95 results about "Parametric search" patented technology

Described is a method for generating a parametric search statement for finding a target document. The parametric search statement is generated in the text boxes of a search bar. A user action is performed in the text box. An in-place context menu having menu items responsive to the user action are displayed near the location of the user action. Each menu item includes at least one of an attribute of the target document, a comparison operator and a value. One of the menu items is selected from the in-place context menu based on a known characteristic of the target document. Parametric search statements are easily generated using the method without the need to access numerous dialogs boxes or to enter significant text.

A computer readable storage medium includes executable instructions to receive a relevancy parameter. The relevancy parameter is searched in a category ensemble including a set of categories, where the category ensemble overlies a dataset. A first order of the set of categories is created based on the relevancy of the relevancy parameter to each category in the set of categories, where the relevancy is a degree of match to the relevancy parameter. A second order of the set of categories is created based on the merit of each category to partition the dataset. The first order and the second order are combined into a final order, which is returned. A measure in the category ensemble is searched based on the relevancy parameter. The measure is returned as a selected measure, where the selected measure is a codomain of a visualization depicting a portion of the dataset.

A maximum likelihood detection (MLD) method is disclosed. Received data is processed to obtain preliminary parameters. An initial radius r is determined. r² is multiplied by a corresponding scaling factor according to a partial Euclidean distance (PED) constraint function to determine the upper limit values of PED for each layer. It is examined whether a sub-lattice exceeds a search scope according to the upper limit values of PED for each layer to search a better solution by utilizing the preliminary parameters.

A method, system, and computer program for enabling parametric searches on source data using text search engine. The invention is generally divided into a build-time process and a run-time process. During the build-time process, a crawler extracts data units from source data. A data translator then translates data units into keyword parametric entries that are submitted to the text search engine. During the run-time process, a query translator translates parametric search queries into keyword search entries. A metadata refiner then filters intermediate search results from the search engine based on the parametric search query.

Systems and methods for parametrically searching databases. Database definitions may be provided by users. Interface definitions may be provided by users. Interfaces may be provided dynamically.

The invention discloses an automatic labeling method for three-dimensional model component categories. The method includes the step of a CRF (conditional random field) labeling model training process, namely, training and learning to obtain a CRF labeling model for segmenting and labeling an unknown three-dimensional model according to a three-dimensional model labeling training set: firstly, dividing the three-dimensional model labeling training set into an instance set and a validation set; then, preprocessing the three-dimensional model labeling training set in the instance set so as to train to obtain unitary items and binary items of the CRF labeling model by classification; and finally, using a preprocessing result of the validation set for parameter search to obtain parameters of the CRF labeling model so that learning of the CRF labeling model is completed. During labeling of the target three-dimensional model, the CRF labeling model obtained from a learning process of the three-dimensional model labeling training set is used for segmenting and labeling, so that category labeling of target three-dimensional model components is achieved.

The invention relates to a detection and parameter estimation method for linear frequency modulation signals. The method comprises the following steps: (1) carrying dimension normalization for signals received; (2) carrying out discrete fractional Fourier transform self-adaptive calculation for signals after dimension normalization; and (3) extracting parameters based on interpolative calculation to obtain a central frequency calculation frequency of the linear frequency modulation signals. According to the invention, when the signals are received, the DFRET of the model is calculated by using an adaptive algorithm, so that the time delay generated by the calculation of DFRET after completely collecting data. In addition, the signal estimation precision is improved by difference processing in a parameter searching stage in a two-dimensional plane of the DFRFT.

A unique method for determining compatibility between people who, in the preferred embodiment, utilize an interactive internet dating service. Users complete a compatibility questionnaire, first describing themselves and then describing their “ideal match” on questionnaire items whose response options vary between two extremes. The user defines a search based upon demographic information for an “ideal match.” The pool of completed self assessment questionnaires of current users is searched by the computer utilizing the search parameters defined by the user. Pearson correlation coefficients are computed upon the items in the users “ideal match” questionnaire and the pool of self assessment questionnaires defined by the search. The “ideal matches” are ranked and reported as percentile scores that are obtained from a norm group of correlation coefficients for each gender. Percentile scores are also reported in similar manner for each content scale of the compatibility questionnaire. The user is able to search for an “ideal match” utilizing separate content scales from the compatibility questionnaire as well as with combinations of content scales from the questionnaire.

The invention belongs to the technical field of radar signal analysis, and discloses an LFMCW signal rapid detection and estimation method. Quasi-coherent accumulation is performed on the LFM part of each period of the same modulation frequency in LFMCW signals according to PFRFT energy so that the signals are enabled to have great energy concentration characteristic in the PFRFT domain, i.e. the PFRFT of the signals has an obvious peak value in two sections. Firstly rapid period fractional order Fourier transform is performed on the linear frequency modulation continuous wave signals, the maximum modulus square of period fractional order Fourier transform act as a target function to establish an optimization model, and the optimization model is solved by using a genetic algorithm so that the optimal parameter estimation of the signals can be obtained. Four-dimensional parameter searching is performed on the PFRFT energy of the linear frequency modulation continuous wave signals by using the genetic algorithm so that detection and estimation of radar weak signals can be realized, the method is especially applied to the design of a signal analysis system of low interception probability radar and thus the theoretical and project application of the PFRFT algorithm can be realized.

The invention discloses a method for estimating the cycle slope and the starting frequency of hyperbolic frequency modulated signals. The method comprises the following steps of first, acquiring a data sequence, second, initializing parameters, third, calculating the power spectrum of data in the ith short time window, fourth, estimating the instantaneous frequency fi of the data in the ith short time window by using a maximum gammagraphy method, fifth, estimating the zero crossing point interval gi = 1/fi of the data in the ith short time window, sixth, judging whether the data of all the short time windows are processed, executing the third step if not processed, otherwise executing the seventh step, seventh, sliding median filtering is conducted on a zero crossing point interval estimating sequence {gi, i = 1, 2, ..., I}, eighth, calculating the kth time interation weight, ninth, judging whether an interation stopping condition is met or not, if not, executing the eighth step again, otherwise executing the tenth step, and tenth, calculating the cycle slope and the starting frequency. According to the method, complex calculating and parametric search are of no need, the stability is strong, and quick and high-precision estimation of the parameters can be achieved.

Systems and methods are disclosed for the remote design of an electric motor (e.g. an AC or DC motor) by a customer through an interactive Web-based process. A typical system includes a Web server capable of delivering an interactive web page to a remote system. The web page includes one or more input fields allowing a user to specify motion performance requirement values applied to a design algorithm. The user may specify only some of the possible performance values. The design algorithm generates electric motor design parameters which will achieve the desired performance values. The algorithm also performs a parametric search through an existing parts database for at least some existing components which can be used in the electric motor design. The electric motor performance data is presented as an output to the user.

The invention provides a high-speed stealth target detection method of the polynomial Hough Fourier transform, and aims at solving the problems in distance walk and Doppler expansion in accumulated detection of a high-speed maneuvering stealth target. The detection method comprises that polynomial models of relatively high resolution are established, energy accumulation of a parameter space is realized by the polynomial Hough Fourier transform, polynomial models of higher resolution are established according to a parameter corresponding to the maximal energy value of the parameter space, polynomial Hough Fourier transform of high resolution is then carried out in small areas and so on till the requirement for compensation precision is met, and thus, coherent accumulation detection for the high-speed maneuvering stealth target is realized. The searching train of thought is approached layer by layer via the multiple resolution levels of the polynomial models, accumulation detection for the target is realized by the provided polynomial Hough Fourier transform, and compared with multi-dimension parameter search in a large range in a traditional method, the computational complexity, the memory amount and the complex degree can be substantially decreased, and convenience is provided for engineering.

A computerized workflow analysis tool, which allows a user to navigate through many levels of increasingly detailed order-related information. The order tracking and reporting tool of the preferred embodiments further allow a user to create customized, ad-hoc reports. In addition, the preferred embodiments allows a user to search information obtained from a plurality of databases by selected parameters, and to download the results obtained for further mathematical manipulation, graphing or trend analysis.

The invention relates to a non-parametric-search radar maneuvering target long-term coherent integration method and belongs to the technical field of radar signal processing. The method includes the steps of firstly, performing Fourier transform on pulse-compressed radar data along distance to obtain distance frequency-interphase slow time two-dimensional data; performing non-uniform sampling order-reducing operation and time coordinate axis scale transform; thirdly, performing distance frequency inverse Fourier transform and non-uniform sampling slow time Fourier transform to allow a maneuvering target to form a peak value in a two-dimensional plane and achieve long-term coherent integration. The method has the advantages that high-order phase signals are reduced to first-order phase signals through one non-uniform sampling order-reducing operation, cross term influence is lowered as compared with a traditional gradual order-reducing method, and parameter estimation precision is increased; parametric search matching calculation is not needed, operation quantity is lowered, and the method is applicable to engineering; distance and high-order Doppler migration can be compensated atthe same time, long-term coherent integration can be achieved, and the maneuvering target detecting ability of a radar in a strong clutter background is increased.

Method and system for calculating space planning of a building, using a building database (31), with unit distribution possibility tables (33), and compatibility tables (33, 34) showing the compatibility between them, whether horizontal, vertical or both, and comprising: defining (38) design criteria of the units and need program parameters; defining (39) a set of parameters of the typology and shape of the building; searching (40) in the vertical distribution table (33) for those that are as close as possible to the parameters defined; establishing (41) relation possibilities between the floors obtaining compatible houses; filtering (42) the design solutions which meet the design criteria; selecting (43) the buildings with houses as close as possible to the parameters and to the need program; calculating (44) the parameters which define floors of a building and distribution units by means of regression algorithms, decision trees or neural networks.

The invention relates to a hypersonic speed target detecting method for polynomial Radon-polynomial Fourier transform, and belongs to the technical field of radar signal processing and detecting. The method comprises the steps that N periodic signals to be accumulated are sampled, a slow time-fast time target observed value is extracted, and pulse compression is performed on the sampled signals separately; initialization parameters of polynomial Radon-polynomial Fourier transform are determined; search, compensation and accumulation are performed in a parameter space through polynomial Radon-polynomial Fourier transform to obtain a range-Doppler distribution diagram subjected to phase-coherent accumulation; constant false-alarm detection and target motion parameter estimation are performed on the range-Doppler distribution diagram. According to the method, model building is performed on target motion through polynomial, range walk and Doppler spread of the signals are compensated through parameter search of the polynomial, and therefore effective accumulation detection on a high-speed high-mobility target can be achieved under a low signal-to-noise ratio background; in addition, effective search on the multi-dimensional parameter space is achieved in a multi-resolution search mode, and therefore the search real-time performance is improved.

A controlled system model generating apparatus includes a real controlled variable storage unit which stores time-series data of a real controlled variable, a model storage unit which stores a mathematical model of a controlled system, a controller storage unit which stores a controller algorithm, a simulation computation unit which executes a simulation of simulating a control response concerning a control system, an evaluation function computation unit which compares a real controlled variable with a model controlled variable and computes an evaluation function value representing a proximity between the real controlled variable and the model controlled variable, and a controlled system model parameter search computation unit which causes the simulation computation unit to execute a simulation while sequentially changing a value of a controlled system model parameter set for a mathematical model, and determines a value of a controlled system model parameter with which an evaluation function value becomes an optimal value. A controlled system model generating method is also disclosed.

The invention discloses a bat algorithm-based control parameter self-tuning method for an alternating current (AC) servo speed regulation system. The method comprises the following steps of step one,setting corresponding linear weighting performance indexes and setting a parameter search space according to different application working conditions and performance preferences; step two, collectingsignal parameters of the AC servo speed regulation system for calculating the performance index of the current system; step three, establishing a fitness evaluation function and initializing relevantparameters; and step four, searching for a control parameter capable of realizing the optimal system performance by using a bat algorithm. Through the method disclosed by the invention, the difficultand time-consuming manual parameter tuning process is avoided; and compared with the controller parameter tuning method of the servo system at this stage, the operation is simple, the adaptability isgood, and the comprehensive performance demands under multiple performance indexes can be particularly guaranteed.

The invention relates to a radar high maneuvering target phase-coherent accumulation detection method based on time-reversed non-uniform sampling, and belongs to the technical field of radar signal processing and detecting. The radar high maneuvering target phase-coherent accumulation detection method comprises the steps that first, radar echo pulse pressure is performed, time reversal is matchedwith Fourier transform, and slow time second-order phase compensation is performed; fast time dimension Fourier transform is performed to obtain distance frequency-slow time data, and frequency second-order phase compensation is performed; then, non-uniform sampling order reduction and variable scale scaling change are performed; inverse Fourier transform and the Fourier transform are performed inthe distance frequency and time dimension separately to realize long-term phase-coherent accumulation; and finally, the detection statistics are constructed to detect and estimate a maneuvering target. The radar high maneuvering target phase-coherent accumulation detection method can effectively accumulate maneuvering target signals with a high-order phase, compensate the distance and Doppler migration and improve the detection capability of the radar maneuvering target; meanwhile, the influence of a cross term of a traditional successive order reduction method is reduced, and the parameter estimation accuracy is improved; and no multi-dimensional motion parameter search matching calculation is needed, the amount of calculation is reduced, and the radar high maneuvering target phase-coherent accumulation detection method is suitable for engineering application.

The invention discloses an automatic parameter tuning method for an iterative MapReduce operation. The method comprises the following steps of A) judging whether to meet an iterative ending condition or not, if so, ending an iterative calculation task, otherwise, executing step B; B) searching to obtain new MapReduce parameter configuration according to a given MapReduce parameter search space by utilization of a parameter searching algorithm; C) realizing the running of the current MapReduce operation by utilization of the searched new MapReduce parameter configuration, judging the running effect of the current MapReduce operation after the operation is finished, and performing corresponding data adjustment treatment according to a judging result; D) returning to execute the step A. By utilization of the method disclosed by the invention, the running efficiency of each iterative MapReduce operation can be improved, the convenience is brought to a user, and the waste of time resources is greatly reduced. The method disclosed by the invention can be widely applied to a Hadoop running parameter tuning field.

The embodiment of the invention provides a searching method and device for distributed model parameters and an electronic device, and the method and device specifically comprise the steps: carrying out the verification calculation of each gridding space through employing a pre-obtained verification sample set, and obtaining a cross verification mean value of an evaluation index corresponding to each gridding space; selecting a current optimal cross validation mean value from the obtained cross validation mean values, and selecting a most possible local search space according to the current optimal cross validation mean value; and performing Bayesian optimization calculation in the local search space according to a pre-selected optimal sampling point to obtain an optimal parameter combination in the local search space. According to the scheme, the search space is reduced on the basis of the corresponding rule, and then the parameter search is carried out in the reduced search space, sothat the parameter optimization efficiency is improved when the parameter space dimension is relatively high.