174 results about "Criterion function" patented technology

A scheme to design an audio precompensation controller for a multichannel audio system, with a prescribed number N of loudspeakers in prescribed positions so that listeners positioned in any of P>1 spatially extended listening regions should be given the illusion of being in another acoustic environment that has L sound sources located at prescribed positions in a prescribed room acoustics. The method provides a unified joint solution to the problems of equalizer design, crossover design, delay and level calibration, sum-response optimization and up-mixing. A multi-input multi-output audio precompensation controller is designed for an associated sound generating system including a limited number of loudspeaker inputs for emulating a number of virtual sound sources. Method includes: estimating, for each loudspeaker input signals, an impulse response at each of a set of measurement positions that cover the P listening regions; specifying a target impulse response (target stages) for each virtual sound source at each measurement position; and determining adjustable filter parameters of the audio precompensation controller so that a criterion function is optimized.

A static code analysis (SCA) tool, apparatus and method detects, prioritizes and fixes security defects and compliance violations in SAP® ABAP™ code. The code, meta information and computer system configuration settings are transformed into an interchangeable format, and parsed into an execution model. A rules engine is applied to the execution model to identify security and compliance violations. The rules engine may include information about critical database tables and critical SAP standard functions, and the step of applying the rules engine to the execution model may include the calculation of specific business risks or whether a technical defect has a business-relevant impact. In particular, an asset flow analysis may be used to determine whether critical business data is no longer protected by the computer system. Such critical business data may include credit or debit card numbers, financial data or personal data.

Feature attributes are extracted from an observation space to create feature vectors for each class to be identified. A linear transformation matrix is used to reduce the dimension of the feature vectors. A numerical optimization algorithm maximizes a geometric criterion function in order to calculate the linear transformation matrix, where it exploits the geometry of the class contours of constant density. Next, a classifier based on the feature vectors in a lower dimension is generated and a class is determined for the data represented.

In accordance with an embodiment of the invention, a method for measuring pitch in data obtained from metrology and imaging systems is provided. A data set from a metrology or imaging instrument is obtained. The data set is converted into digital format if not already in that format. The digitized data set is mapped into a one-dimensional profile data if the digitized data set is not already one-dimensional. The one-dimensional profile data denoted by f(x) is a function of x position values corresponding to equally spaced or nearly equally spaced pixels. A criteria function g(T) is constructed as a one-dimensional data array from the profile data f(x) or any of its derivatives and a translation of the profile data f(x) denote by f(x+T) or any of its derivatives. Here, T represents the amount of translation, and g(T) is a function of T translation values corresponding to equally spaced or nearly equally spaced pixels. A value of translation T is then determined either as a whole pixel or with subpixel interpolation such that the magnitude of g(T) would be either a maximum or a minimum whichever appropriate at said value, wherein the determined value is not zero. The determined value is then reported as the pitch in the data set.

The invention relates to a generative adversarial network-based remote sensing image thin cloud removal method. The method includes the following steps that: step 1, a thin cloud removal system modelis established; step 2, a network model is designed; step 3, an identification criterion function is constructed; step 4, the thin cloud removal system performs identification; and step 5, thin cloudsin a remote sensing image are removed. According to the method of the invention, the generative adversarial network is adopted to construct the model of an image thin cloud removal problem and perform system identification on the model, thereby realizing end-to-end thin cloud removal; and the constructed criterion function combines the errors of data distribution and reconstruction accuracy, so that the system can better learn the characteristics of data, thus, achieving the removal of the thin clouds. The method provided by the invention has a capacity to adaptively remove uneven thin clouds. With the method adopted, a restored image has high color and texture consistency.

The invention relates to a method for detecting a DDoS (Distributed Denial of Service) attack in a big data environment. The method comprises the following steps: extracting a source IP address from various collected data streams, calculating information entropy of the source IP address, and if the information entropy is greater than a preset threshold value V, determining that the data stream corresponding to the IP address may be a DDoS attack stream, and implementing early warning; otherwise, determining that the data stream corresponding to the IP address is a normal data stream; training a dynamically-sampled K-Means model by using the normal data stream, and designing a dynamically-sampled K-Means parallelization algorithm based on a Spark stream processing technology; and detecting the data stream subjected to early warning by using the dynamically-sampled K-Means parallelization algorithm, and if a criterion function E of a detection result is smaller than or equal to a preset threshold value d, determining that the data stream is the DDoS attack stream, then blacklisting the source IP, and shielding the data stream. According to the method disclosed by the invention, various DDoS attacks in the big data environment can be effectively detected through early warning detection and abnormality confirmation detection, and thus the security of a system can be ensured.

Methods to match certain context of commands directed to a network technology or a network design from configuration files and a user interface to display these results. A language with the simple syntax similar to the human language is provided. The language includes rules to define the parameter and syntax for the parameter operations and also standard functions to parse commands. A script file can be conveniently written in this language to filter the desired contexts from a configuration file. In the exemplary embodiment, the system translates the script file to an executable standard Perl programming and Perl programming is run with the configuration file as the input. The result is displayed in the graphic user interface, which is designed to work with an interactive network topology map.

The invention concerns digital audio precompensation, and particularly the design of digital precompensation filters. The invention proposes an audio precompensation filter design scheme that uses a novel class of design criteria. Briefly, filter parameters are determined based on a weighting between, on one hand, approximating the precompensation filter to a fixed, non-zero filter component and, on the other hand, approximating the precompensated model response to a reference system response. For design purposes, the precompensation filter is preferably regarded as being additively decomposed into a fixed, non-zero component and an adjustable compensator component. The fixed component is normally configured by the filter designer, whereas the adjustable compensator component is determined by optimizing a criterion function involving the above weighting. The weighting can be made frequency- and / or channel-dependent to provide a very powerful tool for effectively controlling the extent and amount of compensation to be performed in different frequency regions and / or in different channels.

Device and method for separating a mixture of source signals to regain the source signals, the device and method being based on measured signals, the invention comprises: bringing each measured signal to a separation structure including an adaptive filter, the adaptive filter comprising filter coefficients; using a generalized criterion function for obtaining the filter coefficients, the generalized criterion function comprising cross correlation functions and a weighting matrix, the cross correlation functions being dependent on the filter coefficients; estimating the filter coefficients, the resulting estimates of the filter coefficients corresponding to a minimum value of the generalized criterion function; and updating the adaptive filter with the filter coefficients.

The invention discloses an iterative optimization distance categorization-based space weak and small target detection method, which is used for solving the technical problem that the existing space weak motion target detection method is low in detection efficiency. The technical scheme of the method comprises the steps: extracting a plurality of candidate targets by a method based on the iterative optimization distance categorization; constructing an error square and a criterion function; categorizing all star points into fixed stars and non-fixed stars; iteratively computing a class mean andan error square function to obtain an optimization distance categorization threshold value; and filtering out the great mass of fixed star backgrounds and noise points, so that the complexity of the successor operation is reduced. A correlation method of a target track is used in the process of filtering the candidate targets, so that the computing complexity of the algorithm is reduced, and the detection efficiency of the space weak motion target is improved.

The invention relates to a system (200) for delineating an anatomical structure in an image computed from a slice of image data, the system (200) comprising a partition unit (210) for partitioning the image into a plurality of image portions, each image portion depicting a portion of the anatomical structure, and an adaptation unit (220) for adapting a template to the image based on a criterion function, the criterion function being a function of template parameters and of image values and their relative positions in the image, and on a criterion to be satisfied by a computed value of the criterion function, wherein the criterion function is defined on the basis of the plurality of image portions. Having a criterion function defined on the basis of the plurality of image portions allows computing optimal contributions to the criterion function value within each portion of the image. This is proven to be particularly useful for extracting myocardial contours in a slice of the LEMR short-axis volume image data in the presence of scar tissues. The invention allows optimizing the treatment of portions of the image comprising scar tissue in the myocardium.

The invention discloses an anti-signal-dependent-interference cognitive constant modulus waveform design method, belongs to the technical field of radar anti-interference and especially relates to the technical field of waveform design and interference suppression. Existing anti-clutter and anti-electronic-interference waveform design criterion functions are mainly based on detection probability and signal-to-clutter ratio and the like, so that for different time delay interference, waveforms need to be redesigned, and besides, quick time forwarding type interference cannot be suppressed. The method adopts an in-pulse subpulse phase modulation waveform design mode to suppress the fast / slow forwarding type SD interference, and is characterized by, to begin with, establishing an interference suppression signal model by utilizing the idea of suppressing cross correlation between interference signals and emission signals, and on the basis of suppressing interference, suppression of auto-correlation sidelobe level and constant modulus constraints being taken into consideration; and then, for an established target problem function, providing a majorization-minimization iteration search optimization algorithm for simplification solving. The method can suppress SD interference very well and can keep low-sidelobe radar detection requirements.

The invention belongs to the technical field of network security, and particularly relates to a moving target defense decision selection method, device and system based on a Markov time game, and themethod comprises the steps: building a moving target attack and defense strategy set; analyzing a moving target defense process based on the Markov time game, and constructing a Markov time game moving target defense model; and carrying out equilibrium solution on the Markov time game moving target defense model, and determining an optimal strategy in the confrontation process of the Markov time game moving target defense model. On the basis of analyzing a moving target attack and defense process, a Markov time game model is constructed, a target criterion function of a moving target defense game is designed based on discount total revenue, and multi-stage attack and defense game quantitative analysis is realized; designing a multi-stage optimal defense strategy selection algorithm based on nonlinear programming multi-stage game equilibrium calculation; further, experimental research results show that the confrontation process can be effectively described, the optimal strategy can be correctly selected, the implementation accuracy of moving target defense can be ensured, and network security management personnel can be helped to make a better decision.

The invention discloses a key transmission section searching method based on fuzzy clustering and shortest path. The method includes: classifying all line power structures, obtained by the use of tide tracing, by a criterion function based random clustering method so that parallel sets of obtain failed or overloaded branches form an initial key transmission section, and thereby avoiding the problems of multiple choices and missing, caused by the inadequacy of a manually given number of classes; for each branch in the initial key transmission section, successively from one end of the failed or overloaded line, searching for a shortest path, including the path from the corresponding branch to the other end of the failed or overloaded branch, and allowing all branches having the same tide direction as the failed or overloaded branch on the path to form all candidate branches of the key transmission section; subjecting the candidate branches to power distribution factor check calculation so as to determine a final key transmission section branch, and thereby quickly searching for the key transmission section.

The invention discloses a beam jitter model parameter real-time identification method based on a particle swarm algorithm, and the method comprises the following steps: firstly, building a beam jittermodel; secondly, collecting a light beam jitter time sequence signal; thirdly, determining an identification error criterion function; and then, carrying out global random search on the parameters ofthe light beam jitter model by utilizing a particle swarm algorithm so as to obtain the optimal parameters of the model, thereby realizing intelligent optimization of the model parameters. Compared with an existing method, the method has the most remarkable characteristics of random initial value, high calculation speed and high real-time performance. Moreover, in the iteration process, through self-adaptive change of an inertia weight factor, the ability of the algorithm to jump out of local convergence is greatly improved, and meanwhile, the efficiency of the algorithm can be improved. In addition, the method does not need an additional auxiliary system or manual debugging, and is low in implementation cost; and the method can be used for identifying the parameters of the light beam jitter model in different systems, and is high in transportability.

The embodiment of the invention discloses a database inquiry method and device and a database system. The database inquiry method comprises the steps of receiving an inquiry statement from a client terminal; analyzing the inquiry statement so as to obtain a function identification contained in the inquiry statement; searching N standard functions and M registered self-defining functions for a first function corresponding to the function identification, wherein the M and the N are natural numbers; if the first function corresponding to the function identification is found, obtaining first function calling interface information corresponding to the first function, calling the first function to search a database according to the obtained first function calling interface information, and feeding the processing result obtained through the operation carried out by the first function for searching the database back to the client terminal. According to the technical scheme, the database inquiry function is expanded, and the usability of database inquiry is improved.

Methods and structure for standardized communication between a test operator, a host system, and an embedded system under test. Test program instructions are designed, written for, and executed on, an embedded system under test in accordance with standard API functions for message exchange. Still further, the invention provides for standards in the user interface to select a desired test, to start the test with defined parameters and to present reply and status information to the test operator. These user interactions are defined in a test configuration language of the present invention and preferably incorporated with the executable image file to define an integral test vehicle file. The present invention thereby reduces test sequence development time by providing standard API functions for message exchange between a host system test application and the system under test and provides for standardized user interaction in a flexible, easily maintained design language.

The invention relates to the field of radar imaging, in particular to an SAR two-dimensional imaging method and system based on a vortex electromagnetic wave. The imaging method comprises the steps that according to the characteristic of the vortex electromagnetic wave, in combination with a geometrical relationship and work mode of traditional SAR imaging, a new-system radar imaging model is constructed, transmitting and receiving modes of the vortex electromagnetic wave are selected, scene, radar and target parameters are set, and after a transmitted signal is radiated by an array antenna and interacts with a target, an echo equation is obtained through derivation; in the distance direction, by designing and generating a signal with a large time-bandwidth product, target distance-direction high-resolution information is acquired. Based on a target information add-in item introduced into an echo by the vortex electromagnetic wave, a criterion function representing that the OAM mode number carried by the vortex electromagnetic wave changes with slow time is mainly designed; finally, vortex SAR two-dimensional imaging based on the orbital angular momentum is achieved, and the new-system imaging radar with combination of the vortex electromagnetic wave and an SAR imaging technology is utilized for achieving high-azimuth-resolution two-dimensional imaging.

The invention provides a method for predicting the actual heading of a wave glider. The method includes the steps of (1) obtaining positions of two points of a wave glider in a short time through a GPS to obtain a motion direction of the wave glider; (2) obtaining a heading angle and a course changing angular velocity of an upper floating body and a heading angle and a course changing angular velocity of a submerged body through compasses carried by the upper floating body and the submerged body; (3) establishing an identification algorithm model of a wave glider motion system, calculating theoutput of the model at a moment k according to an estimated parameter of a previous moment, that is, an output predicted value of the identification algorithm model of the wave glider motion system,and meanwhile, calculating a prediction error; and (4) feeding back the prediction error into the identification algorithm model of the wave glider motion system, calculating a model parameter estimated value at the moment k under the criterion, updating the model parameter, and performing iterations until a criterion function thereof reaches the minimum. The calculating accuracy of the method ofthe invention is independent of the distance, the structure is clear, and the implementation is easy to achieve by writing a computer program.

The invention discloses an indoor positioning method based on AP selection. According to the method, a support vector machine criterion function is taken as a discrimination criterion, AP (Access Point) selection is carried out during establishment of a fingerprint database, and a position coordinate is calculated by utilizing Bayes probability weight during online positioning. During establishment of the fingerprint database, the support vector machine criterion function is utilized to calculate a hyperplane distance, and a set of AP having the strongest discrimination capability is selected as an AP selection result during fingerprint database establishment. During online positioning, rough signal processing is carried out before positioning, the Bayes weight positioning algorithm is utilized during positioning, the Bayes probability is taken as weight to carry out weighted average for a target coordinate, and the target position coordinate is acquired. Through the method, reduction of calculation complexity in a positioning process is facilitated, useless APs for positioning are removed, and positioning precision is improved.

The invention relates to a high resolution seismic wavelet extracting method based on high-order statistics and an ARMA (autoregressive moving average) model, which belongs to the field of seismic signal processing. The high resolution seismic wavelet extracting method provided by the invention is characterized in that: under the precondition of performing ARMA parameter simplified modeling on seismic wavelets, SVD (singular value decomposition) based on autocorrelation function is adopted to determine an order of AR part, an MA order determining method is provided for integrating information content criterion function in a high-order cumulant MA order determining method, and the MA order determining accuracy rate in a seismic wavelet ARMA model is improved; an SV-TLS (singular value decomposition - total least squares estimation) and a cumulant method are respectively adopted to estimate wavelet parameters; and under the precondition of ensuring wavelet precision, the model order is decreased as far as possible to improve the operation efficiency and to finally realize seismic wavelet extraction in high efficiency and high precision. Through the data simulation verification and the practical seismic data processing demonstration, the method provided by the invention is proved to effectively improve the estimated precision and extracting efficiency for the seismic wavelets and to have obvious effect even under short-time seismic data and strong noise pollution.

The embodiment of the invention discloses a method and a device for analyzing a multi-dimensional query sentence in an online analysis processing server. The method comprises the following steps of: analyzing a multi-dimensional query sentence and generating a syntactic tree according to an analyzed result, wherein a node of the syntactic tree comprises a horizontal axis object, a longitudinal axis object, a slicing axis object, a calculating member object, a calculating unit object and a custom function CDF object; when a multi-dimensional query expression of various objects on the syntactictree is executed, if a function needs to be called, judging whether the function is a custom function or not according to a function definition of the custom function, if so, entering the executing process of the custom function; otherwise, judging whether the function is a standard function or not according to the function definition of a standard function; and if so, entering the executing process of a marking function. By the embodiment of the invention, the working efficiency of a developer in the development process of the whole OLAP system can be improved.

The invention discloses an inter-class relative uniformity-based image adaptive thresholding method and apparatus. The method comprises the following steps of reading a grayscale image; calculating a probability, a mean value and a variance of grayscale distribution; calculating relative uniformity information of two types of to-be-segmented grayscale distribution, wherein two types of grayscales are a target grayscale and a background grayscale respectively; and based on relative probability distribution and relative uniformity information of the two types, establishing a thresholding criterion function of inter-class relative uniformity. According to the method and the apparatus, a target obtained by segmentation is completer, and the edge is clearer, so that the applicability can be improved.

The invention discloses a no-model adaptive control method for an assembled spacecraft attitude and a system thereof, wherein the method comprises the steps of performing online parameter estimation on a pseudo-Jacobian matrix in a compact-format dynamic equivalent linear model according to historical control input and historical system output of the assembled spacecraft through a minimization estimation criterion function, and obtaining an estimated value of the pseudo-Jacobian matrix; according to the estimated value of the pseudo-Jacobian matrix, through a frontward forecasting error criterion function, obtaining a control input estimated value at a next time point; and using the control input estimated value at the next time point as the control input of the assembled spacecraft at thenext time point, thereby finishing no-model adaptive control of the assembled spacecraft attitude. Through the no-model adaptive control method and the system thereof, adaptive controlling to the long-time-delay assembled spacecraft is realized.

The invention discloses a characteristic fusion method based on a kernel typical correlation analysis, comprising steps of using a kernel function to map an image matrix to a kennel space, extracting two groups of characteristic vectors of one mode, establishing a criterion function for describing the correlation between the two groups of the characteristic vectors, obtaining two groups of typical projection vector sets according to the criterion function, and extracting a combined typical correlation characteristic through a provided characteristic fusion strategy and applying in the classification identification. The beneficial effects of the characteristic fusion method are that: the kennel introduction technology successfully promotes the linear typical correlation analysis to the non-linear, can extract the characteristic having the stronger discriminability, avoids the decomposition on the matrix after mapping, and simplifies the data operation. The kennel typical correlation analysis algorithm delicately uses the correlation characteristic between the two groups of the vectors as effective determination information, which not only achieves the goal of information fusion, but also eliminates information redundancy between the characteristics and achieves a good result in the classification.

The invention discloses a method for mining data of clothing standard working hours on the basis of clustering analysis. The method comprises the following steps: (1) data acquisition: recording the procedure working hours of each staff in real time by utilizing an RFID (radio frequency identification device) production system and establishing a data warehouse; (2) data preprocessing: removing abnormal data objects from a data set by a triple standard deviation method; (3) clustering by a density-based K-means algorithm, comprising: 1, determining the value of a clustering number K and the convergence precision of a criterion function; 2, initiating a clustering center; 3, appointing a sample object; 4, updating the clustering center; and 5, checking whether to meet the convergence precision or not, if so, finishing clustering, otherwise, repeating the steps 3 to 5 until the convergence precision is met; and (4) dividing all the working hour data into K classes according to the clustering result, and evaluating the average value, namely the standard working hours of the class, on the basis of each class. By the method, the standard working hours can be generated automatically. The method is convenient to implement and low in cost.

The invention belongs to the field of computer application and in particular discloses a network-based satellite cloud picture positioning method. The method is characterized by building a corresponding mathematical model and an algorithm according to the geographic information data in the preset area, obtaining the real-time user mouse position, matching the real-time user mouse position with the satellite cloud picture coordinate, displaying the corresponding geographic information and the real-time meteorological information and finally providing detailed and objective satellite cloud picture data information to a user. The PHP (hypertext preprocessor), JavaScript and the like are used to realize collaboration of a server and a client, a special wide band network is adopted as the transmission medium and the collaboration of different programs is realized by calling relevant standard functions, thus finally ensuring the method to be efficiently and stably carried out.

The invention discloses a generator power transduction method. The generator power transduction method comprises the steps: firstly collecting generator terminal voltage transformer three-phase voltage, generator terminal measurement-level current transformer three-phase current and generator terminal protection-level current transformer three-phase current in real time, secondly respectively calculating fundamental wave phasors of the generator terminal voltage transformer three-phase voltage, the generator terminal measurement-level current transformer three-phase current and the generator terminal protection-level current transformer three-phase current, and calculating generator terminal protection-level current transformer three-phase current fault component, generator frequency, power 1, power 2 and power 3; utilizing current fault component criterion with a floating braking threshold feature; if the criterion is met, outputting the power 2; if the criterion is not met, identifying the criterion by utilizing frequency fluctuation; if the criterion function is inputted and the criterion is met, outputting the power 3; if the criterion function is not inputted and the criterion is not met, outputting the power 1. According to the generator power transduction method, the criterion false operation when a system generates frequency deviation or oscillation can be avoided, and active power is correctly outputted. The invention further discloses a generator power transduction device.