16results about How to "Good estimate" patented technology

Improved techniques for estimating parameters of a jamming signal. An input signal is identified. This input signal is suspected of being a jammed composite signal. Attributes of a reference signal are determined. The reference signal is an expected signal that was expected to be received. A form fitting operation is performed in which the reference signal is formed fitted with the input signal. The reference signal is subtracted from the input signal to generate an isolated output signal. A suspected portion of the isolated output signal is identified. An estimated symbol rate and an estimated center frequency for the jamming signal are determined based on the suspected portion. The estimated symbol rate and the estimated center frequency are used to facilitate a subsequent mitigation operation of eliminating or reducing an impact of the jamming signal against the signal of interest.

The application discloses a product environment stress estimation method, system, device and storage medium, which is applied to the product evaluation technical field and comprises the following steps: receiving environment stress time series data of a measured product at each set detection position collected by a sensor; determining each stress extreme position and an environment stress value of the measured product under a determined working condition; constructing a Kriging model; inputting physical size information of the measured product, coordinate information of each set detection position, environment stress time series data, coordinate information of each stress extreme position and the environment stress value into the Kriging model and performing interpolation through grid division to obtain each environment stress field matrix of the measured product output by the Kriging model in time sequence, and determining an environment stress value of a target position at a target time. According to the scheme, the environment stress at each position of the measured product at each time can be conveniently and effectively estimated, and the accuracy is relatively high.

The embodiment of the application provides a face posture estimation method, which comprises the following steps: obtaining a target face image, performing feature extraction processing on the target face image through a preset feature extraction network to obtain face angle features of the target face image, performing feature conversion processing on the face angle features through a preset feature conversion network to obtain a rotation matrix of the target face image, and determining a face posture angle of the target face image based on the rotation matrix. Through the above method, the face angle features are extracted and processed, the problem that the face posture estimation precision is not accurate enough and the speed is not fast enough at present is solved, and the face posture estimation effect is improved.

The application provides a human posture estimation behavior analysis method, comprising: processing human image information into picture data, obtaining global posture features of each group of pictures, and obtaining an image frame sequence with human two-dimensional key point information based on the global posture features; establishing a motion model according to the image frame sequence, estimating the task motion state in the image frame sequence, constructing a Transformer model, and generating posture hypotheses based on a multi-hypothesis generator of the Transformer model to regress each group of posture hypotheses to generate posture hypothesis information; constructing a behavior prediction network, learning based on pre-collected posture data to obtain optimal parameters of the network; applying the optimal parameters to the behavior prediction network, predicting the posture hypothesis information based on the behavior prediction network, and finally outputting predicted posture estimation data. The application does not require manual parameter setting, improves the efficiency and accuracy of neural network parameter searching, is simple to operate, and is convenient for staff to use.

A subspace-constrained unlicensed large-scale MIMO active user and channel joint estimation method is proposed. Under the GEC framework, the subspace strategy is integrated, and matrix inversion operations within the subspace are used to replace matrix inversion operations in the full-dimensional space. The low-precision quantized uplink received signal matrix received by the base station is iteratively processed to achieve joint channel estimation and user active state estimation, which greatly reduces the computational complexity of the algorithm. In addition, by modeling the hybrid channel as mutually independent conditional distributions, the channel column correlation is decoupled using cyclic belief propagation (LBP), thereby enabling parallel operation of hybrid channel posterior mean estimation, which greatly reduces the algorithm's running time.

This application provides a modeling method, a modeling apparatus, an electronic device, and a storage medium; the modeling method includes: constructing a fourth model based on a first model, a second model, and a third model; the fourth model is used to predict the lifetime of an isotope power source; wherein, the first model characterizes the effect of device temperature difference decay on the lifetime of the isotope power source; the second model characterizes the effect of device material irradiation damage decay on the lifetime of the isotope power source; and the third model characterizes the effect of device material thermal aging on the lifetime of the isotope power source.

This application relates to a method and device for monitoring vascular parameters. The method includes: acquiring finger pressure information and finger arterial physiological information during a monitoring period; obtaining the actual value of the oscillation envelope using the finger arterial physiological information, and obtaining the actual value of the pulse transit time using the finger arterial physiological information; obtaining a first model; obtaining a second model; and simultaneously optimizing the objective function using the first and second models to obtain estimated values ​​of vascular parameters during the monitoring period. The objective function is generated based on a first error and a second error, where the first error is obtained from the actual value of the oscillation envelope and the estimated value of the oscillation envelope generated based on the first model, and the second error is obtained from the actual value of the pulse transit time and the estimated value of the pulse transit time generated based on the second model. This method can improve the accuracy and robustness of vascular parameter estimation.

This invention discloses a method for estimating the spatial power spectrum of a small-aperture linear array based on ellipsoidal semi-axis measurement, comprising: S1. acquiring a time-domain data matrix; S2. calculating a frequency-domain data matrix; S3. calculating a set of frequency indices; S4. decimating the frequency-domain data matrix; S5. determining a set of scanning directions; S6. calculating a time compensation vector; S7. calculating a phase compensation matrix; S8. performing phase compensation on the decimated frequency-domain data matrix; S9. constructing and solving a positive semi-definite programming problem; S10. calculating the ellipsoidal semi-axis measurement; and S11. calculating the spatial power spectrum based on the ellipsoidal semi-axis measurement. This method directly utilizes the frequency-domain data matrix to estimate the spatial power spectrum, eliminating the need to calculate the signal covariance matrix or perform eigenvalue decomposition. While reducing computational complexity, compared to traditional spatial power spectrum estimation methods based on conventional beamformers, it is more advantageous for estimating target directions when the number of array elements is small or the element spacing is much smaller than half the signal wavelength.

The present application belongs to the technical field of hydrogeological parameter measurement, and discloses a kind of spatio-temporal quantitative expression method of hydrogeological parameter based on non-contact observation method, spatio-temporal quantitative expression method of hydrogeological parameter based on non-contact observation method includes: using the NMR geophysical prospecting method of different field source form, GPR geophysical prospecting method, TEM geophysical prospecting method collects different types, different structure geophysical data;And based on the different types, different structure geophysical data inversion obtains hydrogeological parameter;Based on D-S evidence theory, the hydrogeological parameter obtained by inversion is merged with the collected hydrogeological data to obtain the best estimate of the hydrogeological parameter.The present application merges the measured different types, different structure geophysical data and the collected hydrogeological data to obtain the best estimate of the hydrogeological parameter, and quantifies the uncertainty factor.

This invention belongs to the field of power technology and discloses a power grid frequency estimation method and system based on an event camera. The invention first records the event stream corresponding to light source flickering in a lighting environment using an event camera; then, it resamples the event stream along the time dimension to obtain several uniformly sampled event blocks; next, it performs polarity normalization on all event blocks to obtain the polarity of the lighting intensity change for each event block within its corresponding time period; it combines the polarities of the lighting intensity change of all event blocks chronologically to obtain a complete lighting polarity sequence; finally, it performs time-frequency analysis on the lighting polarity sequence to obtain the power grid frequency estimation information corresponding to the lighting environment. This invention can obtain good power grid frequency estimation results.

In an elevator system, an acceleration detector detects vertical acceleration, which is acceleration in a vertical direction, generated in a hoist body, and horizontal acceleration, which is acceleration in a horizontal direction, generated in the hoist body, the hoist body being at least either of a car and a counterweight. An estimation object is a long object having flexibility and is connected to the hoist body. A control device has a swing estimation section. The swing estimation section estimates a swing amount of the estimation object based on the vertical acceleration and the horizontal acceleration, and determines whether or not the estimation object has generated an abnormal swing.

The present invention provides a method comprising a step of estimating the kidney function of an arbitrary subject by a regression analysis which employs the amount of a D, L-amino acid in a biological sample from the arbitrary subject as an explanatory variable and employs the amount of filtrated glomeruli in the arbitrary subject as an object variable, by employing a previously determined formula (I): Y = a1·X1 + a2·X2 + ···+ an·Xn+b (I) [wherein a1 to an independently represent a constant obtained by the regression analysis; X1 to Xn independently represent a variable of the amount of the D,L-amino acid which is selected by the regression analysis; and b represents a constant obtained by the regression analysis] on the basis of the Y value calculated from the amount of the D, L-amino acid in the biological sample from the object to be evaluated. Also provided is a system for carrying out the method.

The application provides a multi-element step stress accelerated degradation modeling and reliability evaluation method, equipment and medium, comprising: obtaining step stress accelerated degradation data of a target product to generate a data set; establishing a multi-element step stress accelerated degradation model; fitting the data set by using the multi-element step stress accelerated degradation model to estimate model parameters; and calculating the product reliability of the target product under normal use conditions based on the estimated model parameters and the multi-element step stress accelerated degradation model. The application has the characteristics of clear model form, simple parameter estimation and easy application.

The present application provides a data assimilation method and system for predicting seawater quality change by using tide station records, and relates to the technical field of marine observation. The method comprises the following steps: selecting a tide station; calculating the global land mass migration change to obtain the sea level fingerprint effect; extracting the dynamic sea level change of the climate model and interpolating the dynamic sea level to the tide station record data; establishing an observation equation according to the selected tide station and using a sparse matrix to associate the state quantity and the observation quantity; introducing a random variable at each tide station to make up for the deficiency of the climate model in simulating the local dynamic sea level change; determining the initial time state of the tide station, optimizing and adjusting the constraint parameters of the state quantity and the correlation coefficient between adjacent tide stations; and based on Kalman filtering and smoothing, estimating the optimal state quantity and predicting the global seawater quality increase. The present application improves the accuracy of seawater quality estimation and realizes the coincidence and compatibility of model prediction and tide station observation data.

The invention discloses an unmanned aerial vehicle anti-interference and noise-reduction control method based on a composite extended state observer, and belongs to the technical field of unmanned aerial vehicle control. A filter is embedded in the extended state observer, so that the influence of zero-mean measurement noise on the attitude angular velocity is reduced, and time-varying interference is extended as a new state quantity, so that the attitude angular velocity of the unmanned aerial vehicle is improved. Effective estimation of time-varying interference is realized, estimation of the time-varying interference is improved, and the influence of measurement noise on the attitude angular velocity, especially control input, is greatly weakened. Time-varying interference is estimated through an extended state observer, and unknown dynamics caused by an external wind field and dynamics influenced by measurement noise are approximated by adopting a radial basis function neural network, so that the estimation performance of lumped interference is effectively improved; in addition, a decoupling term is embedded in the extended state observer, so that the conservative property of the control method is reduced, and the application range of the control method is expanded.

To improve the estimation of the arc voltage for use in the welding process, it is proposed that for estimating the arc voltage, the welding line (4) is modeled as a transfer system of an order greater than one with a welding line model (13), and the estimated value of the arc voltage is determined as the difference between the measured voltage at the measurement location (19) and the line voltage drop as derived.