109 results about "Nonlinear modelling" 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.

The invention discloses a nonlinear modeling method and a linear trimming method for a composite rotor aircraft, and belongs to the technical field of control of composite rotor aircrafts. According to the method, the aerodynamic characteristics of all parts are analyzed, and a split modeling method is adopted to carry out dynamic modeling; on the basis of the model, combined with a quasi-Newton iteration method and a sequence quadratic programming method, a quasi-Newton-sequence quadratic programming method is proposed to dynamically balance the dynamic model of the composite rotor aircraft and make small disturbance linearity at the equilibrium point, so that an approximate linearized kinetic equation for the equilibrium point can be obtained. The dynamic model established by using the modeling method disclosed by the invention is high in confidence coefficient and simple in calculation, in addition, the new trimming method provided by the invention can avoid solving the inverse matrix of the objective function Hessian matrix, the calculation is simplified, the relatively high convergence speed is ensured, and the method can be used for researching the control method of the composite rotor aircraft.

A computer-implemented system and method of non-linear modeling in a computer system having a limited precision processor is provided. A non-linear model is initialized by forming an objective function having one or more functional components and a marginal variance matrix. The model is then iteratively solved using the computer processor until it has converged to a feasible solution. In doing so, the feasibility of computing the objective function is evaluated by determining if the marginal variance matrix is positive definite, thereby indicating whether or not the computer processor is capable of calculating a feasible solution to the non-linear model. If the marginal variance matrix is positive definite, then the objective function and its gradient are computed using the marginal variance matrix. If the marginal variance matrix is not positive definite, then a surrogate marginal variance matrix is constructed that is positive definite and a surrogate objective function is constructed having components continuous first derivatives. The surrogate objective function and its gradient are then computed using the surrogate marginal variance matrix.

A receiver uses a wideband intermediate frequency (IF) in the analog domain and performs low IF down-conversion in the digital domain, using low-power, high-speed, high resolution analog-to-digital converters. The receiver can be integrated into an integrated circuit as one of several receivers. Such an integrated circuit may include multiple transmitters using adaptive non-linear modeling pre-distortion. The non-linear modeling may include memory. Imbalance in intermediate frequency in-phase and quadrature signals may be corrected in the digital domains. DC offsets in the intermediate signal may be corrected in both analog and digital domains. In one instance, the receiver provides a feedback receiver for the adaptive pre-distorter in a transmitter on the integrated circuit.

The invention provides a hydraulic motor preset performance tracking control method with hysteresis compensating. The method comprises the steps that 1. a double-vane motor position servo system mathematical model with hysteresis is established; 2. a preset performance tracking control method with hysteresis compensating is designed; and 3. system parameters are designed. Preset performance requirements are fully considered, system hysteresis nonlinearity and high gain feedback are considered, the hydraulic motor preset performance tracking control method with hysteresis compensating is provided, according to the method, hysteresis nonlinearity is subjected to modeling to form the sum of a linear term and a bounded disturbance term, designing of a following moving controller is very convenient, for system parameter uncertainty and a non-modeling disturbance term, a self-adaptation robust control method is used, and meanwhile good parameter estimation and robust boundedness stability are guaranteed.

In accordance with an example implementation of this disclosure, a receiver may comprise a signal reconstruction circuit and a nonlinearity modeling circuit. The nonlinearity modeling circuit may be operable to generate a look-up table (LUT)-based model of nonlinear distortion present in a received signal. An entry of the LUT may comprise a signal power parameter value and a distortion parameter value. The signal reconstruction circuit may be operable to generate one or more candidates for a transmitted signal corresponding to the received signal. The signal reconstruction circuit may be operable to distort the one or more candidates according to the model, the distortion resulting in one or more reconstructed signals. The signal reconstruction circuit may be operable to decide a best one of the candidates based on the one or more reconstructed signals.

The invention provides a nonlinear modeling method of a broadband piezoelectric energy capture system. The method comprises the following steps of: directly measuring nonlinear restoring force in the broadband piezoelectric energy capture system by using a force measuring instrument; fitting the data of the nonlinear restoring force in the system by adopting a polynomial equation, and then obtaining an expression of the nonlinear restoring force and parameter values in the expression; according to the Hamilton's principle, the theory of piezoelectricity, the Rayleigh-Ritz principle, the Euler-Bernoulli beam theory, the electric-field constant distribution theory and the Rayleigh theorem for damping, performing deduction to obtain an expression of a nonlinear dynamic model of the broadband piezoelectric energy capture system and parameter values in the model. According to the invention, a model with nonlinear output characteristics can be accurately predicted, and can be obtained simply.

The invention provides a non-linear modeling method based on near infrared spectroscopy and a system thereof. The method comprises the following steps: spectrogram of each experimental sample is acquired and converted into near infrared spectroscopic data; a part of each near infrared spectroscopic data is picked out at random as a calibration set, and a part is picked out as a validation set; thecalibration set and the validation set undergo principal component analysis to obtain a spectral feature space; in the spectral feature space, samples in the calibration set that are the most similarto the samples of the validation set are picked out as a calibration subset through a Mahalanobis distance method; and principal component number is extracted from the calibration subset as an inputlayer of a BP neural network to establish a regression model. By the above method, the problem of multiple correlations among various factors can be solved, and much noise and some useless informationare also avoided. Variable dimension is reduced, and based on nonlinear mapping ability and adaptive learning ability of the BP neural network, predictive stability and precision of the model are raised.

Method and system for non-linear modeling of physiological behavior, such as R-R intervals, in implantable devices, such as a rate responsive pacemakers, comprising a comprehensive modeling and optimization methodology based on fractional calculus and constrained finite horizon optimal control theory that allows for allows for fine-grain optimization of pacemaker response to heart rate variations; and the theoretical basis on which a hardware implementation of the fractional optimal controller that can respond to changes in the heart rate dynamics. Present invention describes a fractal approach to pacemaker control based on the constrained finite horizon optimal control problem. This is achieved by modeling the heart rate dynamics via fractional differential equations. Also, by using calculus of variations, the invention describes how the constrained finite horizon optimal control problem can be reduced to solving a linear system of equations. Finally, the invention describes the theoretical basis on which a hardware implementation become possible.

A non-linear modeling solving method based on matrix index electromagnetic transient simulation comprises the steps that first, under a state analysis frame, electromagnetic transient simulation models of a linear network and a grid-connected non-linear element are established, and then through subsystem interconnection relation, an overall electromagnetic transient simulation model of an electric power system to be studied is formed; after relevant simulation parameters such as simulation step sizes and convergence precision are set, a simulation program is started; in each simulation step size, a fixed point iterative method is used for solving a non-linear equation comprising a matrix index function, and the results are used as a state variable of the current moment; an output vector yn + 1 is obtained through an output equation, output files are written in, and a step size is pushed forward in a simulation mode; and iteration is carried out in sequence until simulation is over. The great numerical precision and the rigidity processing capacity of a matrix index integration method are kept, general modeling and simulation capacity is achieved on the non-linear performance of an electric power system element, and the application range in the electric power system electromagnetic transient simulation field of the matrix index integration method is expanded.

The invention discloses a PWM type DC-DC convertor stability analysis method based on a describing function method. The stability analysis method includes the following steps that a PWM type DC-DC convertor is linearly modeled to obtain a linear model, a first transfer function and a second transfer function; the describing function method is adopted to carry out non-linear modeling on a non-linear link in the PWM type DC-DC convertor to obtain a first describing function; the second transfer function is replaced by the first describing function to obtain a non-linear model; according to the first transfer function, the first describing function and the non-linear model, the stability of the PWM type DC-DC convertor is analyzed. The PWM type DC-DC convertor stability analysis method can accurately analyze the critical stable state of the PWM type DC-DC convertor, an obtained result is more accurate than that obtained by a traditional linear analysis method, thus the low frequency oscillation phenomenon occurring in the PWM type DC-DC convertor can be analyzed, and the analysis accuracy is high.

A system may include a controller configured to be coupled to an audio speaker. The controller may be configured to receive an audio input signal. The controller may also be configured to, based on a linear displacement transfer function associated with the speaker, process the audio input signal to generate a modeled linear displacement of the audio speaker, wherein the linear displacement transfer function has a response that models linear displacement of the audio speaker as a linear function of the audio input signal. The controller may further be configured to, based on an excursion linearity function associated with the audio speaker, process the modeled linear displacement to generate a predicted actual displacement of the audio speaker, wherein the excursion linearity function is a function of the modeled linear displacement and has a response modeling non-linearities of the displacement of the speaker as a function of the audio input signal. The excursion linearity function is determined by statistically minimizing an error between the modeled linear displacement and a measured displacement during an offline testing.

Techniques for non-linear modeling of a physical system are provided using direct optimization of look-up table values. A non-linear system with memory is modeled by obtaining physical data for the non-linear system by applying a set of input samples x(n) to the non-linear system and measuring an output y(n) of the non-linear system; directly computing parameters Φ of a memory model for the non-linear system from the physical data, wherein the memory model comprises one or more look-up tables having linear interpolation and wherein the parameters Φ produce a substantially minimum mean square error; and providing the parameters Φ for storage as entries in the one or more look-up tables. The mean square error can be determined, for example, using one or more of a least squares algorithm, a least mean square algorithm and a recursive least squares algorithm. The look-up tables are optionally used in a processor instruction to implement digital pre-distortion.

Methods and apparatus are provided for non-linear modeling of a physical system using look-up tables with polynomial interpolation. A non-linear function is evaluated for a complex input value by obtaining at least one look-up table with polynomial interpolation that represents the non-linear function, wherein entries in the look-up table comprise polynomial coefficients of at least degree two for different segments of the non-linear function; obtaining a point from the look-up table that is near a magnitude of the complex input value; and generating a complex output value by evaluating the polynomial coefficients at the point to perform a Taylor Series expansion from said point. The non-linear function characterizes, for example, a power amplifier or an inverse of a power amplifier and the look-up tables can be used, for example, to implement digital pre-distortion. The look-up table can be stored in a memory of a digital processor, and the polynomial interpolation can be performed as part of a user-defined non-linear instruction that takes a complex number as an input, x, and computes ƒ(x).

A system and a general method estimate figures of merit based on nonlinear modeling and nonlinear time series analysis. Terms in a nonlinear behavioral model that depend on nonlinear combinations of a fixed input signal value are precomputed, optimizing the behavioral model such that figures of merit are evaluated from a single short stimulus vector. The optimized nonlinear behavioral model can then be applied to evaluate figures of merit for multiple devices under test (DUTs) in a manufacturing line. A process continually verifies and adjusts the nonlinear behavioral model based on sub-sampling multiple DUTs in a manufacturing line and comparing their figures of merit based on nonlinear modeling with those based on conventional measurement procedures.

The invention relates to a failure prediction method based on the nonlinear failure reconstruction. The method comprises the following steps that (1), a KPCA model is utilized for carrying out off-line nonlinear modeling on process data monitored when a rotary mechanical system operates, carrying out abnormity detection and extracting failure information, wherein the KPCA model is the kernel principal component analysis model; (2), the failure degree is quantificationally described through the KPCA model and the abnormity detection in the step (1), and failure estimation is achieved under the failure reconstruction through the optimization method; (3), the development tendency of the estimated failure amplitude f is predicted through the multi-layer hierarchical method. The failure prediction method based on the nonlinear failure reconstruction can effectively improve the failure prediction efficiency, reduce false alarm rate and omitted alarm rate and lay the foundation for further researching the prediction maintenance technology of a complex mechanical system. The failure prediction method based on the nonlinear failure reconstruction can also be widely applied to online monitoring systems of large electromechanical devices of petrochemical enterprises, metallurgy enterprises, coal enterprises and other many enterprises.

A receiver uses a wideband intermediate frequency (IF) in the analog domain and performs low IF down-conversion in the digital domain, using low-power, high-speed, high resolution analog-to-digital converters. The receiver can be integrated into an integrated circuit as one of several receivers. Such an integrated circuit may include multiple transmitters using adaptive non-linear modeling pre-distortion. The non-linear modeling may include memory. Imbalance in intermediate frequency in-phase and quadrature signals may be corrected in the digital domains. DC offsets in the intermediate signal may be corrected in both analog and digital domains. In one instance, the receiver provides a feedback receiver for the adaptive pre-distorter in a transmitter on the integrated circuit.

The invention discloses a cascade DC-DC converter stability analysis method based on a describing function method. The cascade DC-DC converter stability analysis method includes the following steps: performing linear modeling on a linear part in a single-stage DC-DC converter in a cascade system through a small signal modeling method to obtain a first linear transfer function; performing nonlinear modeling on a switch link of the DC-DC converter through a describing function method to obtain a describing function; performing equivalent processing on a source converter through a converter equivalent method to obtain a second linear transfer function, and determining the stability range of a two-stage cascade DC-DC converter according to a relation between the second linear transfer function and the describing function; and performing equivalent processing on a load converter through the converter equivalent method to obtain a third linear transfer function, and determining the stability range of the two-stage cascade DC-DC converter according to a relation between the third linear transfer function and the describing function. The method of the invention can accurately determine the critical stable state of a converter system and effectively improve the accuracy of judgment results.

Embodiments of this invention include application of new inferential methods to analysis of complex biological information, including gene networks. In some embodiments, time course data obtained simultaneously for a number of genes in an organism. New methods include modifications of Bayesian inferential methods and application of those methods to determining cause and effect relationships between expressed genes, and in some embodiments, for determining upstream effectors of regulated genes. Additional modifications of Bayesian methods include use of time course data to infer causal relationships between expressed genes. Other embodiments include the use of bootstrapping methods and determination of edge effects to more accurately provide network information between expressed genes. Information about gene networks can be stored in a memory device and can be transmitted to an output device, or can be transmitted to remote location.

A polynomial kernel generator is configured to mitigate nonlinearity in a receiver path from a transmitter path comprising a nonlinear component in a communication device or system. The polynomial kernel generator operates to generate polynomial kernels that can be utilized to model the nonlinearity as a function of a piecewise polynomial approximation applied to a nonlinear function of the nonlinearity. The polynomial kernel generator generates kernels in a multiplier less architecture with polynomial computations in a log domain using a fixed number of adders.

The invention discloses a large dynamic range telescope aberration detection method, device and equipment and a medium, and the method comprises the steps: introducing a known defocusing amount afterthe calibration in a dome of a telescope, enabling a dislocation type curvature sensor to be located at one side of a focal plane, and obtaining a defocusing image; after the defocusing images are processed, obtaining deviation information of the main focus assembly relative to the main mirror from defocusing star point images in the two defocusing images located on the same side of the focal plane; establishing and training a neural network by taking the low-order aberration measured in each field of view as input and the acquired deviation information of the main focus assembly relative to the main mirror as output; and calculating the low-order aberration of each view field through a neural network, and obtaining the deviation amount corresponding to the main focus assembly. By utilizing the characteristics of small influence of curvature sensing aperture and large dynamic range, the wavefront information is obtained in a large range through simultaneous measurement of different defocused star point images, and the imaging quality of the telescope system is ensured under large disturbance in combination with the strong nonlinear modeling capability of the neural network.

The invention discloses a dynamic nonlinear PLS soft sensor modeling method based on Gaussian process regression, which can be used for industrial processes with strong time variability, coupling andnonlinearity. Firstly, the dynamic characteristics of industrial data are captured by augmented matrix. Then, Gaussian process regression is used to replace the linear relationship between the input and output score vectors in the partial least square modeling process, so that the partial least square method has the ability of nonlinear modeling. In order to verify the prediction ability of the model, the method is applied to the wastewater treatment simulation benchmark 1 model and the wastewater treatment process of a factory for soft sensor modeling. The experimental results show that the application of dynamic method and Gaussian process regression can significantly improve the prediction ability of partial least square regression model, which is more suitable for soft sensor modelingof complex industrial processes.

The invention discloses a wind power blade inherent frequency work condition compensation method based on nonlinear modeling. The method includes the steps that firstly according to the power P of a wind power generator SCADA, historical running data are divided into a plurality of modeling data sub-sets, and the modeling data sub-sets are divided into a modeling data training set and a model testing data set; secondly, normalization treatment is performed on elements in the modeling data sub-sets; thirdly, according to the modeling training data set after normalization, a corresponding observing memory matrix D is constructed, and then according to the constructed observing memory matrix D and the model testing data set Xtest corresponding to the observing memory matrix D, a correspondinginherent frequency prediction model is constructed; and fourthly, work condition parameters of a current unit are substituted into the corresponding inherent frequency prediction model, actually measured current inherent frequency and predicted current fixed frequency are subjected to subtracting operation, and blade inherent frequency work condition compensation is performed by utilizing a fixedfrequency deviation value. The method can accurately achieve work condition compensation of the wind power generator blade fixed frequency.

The invention relates to the field of direct-current transmission, in particular to a direct-current transmission converter valve open phase step circuit and an open phase step current determination method. The circuit comprises a stray capacitor Cs, a converter transformer leakage inductor Lmu, a power supply Us, a valve arrester Ra, a saturation resistor SR, a valve damping capacitor Cd and a valve damping resistor Rd. The determination method comprises the following steps of modeling the saturation resistor SR, a thyristor T and the valve arrester Ra in a non-linear mode, confirming the energy transfer relation of the converter valve open phase step circuit, analyzing a converter valve open initial state, simplifying the open phase step circuit, confirming the function relationship between phase step current and open phase step circuit parameters, optimizing system conditions and improving phase step current. An open instant energy transfer process is analyzed, the mathematic relation between the phase step current and the system parameters is built, and accordingly the open phase step current determination method which can correct to the ampere level is formed.