kalman filtration on frequency values, phase positions and amplitude values sent by the zero crossing point detection phase locker and the DQ coordinate system phase locker so as to obtain a final phase position, a final amplitude and a final frequency. The invention also discloses a single phase locking device which can realize a rapid and accurate phase locking function on an input signal sent by a single-phase electrical system by utilizing the advantages that sampling errors can be greatly eliminated due to the Kalman filtration and the recursive computation is high in response speed, so that the device is far better than a traditional phase locking ring in dynamic performance and static performance, overcomes the shortcomings that a traditional single phase locking method is low in speed and easy to affect, and realizes a rapid and accurate phase locking function on the phase position, amplitude and frequency of an input signal of a single-phase power grid.

The invention discloses an on-line sequence data prediction method and device. The prediction method includes: constructing an interval type-2 intuitionistic loop fuzzy neural network model; and training the interval type-2 intuitionistic loop fuzzy neural network model. The special procedure is as follows: recursively updating an average and an standard deviation to standardize sequence data samples; selecting an intuitionistic fuzzy set fuzzy rule on the basis of a dynamic clustering method of recursive computation of an approximate density center; inputting the standardized sequence data samples into the interval type-2 intuitionistic loop fuzzy neural network model with the selected intuitionistic fuzzy set fuzzy rule, outputting a sequence data prediction result, and determining whether the sequence data prediction result meets a preset precision requirement or not; completing training of the interval type-2 intuitionistic loop fuzzy neural network model; otherwise, updating an output weight, a feedback weight, an intuitionistic fuzzy set fuzzy rule center and a point difference until the output prediction result reaches the preset accuracy requirement; and inputting on-line sequence data into the trained model to obtain a prediction result.

This invention describes a quick 3D-to-2D point matching algorithm. The major contribution is to substitute a new O(2n) algorithm for the traditional N! method by introducing a convex hull based enumerator and projecting a 3D point set into a 2D plane yields a corresponding 2D point set. In some cases, matching information is lost during the projection. Therefore, to compute projection parameters, the recovery of the 3D-to-2D correspondence is important. Traditionally, an exhaustive enumerator permutes all the potential matching sets and a calibration computation is used to choose the lowest residual error computed parameters as “correct” one. Our enumerator shrinks the search space by computing the convex hull for both 2D and 3D points set, validating the potential matching cases with a horizon validation and, finally, applying recursive computation to further reduce the searching space.

The invention discloses a speech signal endpoint detection method based on dynamic cumulant estimation, including sliding window-based high-order cumulant recursive computation and sliding window kurtosis-based endpoint detection. The sliding window-based high-order cumulant recursive computation includes: adding a rectangular window to original sample data, subjecting intra-window data to cumulant estimation, updating the intra-window data each time when one sample point is slid, and thus dynamically estimating the cumulant. The sliding window kurtosis-based endpoint detection includes: computing sliding window kurtosis and energy features by the use with the sliding window-based high-order cumulant recursive computation, thus subjecting speech signals to endpoint detection. Compared with the prior art, the method has the advantages that endpoint detection is based on sliding window kurtosis and energy double-threshold, the sliding window kurtosis is highly sensitive to the start point of a speech segment, resistance to noise interference is better, and the method is of better robustness in the noise environment.

An order-preserving encryption (OPE) encryption method receives a plaintext (clear text) and generates a ciphertext (encrypted text) using a software arbitrary precision floating point libraries during initial recursive computation rounds. In response to the ciphertext space reducing to breakpoint, the OPE encryption method continues computations using a hardware floating point processor to accelerate the computation. In this manner, the OPE encryption method enables efficient order preserving encryption to enable range queries on encrypted data.

The invention discloses a time varying network link packet loss probability estimation method based on a Kalman filter. The time varying network link packet loss probability estimation method based on the Kalman filter mainly comprises a training phase and an estimation phase. In the training phase, a source node sends back-to-back detection packets to multiple destination nodes so as to obtain path data, then, prior information of time varying link packet loss probability is estimated according to the path data, and a state transition equation of the Kalman filter is established. In the estimation phase, under the condition that the detection packets do not need to be sent, recursive computation and estimation of the time varying link packet loss probability are completed through a feedback control method according to the state transition equation and the path data obtained from network background flow. Due to the fact that a Kalman filter module is introduced to estimate the link packet loss probability of a time varying network, an obtained link packet loss probability estimated result has a minimum mean square error as well as high estimated accuracy, and the time-variation characteristic of the time varying network link packet loss probability can be reflected in real time.

The invention discloses a method for analyzing the velocity vector of a flow field of a heart based on a gray scale ultrasound image. The method is characterized by comprising the following steps of: dividing the gray scale ultrasound image into a grid unit; selecting a pixel point of which the pixel is closest to the average scale value in each cell of the grid unit, wherein the pixel point is used as a control point, and updating the gray value of the gray scale ultrasound image by an interpolation algorithm to fulfill the aim of removing speckle noise; and calculating by an optical flow method to obtain the heart flow field movement vector of the denoised gray ultrasound image. According to the method, multiple times of recursive computation is not needed in the interpolation algorithm process, and speckles can be removed and preprocessed in real time; and a calculation result is closest to the actual condition, and detailed information of flow such as eddy can be accurately acquired.

The invention discloses a near space circular synthetic aperture radar rapid back-direction projection imaging method. In view of the problem of near space circular synthetic aperture radar rapid imaging, the method replaces a phase error in coherent imaging method with a pixel amplitude error as the evaluation criterion of imaging precision, approximately expands through low order of Green function which is based on chebyshev nodes and lagrange interpolation according to the principle of minimum mean square error, switches the problem of calculation of sub aperture projection to the problem of calculation of limited number of approximate expansion coefficients, and reduces as much as possible the number of expansion coefficients under the condition of meeting the focusing accuracy so that algorithm computational complexity is reduced, and then accomplishes the imaging from coarse focusing to fine focusing by applying recursive computation. Compared with the existing circular SAR back-direction projection imaging method, the near space circular synthetic aperture radar rapid back-direction projection imaging method has the advantages that computing speed is greatly improved, big scene imaging is achieved and imaging accuracy is much higher.

A dual evaluation mode method for use with computer software that includes the acts of determining, for certain functions and expressions within input computer code, whether each function and expression may have any recursive dependencies, generating eager evaluation mode executable code for one or more elements of the input computer code based on the act of determining and providing both eager evaluation mode executable code and non-eager evaluation mode executable code to runtime software that supports both eager and non-eager evaluation modes.

A subtraction image is obtained, by a subtraction process (DSA process), from a live image and a mask image. A lag-behind part included in each X-ray detection signal is considered due to an impulse response formed of exponential functions. The lag-behind part is removed from each X-ray detection signal by a recursive computation to obtain a corrected X-ray detection signal. The live image and mask image are obtained from such corrected detection signals.

Corrected X-ray detection signals are obtained by removing lag-behind parts through a recursive computation based on initial values determined from lag signal value (step T 2). Thus, the lag-behind parts can be removed by taking into consideration lag signal values remaining at a starting point of the recursive computation. The lag signal values are dependent on the characteristic of an FPD (flat panel X-ray detector). By removing the lag-behind parts, with the lag signal values taken into consideration, the lag-behind parts are removed from X-ray detection signals with increased accuracy, without being influenced by the characteristic of the FPD.

A radiographic apparatus obtains lag-free radiation detection signals with lag-behind parts removed from radiation detection signals taken from a flat panel X-ray detector as X rays are emitted from an X-ray tube. The lag-behind parts are removed by a recursive computation on an assumption that the lag-behind part included in each X-ray detection signal is due to an impulse response formed of exponential functions, N in number, with different attenuation time constants. X-ray images are created from the lag-free radiation detection signals.

Compile-time recognition of graph structure where graph has arbitrary connectivity and is constructed using recursive computations is provided. In one aspect, the graph structure recognized at compile time may be duplicated at runtime and can then operate on runtime values not known at compile time.