47 results about "Continuous parameter" patented technology

A medical characterization system is configured to input medical-related continuous parameters and discrete data so as to calculate a characterization timeline indicative of a physiological condition of a living being. A data source is in sensor communications with a patient so as to generate a continuous parameter. The data source also provides test data responsive to the patient at a test time. The test data is available to a characterization processor at a result time. The characterization processor is also responsive to the continuous parameter so as to generate a medical characterization as a function of time. A characterization analyzer enables the characterization processor to update the medical characterization in view of the test data as of the test time.

Exemplary embodiments of methods and apparatuses for automatic speech recognition are described. First model parameters associated with a first representation of an input signal are generated. The first representation of the input signal is a discrete parameter representation. Second model parameters associated with a second representation of the input signal are generated. The second representation of the input signal includes a continuous parameter representation of residuals of the input signal. The first representation of the input signal includes discrete parameters representing first portions of the input signal. The second representation includes discrete parameters representing second portions of the input signal that are smaller than the first portions. Third model parameters are generated to couple the first representation of the input signal with the second representation of the input signal. The first representation and the second representation of the input signal are mapped into a vector space.

When making digital data recordings using some form of computer or calculator, data is input in a variety of ways and stored on some form of electronic medium. During this process calculations and transformations are performed on the data to optimize it for storage. This invention involves designing the calculations in such a way that they include what is needed for each of many different processes, such as data compression, activity detection and object recognition. As the incoming data is subjected to these calculations and stored, information about each of the processes is extracted at the same time. Calculations for the different processes can be executed either serially on a single processor, or in parallel on multiple distributed processors. We refer to the extraction process as “synoptic decomposition”, and to the extracted information as “synoptic data”. The term “synoptic data” does not normally include the main body of original data. The synoptic data is created without any prior bias to specific interrogations that may be made, so it is unnecessary to input search criteria prior to making the recording. Nor does it depend upon the nature of the algorithms / calculations used to make the synoptic decomposition. The resulting data, comprising the (processed) original data together with the (processed) synoptic data, is then stored in a relational database. Alternatively, synoptic data of a simple form can be stored as part of the main data. After the recording is made, the synoptic data can be analyzed without the need to examine the main body of data. This analysis can be done very quickly because the bulk of the necessary calculations have already been done at the time of the original recording. Analyzing the synoptic data provides markers that can be used to access the relevant data from the main data recording if required. The nett effect of doing an analysis in this way is that a large amount of recorded digital data, that might take days or weeks to analyze by conventional means, can be analyzed in seconds or minutes. This invention also relates to a process for generating continuous parameterised families of wavelets. Many of the wavelets can be expressed exactly within 8-bit or 16-bit representations. This invention also relates to processes for using adaptive wavelets to extract information that is robust to variations in ambient conditions, and for performing data compression using locally adaptive quantisation and thresholding schemes, and for performing post recording analysis.

A method is provided for training a statistical pattern recognition decoder on new data while preserving its accuracy of old, previously learned data. Previously learned data are represented as constrained equations that define a constrained domain (T) in a space of statistical parameters (K) of the decoder. Some part of a previously learned data is represented as a feasible point on the constrained domain. A training procedure is reformulated as optimization of objective functions over the constrained domain. Finally, the constrained optimization functions are solved. This training method ensures that previously learned data is preserved during iterative training steps. While an exemplary speech recognition decoder is discussed, the inventive method is also suited to other pattern recognition problems such as, for example, handwriting recognition, image recognition, machine translation, or natural language processing.

The present invention relates to a pre-rainfall optimal parameter based flood forecasting method, and belongs to the technical field of flood forecasting. The method comprises the following steps: collecting statistics of the amount of the pre-rainfall in a forecast area before the occurrence of all historical flood in the forecast area; dividing the historical flood into a flood season group and a non-flood season group, and constructing a flood forecasting model for the forecast area; carrying out single parameter calibration on each historical flood so as to obtain a set of parameters for each flood; carrying out continuous parameter calibration respectively on the flood in the flood season group and the non-flood season group so as to obtain two sets of parameters, and dividing each of the two sets of parameters into two types of parameters of high sensitivity and low sensitivity; monitoring and recording daily rainfall data in real time, and collecting statistics of the amount of the pre-rainfall of the rainfall; and calculating a close degree between the amount of the pre-rainfall of the rainfall and the amount of the pre-rainfall of the historical flood, and taking the minimum value of the close degree as the flood forecasting model established by using the objective factor index so as to carry out flood forecasting. According to the method disclosed by the present invention, the accuracy and practicability of the hydrological model applied in flood forecasting are improved.

A method and system for determining whether a situation is logically true or false upon occurrence of an event uses conditions associated with the situation in combination with current values of parameters related thereto to create and maintain a database of current thresholds each corresponding to respective limits which characterize the situation and at least one of which is a composite threshold that encapsulates multiple conditions that can be directly compared with a single parameter associated with an event. Responsive to an event, successive parameters associated with the event are compared with respective ones of the current thresholds until either there are no more thresholds to be compared or until it can be definitively established that the situation is logically true or false. Prior to processing a subsequent event, the current database thresholds are updated.

The invention relates to a three-dimensional-coupling slip surface-controllable slope stability similar testing system which comprises a water level control system, a slip surface control system, a surface displacement monitoring system, a deep displacement monitoring system, a slipping force compensation servo control system, an earthquake effect control system, a reinforcing scheme monitoring system, and a data acquisition system. The system can realize surface and deep displacement monitoring during slope excavation process, and search of slope instable slip surfaces, and can determine the influence of rock and soil or weak plane (structural plane) water content on slope stability, and the influence of earthquake effect on slope stability. The system can simultaneously study the coupling influence of factors influencing slope stability; testing conditions provided by the system better accord with actual engineering conditions; the system can realize study of influence of continuous parameter change on slope stability; no individual testing with different parameters is necessary, and no individual testing with different values of the same parameter is necessary; materials are saved greatly; the testing efficiency and testing precision are improved; and the testing results are more real and reliable.

The invention discloses a fast multi-target antenna design method based on dynamic updating of an agent model. The agent model is utilized for fitting electromagnetic simulation data of an antenna design parameter sample, electromagnetic simulation consuming a long time is replaced for achieving instantaneous approximate calculation from antenna structure parameters to electromagnetic responses, therefore, the electromagnetic response frequency is reduced, and the calculation cost is greatly reduced; meanwhile, the antenna design parameter sample is newly added in the antenna design process for dynamically updating the agent model, so that the prediction precision of the agent model is improved. According to the fast multi-target antenna design method based on dynamic updating of the agent model, the antenna design efficiency is greatly improved, the method is suitable for solving various antenna structure continuous parameter variable design problems and more remarkable in advantage when especially used for solving the complex high-dimensional multi-target antenna design problem.

A method for hydrocarbon exploration and extraction is described. Specifically, the method includes using synthesis in reservoir modeling. The method may include obtaining local coordinates associated with a subsurface region. Then, a synthesis is performed with the local coordinates to determine continuous parameters and / or categorical parameters based on the synthesis. Then, a fluid flow simulation is performed from the continuous parameters and / or categorical parameters.

The invention discloses a method and device for managing data transmission channels, and relates to the technical field of communications. Through the adoption of the method and device, the quality of network services in complicated business scenes can be improved. The method comprises the following steps: obtaining the time delay of the data transmitted on the first channel and the continuous parameters of the first channel, and the time delay of the data transmitted on the second channel and the continuous parameters of the second channel; detecting whether a failure event occurs on the first channel or not; if yes, switching the working channel for a source service provider edge PE and a sink service provider edge PE to the second channel.

The invention discloses a circular target detection method based on voting line clustering, belongs to the technical field of computer vision and in particular relates to an image target detection technology. The method comprises establishing voting lines in a parameter space by use of the gray scale gradient direction of boundary points, and finding out the point having the maximum voting line density as the optimal circular parameter. According to the modeling manner, the optimal parameter can be quickly obtained by use of a probability density estimation method in a continuous parameter space, and therefore, the accuracy of circular target detection is improved and the detection efficiency is also guaranteed.

Pipeline wall thickness is measured as a function of position using ultrasound propagation. A series of predictive models is used, which define predictions of the ultrasound response signals as a function of different sets of parameters. The different sets that are determine of position dependent ultrasound speed at different sound frequencies and different spatial resolution. Successive iterative fitting process are executed, each fitting a combination of values of a successive set of parameters to the detected ultrasound response signals according to a respective model, using the values fitted values from the previous fitting process to initialize the next set of parameters for iterative fitting. At least the first model defines predictions of wave vector values as a function of circumferential position in successive rings around the pipe as sums of wave vector value for a plurality of circumferential positions in a preceding one of the rings multiplied by propagation coefficients, using propagation coefficients that depend on a first set of parameters.

The invention relates to an end-to-end blood cell recognition model construction method and application. A data sample set is formed based on a full-view image. An artificial intelligence technology is used for training a blood cell recognition model, and a mature recognition model is finally formed through continuous parameter optimization and error analysis optimization of the model.The model input is a single-view blood smear image, and the output is all cell positions, edges and categories on the image. Full-view blood cell analysis is achieved through a computer, interference of human objective factors is greatly reduced, and objectivity and consistency of inspection results are improved. The blood cell recognition model is intelligent, the software algorithm has a self-learning attribute, the training efficiency of the recognition model is gradually improved along with the increase of high-quality labeled images, and the software recognition and classification accuracy can be continuously optimized.

The invention discloses a video smiley face recognition method with robust posture, which comprises the following steps: extracting an image frame in a video image, detecting a face in the image framethrough a face detection algorithm; The facial expression feature points are located by using the key points location algorithm for the located facial rectangular frame. Extracting the position information of the located facial expression feature points; Matching the extracted facial expression feature points with the template parameters of the online training smiling expression feature points; After the subsequent image frames are read, the smiling expression parameters are matched in a small range in the vicinity of the smiling state position. The smile recognition result of the current image frame is output as a continuous parameter variable. The invention can precisely track the changing process of expression details, and the method is robust to illumination, realizes real-time application under natural illumination, can be adapted to various face videos, and has wide application prospects in the fields of expression recognition, human-computer interaction, film and television special effects and the like.

The invention relates to a joint resource optimization method for multi-target position estimation in a distributed MIMO radar system. The joint resource optimization method comprises: a target is designated and a minimized maximum value of a multi-target position estimation error is used as a target function; under the circumstances that the total numbers of the transmitting and receiving array elements are limited and the transmitted power is given, a resource optimization model of combination of transmitting and receiving array element selection and power allocation is established; and on the basis of a heuristic search algorithm and a continuous parameter convex approximation algorithm, a resource joint allocation algorithm based on cycle minimization is proposed to solve a hybrid Boolean type joint optimization problem to obtain a joint resource allocation result. According to the invention, the energy relationship between system resources and tracking capabilities is analyzed quantitatively; compared with the array element number, the influence on the system performance by the transmitted power becomes obvious and the influence on the target tracking precision and number by the system resources is displayed, so that the computing load of the system is reduced, the good system performance is realized, and the overall multi-target tracking accuracy is improved. The joint resource optimization method has the great practical application value.

A disk drive capable of being configured into a plurality of data storage zones, wherein some of the zones have different performance characteristics than other zones; a method for performing such a zoning configuration; and, a host device utilizing such a disk drive. The disk drive comprises a disk having a plurality of sectors for storing data, a head for reading and writing the data, and a disk drive controller for controlling the head, wherein the plurality of the sectors are organized into the plurality of zones. In one embodiment of the present invention, the performance characteristics of the zones are dictated by configuration settings in the disk drive controller. The configuration settings may include settings for a plurality of parameters. In some embodiments of the present invention, the plurality of parameters comprises a CCT (command completion time) parameter, a Write Verify parameter, a Write Continuous parameter, a Read Continuous parameter, and an Error Re-allocation parameter. In other embodiments of the present invention, the configuration settings may also include a group of addresses associated with each zone.

The invention discloses a shale gas probability area selecting method. The method includes the following steps that continuous parameters and discrete parameters of shale gas selecting areas are determined; according to changes of the single parameters in an evaluation area, a planar information graph of a uniform proportional scale is generated; conditional probability valuing is performed according to geological implication, continuous parameter values under different conditional probabilities are obtained through a proportion occupying algorithm, and discrete parameter values corresponding to different conditional probabilities are obtained through normal distribution model integrals; single parameter values under the same conditional probability serve as a shale gas selecting area combination standard under the probability, the beneficial range under the conditional probability is delineated on the planar information graph of the single parameters, and the superposed area of the planar beneficial ranges of the single parameters is the shale gas probability area selecting result under the conditional probability. The method is high in operability and reliability and capable of reasonably implementing shale gas probability area selecting, and reliable and effective quantitative area selection is achieved.

The invention discloses a log parameter anomaly detection method based on word embedding, and the method comprises the following steps: 1, analyzing all parameters in a log, and independently dividingdiscrete parameters in all the parameters; 2, converting the discrete parameters into continuous parameter word vectors; 3, training a parameter word vector by using a long-term and short-term memoryneural network model, and predicting the parameter word vector at a subsequent target moment by using the trained parameter word vector; 4, determining the association degree of the prediction parameter word vector and the target parameter word vector by using cosine similarity, calculating a loss value through the association degree, feeding back the loss value to the network, and updating and optimizing the model until convergence; and 5, acquiring a log to perform parameter anomaly detection, calculating cosine similarity between the prediction parameter and the target parameter, and if the cosine similarity is lower than a threshold value, determining that the log parameter is abnormal. The detection bottleneck caused by parameter dynamics and difference can be effectively solved, andthe overall accuracy of log detection is improved.

The embodiment of the invention provides a voltage stabilization analyzing method and device for a power system of a wind power plant. The method comprises: selecting continuous parameters to form a new equation, expanding the flow equation of the power system by using the new equation, correcting the expanded flow equation of the power system to obtain corrected flow equation of the power system, wherein in the corrected flow equation of the power system, the corrected flow jacobian matrix is the flow jacobian matrix generated when the node in the power system with maximum reduced voltage amplitude value is processed as the node with appointed injection power and voltage amplitude value; using a Newton-Raphson algorithm iteration to solve the corrected flow equation of the power system so as to obtain a prediction direction; determining a predication point according to the prediction direction and a preset step size; and analyzing the voltage stabilization condition of the power system of the wind power plant according to the prediction point. According to the scheme of the invention, the convergence of the continuous flow calculation nearby the critical point is greatly improved; and the reliability of the algorithm is greatly improved.

The invention discloses a flue gas emission prediction method comprising the following steps: obtaining flue gas sample data collected by a flue gas data extraction tool, the flue gas sample data comprising to-be-detected flue gas emission index data, analog quantity data and switching value data, the analog quantity data being continuous parameter data of flue gas in the production process, the switching value data being continuous parameter data of flue gas in the production process, and wherein the switching value data is discrete parameter data of flue gas in the production process; inputting the flue gas sample data into a pre-constructed flue gas emission prediction network for model training to obtain a flue gas emission prediction model; and inputting to-be-detected flue gas test data into the flue gas emission prediction model, and predicting various flue gas emission indexes in the production process. The invention further discloses a flue gas emission prediction system and acomputer readable storage medium. Flue gas emission index prediction is carried out through the flue gas emission prediction model, so that timeliness and effectiveness of flue gas emission index prediction can be guaranteed, and material cost is reduced.

The invention discloses an ISAR imaging method based on matching tracking, and solves the problem of echo data distance alignment in IASR imaging. The ISAR imaging method comprises the following steps: performing Fourier transform on received echo data in a distance direction; 2, achieving matching tracking on a continuous parameter space by virtue of Chebyshev polynomials construction atoms by using a simulation annealing algorithm, thereby obtaining atoms in optimal matching with echo data; 3, performing motion compensation on the echo data by using the optimal atoms; 4, performing inverse Fourier transform on the echo data in the distance direction, and recovering into a time-domain signal; 5, imaging the echo data by using a self-focusing method. By adopting the ISAR imaging method, a relatively good motion compensation effect can be achieved, and high-resolution ISAR imaging can be achieved.

Disclosed is a method of monitoring the behaviour of a subsurface volume. The method comprises transforming a single discrete parameter or an ensemble of discrete parameters describing an attribute of the subsurface volume, each discrete parameter having N possible discrete values with N ≧2, into N indicator parameters each having 2 possible discrete values; for each of the two value classes of each indicator parameter, determining the anisotropic distance to a value transition interface; transforming each of the indicator parameters into a corresponding continuous parameter using the determined anisotropic distance to the value transition interface; and using the continuous parameters in a history matching process.

The invention relates to the technical field of mine hydrogeological monitoring, in particular to a method for obtaining continuous parameters of an aquifer based on a superimposed drainage test. Themethod comprises the following steps: 1, implementing the superimposed drainage test in a research area; 2, establishing a numerical model of a research area and dividing a grid discrete model; 3, setting a random distribution function value of aquifer parameters; 4, selecting an applicable covariance function to describe the variation degree of the aquifer parameters; 5, iteratively calculating the continuous distribution of the aquifer parameters by using a water drainage chromatography method. The method is easy to operate and wide in applicability; compared with a traditional analysis method, the obtained hydrogeological parameters are more detailed and specific, the heterogeneity of the aquifer can be accurately described, the position and range of the water-rich abnormal area can beaccurately positioned, the mine water inrush disaster risk is effectively reduced, and comprehensive technical guarantee is provided for safe production of mining areas.

The invention relates to a method for optimizing cognitive radio system parameters in a membrane structure. According to the method, by means of a mixture quantum goose swarm method in the membrane structure, the minimized transmitting power, the minimized bit error rate and the maximized data rate of a cognitive radio system are optimal simultaneously. The method includes the steps that the membrane structure is determined, the quantum position and the speed are generated, the system parameters and the mixing positions correspond to each other in a one-to-one mode, the speed and the quantum position are updated, the system parameters are formed through mapping, a fitness value is calculated, an optimal local mixing position and an optimal global mixing position of each goose are updated, the optimal global mixing positions are updated, and the optimal global mixing positions traveled by all geese of the whole quantum goose swarm are mapped to the system parameters and output from a surface membrane. The optimization problem of the system parameters with mixed disperses and continuous parameters is solved, the mixture quantum goose swarm method in the membrane structure is designed to serve as a solving strategy, and the designed method has the advantages of being high in convergence precision and convergence speed.

The invention discloses an image denoising method based on statistical local rank characteristics. The image denoising method comprises the following steps: performing local rank transformation on the image under different parameter conditions by utilizing a local rank operator, thereby obtaining positive local rank transformation and negative local rank transformation of the image; adding the local rank transformation and negative local rank transformation to obtain statistical local rank characteristics with continuous parameter changes; taking the statistical local rank characteristics as constraint conditions on the basis of an image denoising method with sparse representation, and performing primary denoising on the image; and finally, performing secondary denoising on the image by controlling the difference of the statistical local rank characteristics between the images before and after denoising, and removing the image noise, thereby obtaining a final clear image. The method has the obvious effects that compared with the traditional denoising method based on sparse representation, the method has a better denoising effect, can acquire a denoised image with high quality, and further can effectively guarantee the reliability of subsequent image processing and analyzing.

The invention relates to an electric car road testing system, which is characterized in comprising a first collection unit, a second collection unit and a central processing unit, wherein the first collection unit comprises a current sensor, a voltage sensor, an A / D signal conversion module, a data reading, writing and storage module, a display module, a first wireless signal transmission module,a Hall sensor and an adding counter; the second collection unit comprises an active infrared intrusion detector, a lithium battery and a second wireless signal transmission module. The invention alsorelates to an electric car road testing method which is characterized in comprising the following steps that: 1) parameter setting; 2) system self-inspection; and 3) parameter detection. The electriccar road testing system is scientific and reasonable in design, and can carry out real-time dynamic and automatic detection on an electric car driving road condition, and continuous parameter recording is realized.