9743 results about "Non linearite" patented technology

A system and process that provides an on-line, interactive, and fully integrated benefit-driven value exchange and settlement program that monitors, evaluates, and manages economic and personal benefits and executes functions to produce and acquire the maximum or preferred benefit items for users by guiding and automating appropriate payment and settlement actions. The present invention finds useful patterns in data; produces conclusions based on rules and experience; responds to environmental changes with or without human intervention; and, may evolve through selecting the best results from random mutations all of which are intended to maximise user value.

A petroleum reservoir production modeling apparatus and method is disclosed which incorporates a complete (from reservoir to wellhead) production systems analysis system for the evaluation of petroleum reservoir production performance, using industry accepted techniques of analysis. A computer generated model facilitates the determination of well and formation properties in a computerized methodology, efficiently, reliably and accurately, thereby facilitating subsequent changes in wellbore properties to maximize well production. The method includes a rigorous analytic reservoir inflow performance model for a variety of well types and reservoir outer boundary conditions and drainage area shapes, and uses industry accepted production analysis techniques. These techniques accepted in the industry include material balance, decline curve analysis, and non-linear minimization procedures. Field-recorded production data is evaluated to obtain estimates of the well or formation properties. Statistical techniques are used to minimize or eliminate the effects of outlier (i.e. noise) points in the data.

According to one embodiment, A nonlinear editing system comprises a video encoder, an audio compressor and an engine unit. The engine unit is adapted to synchronize the video with the first alternate video and to synchronize the audio with the first alternate audio so that, where the scene of the program includes objectionable content, either (i) the video is substituted with the first alternate video, (ii) the audio is substituted with the first alternate audio, or (iii) both the video and the audio are substituted with the first alternate video and the first alternate audio.

Based on a received signal y(t) received by a radiating element of an array antenna including the single radiating element and a plurality of parasitic elements, an adaptive controller calculates and sets a reactance value of a variable reactance element for directing a main beam of the array antenna in a direction of a desired wave and directing nulls in directions of interference waves so that a value of an objective function expressed by only the received signal y(t) becomes either one of the maximum and the minimum by using an iterative numerical solution of a nonlinear programming method.

A method and system for performing continuous (real-time) physics based prognostics analysis as a function of actual engine usage and changing operating environment. A rule-based mission profile analysis is conducted to determine the mission variability which yields variability in the type of thermal-mechanical loads that an engine is subjected to during use. This is followed by combustor modeling to predict combustion liner temperatures and combustion nozzle plane temperature distributions as a function of engine usage which is followed by off-design engine modeling to determine the pitch-line temperatures in hot gas path components and thermodynamic modeling to compute the component temperature profiles of the components for different stages of the turbine. This is automatically followed by finite element(FE) based non-linear stress-strain analysis using an real-time FE solver and physics based damage accumulation, life consumption and residual life prediction analyses using microstructural modeling based damage and fracture analysis techniques.

The Quanton virtual machine approximates solutions to NP-Hard problems in factorial spaces in polynomial time. The data representation and methods emulate quantum computing on classical hardware but also implement quantum computing if run on quantum hardware. The Quanton uses permutations indexed by Lehmer codes and permutation-operators to represent quantum gates and operations. A generating function embeds the indexes into a geometric object for efficient compressed representation. A nonlinear directional probability distribution is embedded to the manifold and at the tangent space to each index point is also a linear probability distribution. Simple vector operations on the distributions correspond to quantum gate operations. The Quanton provides features of quantum computing: superpositioning, quantization and entanglement surrogates. Populations of Quantons are evolved as local evolving gate operations solving problems or as solution candidates in an Estimation of Distribution algorithm. The Quanton representation and methods are fully parallel on any hardware.

The invention discloses a comment text emotion classification model training and emotion classification method and device and equipment and belongs to the field of text emotion classification in natural language processing. Model training comprises the steps that a comment text and associated subject and object information are acquired; a comment subject and object attention mechanism is fused based on a first-layer Bi-LSTM network to extract sentence-level feature representation; the comment subject and object attention mechanism is fused based on a second-layer Bi-LSTM network to extract document-level feature representation; and a hyperbolic tangent non-linear mapping function is adopted to map document-level features to an emotion category space, softmax classification is adopted to train parameters in a model, and an optimal text emotion classification model is obtained. According to the method, the hierarchical bidirectional Bi-LSTM network model and the attention mechanism are adopted, context semantic robust perception and semantic expression of the text can be realized, the robustness of text emotion classification can be remarkably improved, and the correct rate of classification is increased.

In a database, a frequently retrieved column is encrypted using a common key, and other columns are encrypted using a specific row key. Thus, a retrieving process can be performed at a high speed, and the security can be improved. Then, the row and column of the database are encrypted by assuming the plaintext to be encrypted as a bit string, and performing a binary operation with a random bit string. A random bit string is obtained by sequentially generating multidimensional vectors using a nonlinear function by defining a predetermined bit length as 1 word and a plurality of words as components of the multidimensional vector.

A system and method for historical database training of non-linear models for use in electronic commerce. The non-linear model is trained with training sets from a stream of electronic commerce data. The system detects availability of new training data, and constructs a training set from the corresponding input data. Over time, many training sets are presented to the non-linear model. When multiple presentations are needed to effectively train the non-linear model, a buffer of training sets is filled and updated as new training data becomes available. Once the buffer is full, a new training set bumps the oldest training set from the buffer. The training sets are presented one or more times each time a new training set is constructed. An historical database may be used to construct training sets for the non-linear model. The non-linear model may be trained retrospectively by searching the historical database and constructing training sets.

A method of multivariate spectral analysis, termed augmented classical least squares (ACLS), provides an improved CLS calibration model when unmodeled sources of spectral variation are contained in a calibration sample set. The ACLS methods use information derived from component or spectral residuals during the CLS calibration to provide an improved calibration-augmented CLS model. The ACLS methods are based on CLS so that they retain the qualitative benefits of CLS, yet they have the flexibility of PLS and other hybrid techniques in that they can define a prediction model even with unmodeled sources of spectral variation that are not explicitly included in the calibration model. The unmodeled sources of spectral variation may be unknown constituents, constituents with unknown concentrations, nonlinear responses, non-uniform and correlated errors, or other sources of spectral variation that are present in the calibration sample spectra. Also, since the various ACLS methods are based on CLS, they can incorporate the new prediction-augmented CLS (PACLS) method of updating the prediction model for new sources of spectral variation contained in the prediction sample set without having to return to the calibration process. The ACLS methods can also be applied to alternating least squares models. The ACLS methods can be applied to all types of multivariate data.

A method, system and apparatus for real-time reservoir model updating using ensemble Kalman filters is described. The method includes a conforming step for bring bringing static and dynamic state variables into conformance with one another during a time step of the updating. Also, an iterative damping method is used in conjunction with the conformance step to account for nonGaussian and nonlinear features in a system. Also, a re-sampling method is described which reduces the ensemble size of reservoir models which are to be updated.

In one embodiment, systems and methods are provided for nonlinear journaling. In one embodiment, groups of data designated for storage in a data storage unit are journaled into persistent storage. In one embodiment, the journal data is recorded nonlinearly. In one embodiment, a linked data structure records data and data descriptors in persistent storage.

The invention discloses an experimental method of simulating dynamic and static load and a device thereof, relating to indoor model experimental technique of geotechnical engineering. The structure of the device is as follows: a model experimental platform (1), a model experimental box (2) and a load transmitting lever (3) are sequentially connected; the load transmitting lever (3) is respectively connected with a static load system (4) and a dynamic load system (5) which are respectively connected with a dynamic signal testing system (6); the dynamic signal testing system (6), a data acquisition system (7) and a computer (8) are sequentially connected. The device caries out dynamic and static load experiments on different structure models, and can monitor and collect non-linear properties of deformation and stress of gneiss under complex load condition in real time. The device has intuitional testing principle, simple structure, high precision, good stability, easy operation, convenient detachment and no high technical requirement to mounting and testing workers.

The present invention relates to audio coding systems which make use of a harmonic transposition method for high frequency reconstruction (HFR). A system and a method for generating a high frequency component of a signal from a low frequency component of the signal is described. The system comprises an analysis filter bank providing a plurality of analysis subband signals of the low frequency component of the signal. It also comprises a non-linear processing unit to generate a synthesis subband signal with a synthesis frequency by modifying the phase of a first and a second of the plurality of analysis subband signals and by combining the phase-modified analysis subband signals. Finally, it comprises a synthesis filter bank for generating the high frequency component of the signal from the synthesis subband signal.

A system and method for on-line training of a non-linear model for use in electronic commerce. The non-linear model is trained with training sets from a stream of process data. The system detects availability of new training data, and constructs a training set from the corresponding input data. Over time, many training sets are presented to the non-linear model. When multiple presentations are needed to effectively train the non-linear model, a buffer of training sets is filled and updated as new training data become available. Once the buffer is full, a new training set bumps the oldest training set from the buffer. The training sets are presented one or more times each time a new training set is constructed. An historical database may be used to construct training sets for the non-linear model. The non-linear model may be trained retrospectively by searching the historical database and constructing training sets.

A system of non-linear feedback control for spinal cord stimulation is provided. The system comprises a lead adapted to be implanted within an epidural space of a dorsal column of a patients spine, and a pulse generator (PG) electrically coupled to the lead. The PG is configured to deliver spinal cord stimulation (SCS) therapy. The system also comprises a sensing circuitry configured to sense an evoked compound action potential (ECAP) response that propagates along the neural pathway. The system also comprises a processor programmed to operation, in response to instructions stored on a non-transient computer-readable medium, to obtain a baseline ECAP response when the lead and spinal cord tissue properties are in baseline states; analyze ECAP responses relative to the baseline ECAP response to obtain an ECAP feedback difference indicative of a change in at least one of the baseline state of the lead and the baseline state of the spinal cord tissue properties. The processor is also programmed to adjust an SCS therapy based on the ECAP feedback.

A method and apparatus compensate for a non-linear characteristic of a wideband power amplifier in a transmitter for a communication system, which has the wideband power amplifier for amplifying a digital input signal. The method involves the steps of (a) generating an address based on the digital input signal, reading a distortion control value corresponding to the address from a look-up table, and applying the read distortion control value to the digital input signal to predistort the digital input signal; (b) frequency up-converting the predistorted signal and amplifying the frequency up-converted signal; (c) frequency down-converting the amplified signal and compensating for a delay of the frequency down-converted signal; and (d) updating a predetermined distortion control value in the look-up table to compensate for an error value generated in the power amplifier and an analog path occurring in steps (b) and (c) based on the compensated signal.

A classifier training method and apparatus for training, a linear classifier trained by the method, and its use, are disclosed. In training the linear classifier, signatures for a set of training samples, such as images, in the form of multi-dimension vectors in a first multi-dimensional space, are converted to a second multi-dimension space, of the same or higher dimensionality than the first multi-dimension space, by applying a set of embedding functions, one for each dimension of the vector space. A linear classifier is trained in the second multi-dimension space. The linear classifier can approximate the accuracy of a non-linear classifier in the original space when predicting labels for new samples, but with lower computation cost in the learning phase.

The invention relates to a novel image-reconstruction technique which is used to view multiphase flows using electrical capacitance tomography (ECT), which is based on non-linear heuristic global optimization methods involving simulated annealing and genetic algorithms. The inventive method consists in obtaining electrical capacitance data which are measured between electrodes positioned on the outer surface of pipeline, well or tank (electrically-insulating) containing fluids. The aforementioned data are dependent on the distribution of the fluids inside the pipeline, well or tank. Moreover, the data are processed in order to reconstruct an image of the spatial distribution of the relative electrical permittivity (also known as the dielectric constant) inside the tube, well or tank, which reflects the distribution of the different phases present in the flow.

The present invention applies a novel iterative algorithm to the problem of multidimensional optimization by supplying a strict, nonlinear mathematical solution to what has traditionally been treated as a linear multidimensional problem. The process consists of randomly selecting a statistically significant sample of a prospect list, calculating the value of the utility function for each pair of an offer and selected prospects, reducing the original linear multidimensional problem to a non-linear problem with a feasible number of dimensions, solving the non-linear problem for the selected sample numerically with the desired tolerance using an iterative algorithm, and using the results to calculate an optimal set of offers in one pass for the full prospect list.

The invention discloses a parking path planning method and parking motion control method of an auxiliary parking system. A multi-stage smooth parking path which is designed through the parking path planning method based on the B-spline theory meets multiple non-linear constraints such as a vehicle obstacle avoidance constraint, a minimum turning radius constraint and a maximum steering speed constraint; through the path curvature continuity, a pivot steering phenomenon is avoided, and tire wear and steering motor loads are reduced; through the multi-stage smoothness of the path, vehicle tracking is easy to achieve. According to the parking motion control strategy, the requirements of the parking system for the parking speed of a driver are lowered, and the driver only needs to control a vehicle to be driven at low speed. For the phenomenon that in the parking process, the vehicle deviates from the target path and cannot park in the correct position due to the fact that the vehicle speed is too high, a vehicle position posture adjusting strategy based on fixed-point tracking control is presented, and therefore the parking success rate is increased; in addition, fixed-point tracking control is adopted, therefore, the vehicle can be parked to be parallel to a parking space, and vehicle parking standardization is achieved.

The invention discloses a text sentiment classification algorithm based on a convolutional neural network and an attention mechanism. The text sentiment classification algorithm comprises the steps of1, establishing the convolutional neural network comprising multiple convolutions and multiple kinds of pooling, and using sentiment classification text for training to obtain a first model; 2, establishing the multi-head point product attention mechanism into which residual connection and nonlinearity are added, and using the sentiment classification text for training to obtain a second model; 3, conducting model fusion on the two models to obtain sentiment classification of the text. Multiple granularity, the convolutions and multiple kinds of pooling are fused into the convolutional neuralnetwork, the residual connection and the nonlinearity are introduced into the attention mechanism, and attention is calculated several times to obtain two text sentiment classification models. Through a Bagging model fusion method, a fusion model is obtained, the text is classified, the advantages that the convolutional neural network can well capture local features and the attention mechanism can well capture global information can be combined, and the more comprehensive text sentiment classification models are obtained.

Neural networks provide efficient, robust and precise filtering techniques for compensating linear and non-linear distortion of an audio transducer such as a speaker, amplified broadcast antenna or perhaps a microphone. These techniques include both a method of characterizing the audio transducer to compute the inverse transfer functions and a method of implementing those inverse transfer functions for reproduction. The inverse transfer functions are preferably extracted using time domain calculations such as provided by linear and non-linear neural networks, which more accurately represent the properties of audio signals and the audio transducer than conventional frequency domain or modeling based approaches. Although the preferred approach is to compensate for both linear and non-linear distortion, the neural network filtering techniques may be applied independently.

New and efficient protocols are provided for privacy-preserving machine learning training (e.g., for linear regression, logistic regression and neural network using the stochastic gradient descent method). A protocols can use the two-server model, where data owners distribute their private data among two non-colluding servers, which train various models on the joint data using secure two-party computation (2PC). New techniques support secure arithmetic operations on shared decimal numbers, and propose MPC-friendly alternatives to non-linear functions, such as sigmoid and softmax.

The invention discloses a microgrid running optimization system and method based on power and heat combined dispatching. Running restrains such as the output force characteristic, start, stop and climbing of a distributed type generator set and the charge and discharge characteristics of power and heat energy storage are comprehensively considered, a microgrid power and heat combined dispatching model containing a fan, a photovoltaic cell, a combined heat and power generation system, an electric boiler, a fuel cell and an energy storage (electrical energy storage and heat energy storage) is built, the 0-1 mixed integer nonlinear programming method is adopted for solving the optimal output force and total running cost of all units in the network, and power and heat dispatching contrastive analysis is carried out on the system and a traditional separated generation and combined generation optimization model. In addition, the influences of the heat and power reliability difference on the running are analyzed and discussed, and therefore the heat and power dispatching module is more reasonable, comprehensive and universal.

A non-linear dynamic predictive device (60) is disclosed which operates either in a configuration mode or in one of three runtime modes: prediction mode, horizon mode, or reverse horizon mode. An external device controller (50) sets the mode and determines the data source and the frequency of data. In prediction mode, the input data are such as might be received from a distributed control system (DCS) (10) as found in a manufacturing process; the device controller ensures that a contiguous stream of data from the DCS is provided to the predictive device at a synchronous discrete base sample time. In prediction mode, the device controller operates the predictive device once per base sample time and receives the output from the predictive device through path (14). In horizon mode and reverse horizon mode, the device controller operates the predictive device additionally many times during base sample time interval. In horizon mode, additional data is provided through path (52). In reverse horizon mode data is passed in a reverse direction through the device, utilizing information stored during horizon mode, and returned to the device controller through path (66). In the forward modes, the data are passed to a series of preprocessing units (20) which convert each input variable (18) from engineering units to normalized units. Each preprocessing unit feeds a delay unit (22) that time-aligns the input to take into account dead time effects such as pipeline transport delay. The output of each delay unit is passed to a dynamic filter unit (24). Each dynamic filter unit internally utilizes one or more feedback paths that are essential for representing the dynamic information in the process. The filter units themselves are configured into loosely coupled subfilters which are automatically set up during the configuration mode and allow the capability of practical operator override of the automatic configuration settings. The outputs (28) of the dynamic filter units are passed to a non-linear analyzer (26) which outputs a value in normalized units. The output of the analyzer is passed to a post-processing unit (32) that converts the output to engineering units. This output represents a prediction of the output of the modeled process. In reverse horizon mode, a value of 1 is presented at the output of the predictive device and data is passed through the device in a reverse flow to produce a set of outputs (64) at the input of the predictive device. These are returned to the device controller through path (66). The purpose of the reverse horizon mode is to provide essential information for process control and optimization. The precise operation of the predictive device is configured by a set of parameters. that are determined during the configuration mode and stored in a storage device (30). The configuration mode makes use of one or more files of training data (48) collected from the DCS during standard operation of the process, or through structured plant testing. The predictive device is trained in four phases (40, 42, 44, and 46) correspo

An efficient coding scheme with higher audio bandwidth and / or better audio quality at lower bitrates, wherein the scheme eliminates long-term and short-term frequency domain correlation in a signal via frequency domain predictors. The coding scheme compresses information consisting of coded low frequency components as well as a parametric representation for the high frequency components based on a non-linear model. Additionally, by working on the frequency domain representations of the signal (such as the MDCT representation which is naturally available to a PAC encoder and decoder), low pass and high pass signal components are easily obtained by windowing the appropriate ranges of frequencies in the signal. Furthermore, the power functions of the signal are replaced by corresponding convolution functions of the same order.

A synchronous quick calibration method of a plurality of video cameras in a three-dimensional scanning system, which includes: (1) setting a regular truncated rectangular pyramid calibration object, setting eight calibration balls at the vertexes of the truncated rectangular pyramid, and respectively setting two reference calibration balls at the upper and lower planes; (2) using the video cameras to pick-up the calibration object, adopting the two-threshold segmentation method to respectively obtain the corresponding circles of the upper and lower planes, extracting centers of the circles, obtaining three groups of corresponding relationships between circle center points in the image and the centres of calibration ball in the space, solving the homography matrix to obtain the internal parameter matrix and external parameter matrix and obtaining the distortion coefficient, taking the solved video camera parameter as the initial values, and then using a non-linear optimization method to obtain the optimum solution of a single video camera parameter; (3) obtaining in sequence the external parameter matrix between a plurality of video cameras and a certain video camera in the space, using the polar curve geometric constraint relationship of the binocular stereo vision to establish an optimizing object function, and then adopting a non-linear optimization method to solve to get the optimum solution of the external parameter matrix between two video cameras.

A system and method for measuring dynamic properties of a structure, and for using the measured dynamic properties to assess the dynamic performance of the structure. The system and method measures dynamic properties of the structure such as frequencies of resonance, mode shapes, and non-linear damping, and uses them in an analysis of the structure to compare the dynamic response of the structure with the anticipated properties of a structure built according to applicable building code requirements. The system and method thus quantifies a risk of failure of the structure by determining a risk ratio that compares an as-is condition of the structure with an as-designed condition of the structure.

A method and apparatus for identifying running vehicles in an area to be monitored using acoustic signature recognition. The apparatus includes an input sensor for capturing an acoustic waveform produced by a vehicle source, and a processing system. The waveform is digitized and divided into frames. Each frame is filtered into a plurality of gammatone filtered signals. At least one spectral feature vector is computed for each frame. The vectors are integrated across a plurality of frames to create a spectro-temporal representation of the vehicle waveform. In a training mode, values from the spectro-temporal representation are used as inputs to a Nonlinear Hebbian learning function to extract acoustic signatures and synaptic weights. In an active mode, the synaptic weights and acoustic signatures are used as patterns in a supervised associative network to identify whether a vehicle is present in the area to be monitored. In response to a vehicle being present, the class of vehicle is identified. Results may be provided to a central computer.