210 results about "Self estimation" patented technology

Techniques for performing accurate and automatic head pose estimation are disclosed. According to one aspect of the techniques, head pose estimation is integrated with a scale-invariant head tracking method along with facial features detected from a located head in images. Thus the head pose estimation works efficiently even when there are large translational movements resulting from the head motion. Various computation techniques are used to optimize the process of estimation so that the head pose estimation can be applied to control one or more objects in a virtual environment and virtual character gaze control.

In the proposed low complexity technique a hierarchical approach is created. An initial FFT based detection and range estimation gives a coarse range estimate of a group of objects within the Rayleigh limit or with varying sizes resulting from widely varying reflection strengths. For each group of detected peaks, demodulate the input to near DC, filter out other peaks (or other object groups) and decimate the signal to reduce the data size. Then perform super-resolution methods on this limited data size. The resulting distance estimations provide distance relative to the coarse estimation from the FFT processing.

The invention discloses a prediction method for the q-precentile life of an intelligent meter and relates to the technical field of reliability estimation of accelerated degradation data. The method comprises the following steps: performing degradation path modeling according to test data, and obtaining the pseudo life estimation of the intelligent meter under all stress levels according to the failure threshold value of given parameters; building a Weibull distribution-based accelerated degradation model of three parameters, such as temperature, humidity and electrical stress according to the pseudo life estimation results of the intelligent meter under all stress levels of an accelerated degradation test, so as to obtain the point estimation and covariance estimation of the acceleration model; and obtaining the lower estimation of parameter service life of the intelligent meter under a given reliability degree and a given confidence degree in normal use conditions according to the point and covariance matrix of the parameters of the accelerated degradation model. Due to the adoption of the method, the test time is effectively shortened, the test expense is reduced, and the quick and accurate estimation of a stable period of an accelerometer is realized.

The invention relates to a method for real-time estimation of the queuing length of a signalized intersection based on a vehicle track. The method comprises the following steps: (1) judging a vehicle traffic state according to real-time vehicle traffic information; (2) estimating a vehicle queue-joining key point and a vehicle queue-leaving key point according to the real-time vehicle track information, vehicle traffic state and kinematical equation; (3) identifying an upstream reached fleet according to the estimated vehicle queue-joining key point; (4) performing queuing wave and evanescent wave estimation according to the estimated vehicle queue-joining key point, the queue-leaving key point and the identified fleet; and (5) estimating the intersection signal parameter and the queuing length according to the estimated queuing wave and evanescent wave. Compared with the prior art, the method is adaptive to a data environment with low sampling frequency and low sampling rate, and has the advantages of strong robustness, high real-time performance, good accuracy and the like.

The present invention is directed to a context-based image retrieval (CBIR) system for disease estimation based on the multi-atlas framework, in which the demographic and diagnostic information of multiple atlases are weighted and fused to generate an estimated diagnosis, on a structure-by-structure basis. The present invention demonstrates high accuracy in age estimation, as well as diagnostic estimation in Alzheimer's disease. The system and the pathology-based multi atlases can be used to estimate various types of disease and pathology with the choice of patient attributes. The present invention is also directed to a method of context-based image retrieval.

The invention provides an accurate linearization method of a measurement equation for electric power system state estimation. The accurate linearization method is characterized by including steps of establishing a network model and calculating a nodal admittance matrix; selecting state vectors and measurement vectors; and forming a jacobian matrix so as to get the accurately linearized measurement equation. The accurately linearized measurement equation is obtained by selecting the state vectors and the measurement vectors, and the state vectors can be solved by means of any types of existing state estimation according to the accurately linearized measurement equation, and estimation values such as all branch power and node injection power in the network can be acquired, so that complexity of the state estimation model is reduced greatly and the equation is easy to solve.

A spur detection and spur cancellation apparatus in a multiple sub-carrier digital communication receiver includes a spur detection block that estimates, using one or more Fourier transforms, a frequency location of a narrowband interference spur in a received digital signal that includes a plurality of sub-carriers, and a spur cancellation block that attenuates the estimated narrowband interference spur. The spur detection block may use a fast Fourier transform (FFT) and/or a discrete Fourier transform (DFT) to locate a frequency and to measure a discrete power spectra of the narrowband interference spur. A channel state information block in the receiver may adjust a channel state information metric based on the located frequency and/or the measured discrete power spectra of the narrowband interference spur.

The invention discloses a hybrid measurement based power distribution network dynamic state estimation method, which comprises the steps of reading current network parameters and a network topology structure of a power distribution network, and forming a node admittance matrix and a branch-node association matrix; reading SCADA data and PMU data of each node of the power distribution network, configuring a mapping relation between the two kinds of data, and processing differences between the two kinds of data; building a state transition equation and a measurement equation which are adapt to PMU/SCADA hybrid measurement; adding a fault-tolerant mechanism to a traditional extended Kalman filter method, and performing state estimation on the power distribution network by adopting the improved extended Kalman filter method. Dynamic state estimation is applied to hybrid measurement, and the accuracy of state estimation is improved. Meanwhile, an adaptive data detection mechanism is introduced, and the accuracy of dynamic state estimation is improved.

The invention discloses a position and speed combined estimation method for satellite navigation, which solves the problem of real-time estimation of the position and speed of a receiver when an accurate carrier phase measured value cannot be acquired by modeling a recurrent Doppler measured value of the receiver and performing coupled solution with a pseudo-range measurement model based on the correlation between the Doppler measured value and the position of the receiver. The method comprises the following steps of: performing combined estimation on positioning and speed measurement at each new epoch moment according to the current pseudo-range measured value and Doppler measured value; and weighting least square based on a nonlinear equation system to solve an estimated position in an iterative process to replace a pseudo-range positioning result to serve as a reference position for the speed estimation of the receiver, so that the speed estimated value is gradually converged along with the position estimation. Meanwhile, estimation error comprises speed error to ensure that the algorithm convergence judgment is stricter, and the search step of an algorithm around the actual position is reduced so as to acquire higher estimation accuracy. By the method, real-time positioning and speed measurement can be reliably realized, and the method is suitable for various satellite navigation systems such as a global positioning system (GPS), a global orbit navigation satellite system (GLONASS) and the like.

The invention belongs to the technical field of signal processing, and relates to a speech enhancement method based on speech presence probability and phase estimation. The method comprises the following steps: (1) estimating the speech presence probability; (2) estimating the pure voiced phase; (3) estimating the pure speech magnitude spectrum; and (4) estimating pure speech signals. The Q value is estimated through a multivariable linear regression technology, and the accuracy of speech presence probability estimation is improved. The pure voiced phase is estimated between adjacent bands using a harmonic model of short-time Fourier transform domain. The pure speech magnitude spectrum is estimated based on the phase difference, and the compensation effect of phase on the pure speech magnitude spectrum is fully utilized. The speech enhancement method of the method is a single-channel speech enhancement method. Speech signals with noise are collected using one microphone. The method is easy to implement. The problem that estimation of speech presence probability is inaccurate can be well solved. The compensation effect of the voiced phase and the phase difference on the pure speech magnitude spectrum is fully utilized. Thus, the performance of the speech enhancement method is improved.

The method includes measuring an operating parameter comprising at least one of a phasor current and phasor voltage of an electrical machine. The method further includes determining a diagnostic parameter indicative of a fault of the electrical machine based on the measured operating parameter. The method also includes estimating end of life of the electrical machine based on the diagnostic parameter using an error minimization method.

The invention provides an output feedback control method of a motor position servo system based on state estimation. The method comprises the steps that firstly, a mathematical model of the motor position servo system is established; secondly, a motor output feedback controller based on state observation is arranged; thirdly, parameters in a robustness controller based on finite time interference estimation are adjusted to enable the system to meet the control performance index. According to the output feedback control method, the motor position servo system model is established according to the characteristics of the motor position servo system. The motor output feedback controller based on state observation is designed, estimates the system state and is used for designing controllers, the effect on the controllers of measurement noise is avoided, the problem of uncertain nonlinearity of the motor servo system can be effectively solved, the system control precision can meet the performance index under the interference conditions, and the design of the controllers can be simplified by means of the output feedback control method.

In a system and method for noise estimation with music detection described herein provides for generating a music classification for music content in an audio signal. The music detector may classify the audio signal as music or non-music. The non-music signal may be considered to be signal and noise. An adaption rate may be adjusted responsive to the generated music classification. A noise estimate is calculated applying the adjusted adaption rate. The system and method may mitigate the noise modeling algorithms being misled by the music components.

The invention relates to a method for on-line estimation of internal resistance of a power lithium battery. The method for on-line estimation of the internal resistance of the power lithium battery comprises the steps that an automobile is energized to travel, and a battery management system obtains the working condition of the automobile in real time; a current changing curve graph with the working condition same as or close to the real-time traveling working condition of the automobile is selected according to the real-time traveling working condition of the automobile; the maximum current value I1 and the minimum current value I2 in the current changing curve graph are selected; in the process of traveling discharging process of the automobile, when the current value at present is equal to the maximum current value I1, the battery voltage value at the moment is recorded as the minimum voltage value U2; when the current value at present is equal to the minimum current value I2, the battery voltage value at the moment is recorded as the maximum voltage value U1; the formula R=(U1-U2)/(I1-I2) is used for calculating the battery direct-current resistance R. Compared with the prior art, an auxiliary device or other externally-connected measuring devices are not needed, internal resistance value of the power battery can be estimated in an on-line mode in the traveling process of the automobile, the method is used only according to real-time battery voltage data and real-time battery current data in the traveling process of the automobile, and the method is simple, easy to implement, practical, and easy to popularize and use.

In a method and magnetic resonance (MR) apparatus for MR image reconstruction, an image reconstruction algorithm is used that operates on one calibration matrix that is formed by reorganizing a number of individual, undersampled k-space data sets respectively acquired by multiple reception coils in a parallel MR data acquisition from a subject exhibiting motion. The motion causes the k-space data sets to exhibit errors. In order to use the calibration matrix in the reconstruction algorithm, it is subjected to an iterative rank reduction procedure in which, in each iteration, a residual is calculated for each data point that represents how poorly, due to motion-induced corruptions, that data point satisfies the low rank constraint, and non-satisfying data points are removed from the data point for the next iteration. The resulting low rank matrix at the end of the iterations is then used to produce images with fewer motion-induced errors.

A method for state of health estimation and misalignment correction in a vehicle lane management system. Two lane sensing systems onboard a vehicle provide lane information to a lane management system, where one of the lane sensing systems may be a dedicated forward-viewing lane sensing system, and the other may use images from a surround-view camera system. The lane information is stored in a fixed-length, moving-window circular data buffer. A correlation coefficient is recursively computed from the lane information from the two lane sensing systems and used to calculate a state of health of the lane management system. A linear regression relationship is also computed between the data from the two lane sensing systems, and the scale factor and offset value are applied to the lane information from the second lane sensing system before a fusion calculation is performed on the lane information from the two lane sensing systems.

A method for a receiver to estimate phase of a carrier wave, including receiving a carrier wave carrying pilot symbols and data symbols extending between the pilot symbols, determining phase of the carrier wave at received pilot symbols, and interpolating the phase of the carrier wave at points between pilot symbols based, at least in part, on an estimated phase of demodulated data symbols. Apparatus for estimate phase of a carrier wave, including a unit for determining phase of the carrier wave at received pilot symbols, and a unit for interpolating the phase of the carrier wave at points between pilot symbols based, at least in part, on an estimated phase of demodulated data symbols. Related apparatus and methods are also described.

The invention discloses a scale estimation-based human face detection method. According to the method disclosed in the invention, a size of a human face on an image is estimated via human face scale estimation, the image is zoomed based on a human face scale, a suggestion frame extraction is performed rapidly via a full convolution network, and a human face detection result can be obtained via twotimes of cascaded classification and regression. According to the method, human face detection is performed based on combination of human face scale estimation and a cascaded convolution neural network, an overall calculation amount of human face detection can be reduced, overall time consumption for human face detection can be reduced, and human face detection effects can be ensured.