53 results about "Free parameter" patented technology

In layered VDR coding, inter-layer residuals are quantized by a non-linear quantizer before being coded by a subsequent encoder. Several non-linear quantizers are presented. Such non-linear quantizers may be based on sigmoid-like transfer functions, controlled by one or more free parameters that control their mid-range slope. These functions may also depend on an offset, an output range parameter, and the maximum absolute value of the input data. The quantizer parameters can time-vary and are signaled to a layered decoder. Example non-linear quantizers described herein may be based on the mu-law function, a sigmoid function, and / or a Laplacian distribution.

Methods and systems for designing electromagnetic wave filters and electromagnetic wave filters designed using the methods and systems are disclosed. In one method, functions are selected whose linear combination define the surface of a filter for producing a desired phase-encoded image. Free parameter values are selected for the function and are varied. The values of the free parameters are observed with regard to an optimization function. Final values of the free parameters are selected based on the optimization function having a specific value or range of values.

A P-wave slowness-polarization data set resolving P-wave slowness against P-wave polarization angle is extracted from a multi-offset vertical seismic profiling data set. A function relating P-wave polarization angle to P-wave slowness, and being dependent on at least three free parameters, wherein in at least two of these free parameters information of shear wave velocity is absorbed together with one or more anisotropy parameters that characterize formation anisotropy is selected, and regression values found for the at least three free parameters by fitting the selected function to the P-wave slowness-polarization data set, The regression values may be utilized in a method of producing a mineral hydrocarbon fluid from an earth formation.

A method is described for examining a solidifying and / or hardening material such as cement, concrete or the like, using ultrasound waves emitted by an ultrasound transmitter, which penetrate the solidifying and / or hardening material, are continuously measured and analyzed. During solidification and / or hardening of the material, the signal shapes of the ultrasound waves penetrating the material, are recorded. The change with time of the compression wave velocity and / or the relative energy of the ultrasound waves and / or the frequency spectra of the ultrasound waves is extracted from the ultrasound wave shapes during the entire course of solidification and / or hardening of the material. This change with time of the compression wave velocity and / or the relative energy of the ultrasound waves and / or the frequency spectra of the ultrasound waves is approximated through a compensating function, preferably the Boltzmann function. The free parameters of the compensation function are associated with material properties and permit comparison of a current measurement with reference values of these parameters to permit determination of material properties of the examined material. A receptacle and an ultrasound transmitter for carrying out the method also are described.

The invention discloses a lithium ion battery service life forecasting method based on an integrated model and relates to a lithium ion battery cycle life forecasting method. The lithium ion battery service life forecasting method is used for solving the problem that the existing lithium ion battery is low in service life forecasting adaptability and poor in stability. The lithium ion battery service life forecasting method includes: performing preprocessing on battery cycle charging and discharging test testing data; adopting a Bagging algorithm to perform secondary resampling on a Train database; building a monotonous echo state network model; initializing inner connection weights of a monotonous echo state network, and repeating for T times to obtain T untrained monotonous echo state network sub-models; setting a first free parameter set and a second free parameter set of the monotonous echo state network model; integrating output RULi of the monotonous echo state network model, adopting the Test database to drive the integrated monotonous echo state network model, and obtaining remaining service life of a lithium ion battery. The lithium ion battery service life forecasting method based on the integrated model is suitable for lithium ion battery service life forecasting.

A dynamic predictor usable for rapid and accurate calculation of joint commands of an articulated dynamical mechanism describes the relationship between the joints in the form of a differential equation. The predictor solves this differential equation for predicted joint states by fitting a polynomial equation having free parameters describing the predicted joint states to the differential equations by minimizing the differential equation residuals. This minimization employs a series expansion allowing algorithmic differentiation.

A method for using artificial neural networks as a universal computing device to model the relationship between the training inputs and corresponding outputs and to solve all problems with estimation, classification, and ranking tasks in their nature. Raw data related to problems is obtained and a subset of that data is processed and distilled for application to this universal computing device. The training data includes inputs and their corresponding results, which values could be continuous, categorical, or binary. The goal of this universal computing device is to solve problems by the universal approximation property of artificial neural networks. In this invention, a practical solution is created to resolve the issues of local minima and generalization, which have been the obstacles to the use of artificial neural networks for decades. This universal computing device uses an efficient and effective search algorithm, Retreat and Turn, to escape local minima and approach the best solutions. Generalization for this universal computing device is achieved by monitoring its non-saturated hidden neurons as related its effective free parameters and In-line Cross Validation process. The output process of ranking is achieved by an added baseline probability retaining from best logistic regression model as a secondary order while the categorical results from a MLP neural network as the first order.

Estimating petrophysical properties of a hydrocarbon reservoir traversed by at least one wellbore comprises obtaining at least one core sample from the wellbore and obtaining a three-dimensional (3D) porous solid image of the core sample. A 3D pore scale model is generated from the 3D porous solid image. A distribution of reservoir fluids in pores of the reservoir is simulated by a microhydrodynamic simulation using the 3D pore scale models of the core samples and at least one petrophysical property of the reservoir by a microscale modeling using the simulated distribution of the reservoir fluids is simulated by fitting the at least one simulated petrophysical property to well logging data at a depth corresponding to a depth of taking the core sample using free parameters. Governing parameters of the 3D pore scale models are extrapolated along a logged part of the wellbore and the at least one other petrophysical property is estimated by simulation.

In layered VDR coding, inter-layer residuals are quantized by a non-linear quantizer before being coded by a subsequent encoder. Several non-linear quantizers are presented. Such non-linear quantizers may be based on sigmoid-like transfer functions, controlled by one or more free parameters that control their mid-range slope. These functions may also depend on an offset, an output range parameter, and the maximum absolute value of the input data. The quantizer parameters can time-vary and are signaled to a layered decoder. Example non-linear quantizers described herein may be based on the mu-law function, a sigmoid function, and / or a Laplacian distribution.

Soft-sensing method of crucial biochemical quantity in penicillin fermentation process based on fuzzy neural inverse and system structure thereof is a method for resloving the problem that the crucial biochemical quantity in penicillin fermentation process is difficult to be measured by physical sensor on-line and real-time. Fuzzy neural inverse soft-sensing method establishes a soft-sensor (11) model based on a kinetic equation in penicillin fermentation process (1), on this basis eatablishes an inverse model of the soft-sensor according to inverse system method, and then uses static fuzzy neural network (41) and a differentor to establish fuzzy neural inverse (4) through a free parameters determined by training the static fuzzy neural network, then the soft-sensor inverse is implemented, finally links the fuzzy neural inverse after the penicillin fermentation process to implement on-line and real-time soft-sensing of fungi concentration x[1], substrate concentration x[2] and products concentration x[3]. Specific implementation of the fuzzy neural inverse is the constructed fuzzy neural inverse system applies embedded microprocessor ARM processor.

The present invention provides a spoken language dialogue strategy generation method. The method comprises: the step S1) employing the mode of human being replacing a machine to collect a true man-machine dialog data sample; the step S2) based on an Agenda simulation user model, constructing a virtual user according to the dialog data sample for simulation of the true user behavior; the step S3) adding noise for the virtual user's semantic information, and constructing a noise channel; the step S4: constructing a dialogue strategy template according to the virtual user's semantic information; the step S5: extracting free parameters included in all the conditional statements in the dialogue strategy template to form parameter factors, and inputting the parameter factors into the genetic algorithm for optimization to obtain the optimal solution; and the step S6: applying the optimal solution to the dialogue strategy template to obtain a dialogue strategy. Compared to the current dialogue strategy made by hands, the spoken language dialogue strategy generation method has better noise robustness; and moreover, the dialogue strategy language defined in the invention is easy to artificial edition and maintenance and is more suitable for the business environment having strict requirement for the system behaviors.

The invention provides an end wall molded line modeling method for an intermediate case of a gas compressor. Fitting and adjusting of a hub and a molded line of the intermediate case of the gas compressor are completed through the Nom-Uniform Rational B-Spline curve and perpendicularity equal-division point moving method, the problem that a general method does not exist in the existing geometric design field of the intermediate case is solved, and complicated geometric molded lines such as the intermediate case with the large curvature change characteristic can be described mathematically and accurately. Meanwhile, the number of a plurality of free parameters needed in a traditional experience method is decreased to two, and therefore two-dimensional parameterized modeling is faster, simpler, more efficient and higher in generality, and good aerodynamic design indexes can be met.

A configurable coding system and method of multiple error correcting codes (ECCs) for a memory device or devices are disclosed. The system includes an ECC codec that selectively performs different error corrections with different parameters. The system also includes means for providing a selected parameter to the ECC codec for initializing the ECC codec. The parameter used for initializing the ECC codec is an error-free parameter.

A model estimation device includes: a data input unit 101; a state number setting unit; an initialization unit; a latent variable variational probability computation unit which computes a variational probability of a latent variable so as to maximize a lower bound of a model posterior probability limited in degree of freedom; a component optimization unit which estimates an optimal type of each component and a parameter thereof so as to maximize the lower bound of the model posterior probability limited in degree of freedom and separated for each component of a latent variable model; a free parameter selection variable computation unit which computes the free parameter selection variable; an optimality determination unit which determines whether or not to continue the maximization of the lower bound of the model posterior probability; and a result output unit.

Image data is transformed for display on a target display. A sigmoidal transfer function provides a free parameter controlling min-tone contrast. The transfer function may be dynamically adjusted to accommodate changing ambient lighting conditions. The transformation may be selected so as to automatically adapt image data for display on a target display in a way that substantially preserves creative intent embodied in the image data. The image data may be video data.

A method of determining a residue function in brain tissue, from medical images acquired after introducing contrast agent into the blood, correcting for contrast agent leakage into the tissue, comprising: a) providing time signals indicating contrast agent concentration for leaking voxels, a time signal indicating average contrast agent concentration for non-leaking voxels, and an artery input function, all derived from the images; b) fitting the leaking voxel signals to a model time signal with a free parameter for leakage rate, the model assuming that the concentration of contrast agent perfusing through a leaking voxel has a same shape as a function of time as the average contrast agent concentration for non-leaking voxels; c) using the best fit leakage rate parameter to make a correction for leakage to the leaking voxel signals; and d) deconvolving the corrected signals from the artery input function, to find the residue function.

The invention discloses an adaptive electromechanical equipment weak fault characteristic extraction method. The method comprises steps that firstly, vibration signals of electromechanical equipment are acquired; secondly, two-scale similarity transformation of selected initial multi-wavelets is carried out to improve the approximation order of a multi-wavelet scale function; thirdly, a multi-wavelet lifting matrix satisfying symmetry and translation constraint conditions is designed, and a multi-wavelet integration construction method is realized; and lastly, based on the vibration signals, agenetic algorithm is utilized to optimize free parameters, an adaptive multi-wavelet base function matching with fault characteristics is acquired, and an advantageous method is provided for weak fault characteristic extraction. The method is advantaged in that the dynamic matching bottleneck in the weak fault characteristic extraction process in the actual monitoring and diagnostic application of the electromechanical equipment is solved.

The invention discloses a rotary model-based quasi dense corresponding point matching diffusion method. The method mainly comprises the following steps of: for a pair of fisheye images shot in the same scene from different positions, extracting and matching characteristic points in the images, and then accurately positioning the characteristic points, wherein the characteristic points are used as initial seed points; and performing quasi dense corresponding point diffusion from the optimal seed points to the neighborhood, wherein the diffused corresponding points are used as new seed points for subsequent continuous diffusion. In the method, a rotary conversion model is adopted for parallax constraints of the corresponding points, and compared with the conventional affine transformation model, the model is simple in calculation and has only one free parameter, so the whole diffusion process is stable and reliable and can meet most application requirements. In addition, the method is a non-constraint diffusion method, does not need to demarcate the motion parameters of a camera in advance, and has high flexibility. Experimental results verify the feasibility of the method, and the method has strong practicability.

The invention relates to a dynamic output feedback controller for a time-delay power system based on an LMI. Firstly, a time-delay power system state space model is built; the dynamic output feedback controller is given to the time-delay power system state space model; suitable conversion is carried out to a closed-loop system by utilizing a free parameter matrix; the existence criterion of the controller of the time-delay power system is obtained through combination of a Lyapunov-Krasovskii function; and then the solutions of a controller parameter and a functional parameter are resolved into a linear matrix inequality form through adoption of a parameterized method. According to the controller provided by the invention, the conservative property resulting from solving a non-convex optimization problem is overcome; a simulation result indicates that the dynamic output controller has certain time-delay insensitivity; and the stability of the power system is improved.

The invention provides a process publishing method for programming-free parameter configuration of mobile approval. The process publishing method for programming-free parameter configuration of mobileapproval comprises the following steps: step 1, selecting process name and step name to be configured; step 2, rearranging the style of the mobile approval form and setting the attribute of the control element; step 3, obtaining the tasks to be done and the tasks already done of the current user; step 4, obtaining the value corresponding to the page control element, and writing back the data. Theprocess publishing method for mobile approval without programming parameter configuration transfers the process of the PC terminal to the mobile device approval through the method of parameter configuration without programming, thereby improving the integrity, operation experience and maintainability of the form. Users only need to focus on the layout of mobile approvals, not on the relevance ofthe form data.

Provided is a robust Hinf spacecraft pointing control method and system based on feature structure configuration. A controller designed by the feature structure configuration method can provide complete parameterization representation of all control laws with desired characteristics or structures for the control system, and then a reasonable constraint condition is designed according to the characteristics of a spacecraft to select free parameters in the control laws. According to the method disclosed by the invention, the satellite robust Hinf high-precision pointing control design is carriedout by mainly taking the feature structure configuration method, according to the designed closed-loop control system result, the feature value of the reasonable closed-loop system is determined andis adjusted according to the normalized structure of an existing satellite controller, the main feature value of the on-satellite closed-loop control system is consistent to that of the invention, sothat the closed-looped system has the similar motion characteristics. The in-orbit verification of the spacecraft with uncertain large-flexible structures shows that the convergence and robust stability are high, and the high-precision pointing task demand in the long-term on-orbit operation can be guaranteed, thus the reliability of the system is improved.

The invention provides a simulation method and device for 3D Laplace domain acoustic wave equation value. The method comprises the steps of using average derivative method to establish a 27-point difference equation containing a plurality of free parameters on the basis of 3D Laplace domain acoustic wave equation; using the 27-point difference equation to determine the value of the free parameters through Laplace domain dispersion analysis; and using the 27-point difference equation which determines the values of the the free parameters to simulate values and output a seismographic record. By utilizing 27-point difference equation which contains a plurality of free parameters for value simulation, the invention can greatly improve simulation efficiency.

The invention discloses a mechanical equipment fault feature extraction method based on adaptive integrated multi-wavelets. The method combines the advantages of two-scale similarity transformation and a lifting frame, so that the approximation order of the multi-wavelet multi-scale function is improved, the regularity is enhanced, and the energy of signals in a frequency domain is more concentrated; at the same time, the vanishing moment of the multi-wavelet function is improved, so that the localization ability and the smoothness are also improved, and higher-order complex signals can be described and expressed more accurately. An adaptive multi-wavelet basis function for signals to be analyzed is constructed by designing free parameters in the construction process, selecting specific basis function evaluation and optimization criteria and combining free parameters in the optional selection construction process of an optimization method such as a genetic algorithm, to realize the extraction of weak fault features.

Object detection (58) uses a deep or multiple layer network (72-80) to learn features for detecting (58) the object in the image. Multiple features from different layers are aggregated (46) to train (48) a classifier for the object. In addition or as an alternative to feature aggregation from different layers, an initial layer (72) may have separate learnt nodes for different regions of the image (70) to reduce the number of free parameters. The object detection (58) is learned or a learned object detector is applied.

The invention discloses a state estimation method based on novel adaptive high-order unscented Kalman filter, which belongs to the field of high-speed carrier state estimation in passive radar tracking. The method provided by the invention comprises the steps that a non-linear discrete state model and a measurement model of a target tracking system are established; the optimal free parameter k isselected according to the state dimension of the target tracking system; a high-order UT is established to acquire state adoption points and weights; sampling points are transferred through a nonlinear function; the optimal adaptive factor is brought into a state one-step prediction covariance matrix; a high-order UT is established to acquire measurement adoption points and weights; the sampling points are transferred through the nonlinear function; a gain matrix is calculated; and posterior state estimation output and the output of the covariance matrix are carried out. According to the invention, the influence of a strong nonlinear maneuvering target and large mutations on a filter is effectively suppressed; the method has a good influence on different sampling intervals and different corner rates; and the influence of dynamic model errors is reduced.

The invention relates to a method and a system for displaying a key monitoring interface of a monitoring system. The method comprises the steps of receiving monitoring parameters and dividing the monitoring parameters into waveform-carrying parameters and waveform-free parameters; displaying the waveform-carrying parameters in the key monitoring interface, and displaying the waveform-free parameters in the rest area after the waveform-carrying parameters are displayed in the key monitoring interface; and arranging the waveform-carrying parameters preferentially and then arranging the waveform-free parameters after the received monitoring parameters are classified. As the waveform-carrying parameters and the waveform-free parameters are processed separately and displayed in the key monitoring interface, the processing logic complexity is simplified; and as the method is in accordance with the operating habit of a user, operating steps can be reduced, and operation convenience is improved.

A dynamic predictor usable for rapid and accurate calculation of joint commands of an articulated dynamical mechanism describes the relationship between the joints in the form of a differential equation. The predictor solves this differential equation for predicted joint states by fitting a polynomial equation having free parameters describing the predicted joint states to the differential equations by minimizing the differential equation residuals. This minimization employs a series expansion allowing algorithmic differentiation.