22 results about "Statistical noise" patented technology

The invention relates to the technical field of X-ray imaging, and discloses an X-ray grating comprehensive imaging information extraction method and system. The method comprises the steps of obtaining and preprocessing original data; acquiring multi-dimensional interference parameters formed by grating phase drift distance, photon statistical noise density and imaging object deformation rate; dynamically calculating a phase correction coefficient, a noise suppression weight and information extraction confidence; phase compensation and noise filtering are executed based on the confidence coefficient, and structure and density information is extracted; parameter changes are monitored in real time, and the extraction process is updated; the system correspondingly realizes the method. The problem of low dynamic scene information precision caused by multi-interference coupling is solved, and the imaging information extraction stability and quality are improved.

The invention provides a trapped person position state analysis method and system, and relates to the field of data processing. According to the method, building structure distribution, conductive fluid flow channels and metal component distribution in a disaster target area are constructed to form a background entropy flow ground state, and noise intensity probability distribution, a channel joint fluctuation relation and a time stability index are counted to generate a background entropy flow field. In the search and rescue stage, a background entropy flow field is converted into a controlled mode through active disturbance, multi-physical channel noise responses before and after disturbance are collected through a multi-field passive sensor network, and a multi-dimensional local entropy response vector is constructed. And combining the consistency, directivity and duration of the multi-noise channel to identify an initial suspected region and extract an entropy anomaly core region, finally inferring metabolic activity and posture limitation conditions according to a local entropy response cooperative relationship in different disturbance modes, and outputting a position state result of the trapped person. By implementing the technical scheme provided by the invention, the position state of the trapped person can be accurately identified.

The application relates to the field of point cloud registration, and provides a point cloud registration method and system based on a multi-feature point point set. The method comprises the following steps: preprocessing point cloud by statistical noise reduction based on Gaussian distribution and voxel downsampling; extracting multi-feature points by adopting a directional bounding box algorithm, an improved internal morphological descriptor algorithm and a geometric centroid point algorithm; constructing a multi-feature point point set; and obtaining an initial transformation matrix by adopting a principal component analysis-based coarse registration algorithm; performing fine registration by adopting a G-ICP algorithm based on L2LOSS robust loss function optimization; and outputting a registration result. The application improves the accuracy and efficiency of point cloud matching and reduces the registration time.

The application discloses a kind of based on semantic drive's audio processing method and device;The method comprises: spatial decomposition is carried out to multi-channel audio signal, and forward target signal and backward environmental signal are extracted;Respectively carry out statistical noise reduction, obtain forward noise reduction gain and backward noise reduction gain;Respectively input acoustic semantic perception network, obtain forward and backward semantic probability vector;Based on semantic probability vector and semantic complementary weight matrix, the dynamic transmission weight of backward environmental signal is calculated;Weighted fusion is carried out using forward noise reduction gain, backward noise reduction gain and dynamic transmission weight, and enhanced audio signal is output;The present application transmits side rear important acoustic event on demand through semantic gating mechanism, retains environmental situation awareness capability while suppressing environmental noise, adopts statistical noise reduction and lightweight network heterogeneous deployment, meets the requirement of low delay and high fidelity of edge device, significantly improves the user experience of auditory enhancement device.

The application discloses a color adaptive equalization method for arbitrary trend joint based on space-time Kalman filtering, and belongs to the field of remote sensing image processing. In order to solve the problem that the existing joint color uniform method is difficult to adapt to arbitrary trend fold line joint and the parameter fluctuation caused by local statistical noise, the application comprises the following steps: globally pre-aligning buffer pixels; adopting a unified arc length parameterization setting control point along the joint and mapping into a one-dimensional sequence; calculating local correction parameters of each point as an observation sequence, and establishing a state space model, and recursively smoothing through bidirectional Kalman filtering; and interpolating the smoothed parameters to each pixel in the buffer area by using anisotropic spatial weight, and combining a hybrid coefficient controlled by the distance attenuation along the joint normal to control the correction strength. The application is used for color radiation consistency correction of remote sensing image mosaic splicing, and has the advantages of noise resistance smoothing, adaptation to arbitrary fold line joint and high calculation efficiency.

This invention provides a federated incremental modeling method based on dynamic probabilistic optimization in heterogeneous edge environments. The method includes the following steps: The class density vectors of devices in each factory, after statistical noise addition, are uploaded to a server; the server selects multiple candidate sets, calculates the distribution offset coefficient of each candidate device set, and selects the set with the smallest offset to participate in federated training; the selected device is trained and the optimal parameters are uploaded; the server aggregates and distributes global model parameters; the device calculates the newly added hidden layer output based on the global parameters and uploads it to the server; the server performs multi-index evaluation based on the device's performance, optimizes its selection probability using the Exp3 algorithm based on multi-index evaluation and fairness constraints, and selects the device to participate in training based on this probability; training ends when the number of hidden layer nodes exceeds the limit or the residual meets the expected tolerance, and the model is distributed to the device as a soft measurement model.

To provide an "active noise control system" that can cancel noise successfully in a high frequency range in a blind type configuration where noise is not detected upstream.SOLUTION: An update control section 16 causes an ICA processing section 15 to perform independent component analysis processing when a sound level output by a microphone 11 becomes great. In the independent component analysis, the ICA processing section 15 separates a noise component from observed sound data output by the microphone 11 by independent component analysis, and stores the data representing the separated noise component as statistical noise data 14. An adaptive filter 13, which performs adaptive operation using the output of the microphone 11 as an error, and outputs, as a noise cancellation sound NC from a speaker 12, a sound represented by the noise cancellation sound data, which is obtained by filtering the stored statistical noise data 14. The adaptive filter 13 also adapts the filter coefficients of the filter processing using the observed sound data output by the microphone 11 as an error.SELECTED DRAWING: Figure 1

The method and device for repairing Internet of Things signals complete the whole process of loss statistics, noise modeling, weight generation and sample separation locally at each Internet of Things node, do not need to upload the original data of the nodes, fully fit the core privacy protection characteristics of federated learning, realize the fine quantification of noise through data-driven loss distribution statistics, break through the ideal data hypothesis limitations of traditional schemes on sample balance, data isomorphism and modal integrity, can strongly adapt to complex non-ideal working conditions in actual deployment of the Internet of Things, and the finally output weight parameters and sample separation results can suppress the interference of noise on federated collaborative training from the data source level, provide high-reliability sample support and weight basis for subsequent robust federated model training, and effectively solve the pain points that the existing technology cannot adapt to heterogeneous scenes and has great difficulty in cross-domain adaptation.

A computer-implemented method (300) for generating a sample of statistical noise (η) to be aggregated, by an aggregation operation, with a result of a query (Q) in a differential privacy mechanism. The method comprises obtaining (310) data indicative of a statistical noise distribution; obtaining (320) one or more parameters (ϵ, ẟ) indicative of desired differential privacy guarantee; obtaining (330) a parameter (Δ Q ) indicative of a sensitivity of the query (Q) in the differential privacy mechanism; obtaining (340) a parameter indicative of a first natural number (ds) of significant digits for computing the aggregation operation in the differential privacy mechanism and / or indicative of second natural number (d0) of observable digits after the radix point for a result of the aggregation operation in the differential privacy mechanism; and generating (350) the sample of statistical noise (η) from the statistical distribution based on the one or more parameters (ϵ, ẟ) indicative of desired differential privacy guarantee, the parameter (Δ Q ) indicative of a sensitivity of the query (Q) in the differential privacy mechanism, and the parameter indicative of the first natural number (ds) and / or the second natural number (d0). Furthermore, the sample of statistical noise (η) is generated (351) using exact real arithmetic based on a Cauchy sequence.

The present invention addresses the problem of providing an "active noise control system" capable of satisfactorily eliminating noise even in a high-frequency region in a blind configuration in which noise is not detected upstream. [Solution] An update control unit (16) causes an ICA processing unit (15) to perform independent component analysis processing when the level of sound output by a microphone increases. In the independent component analysis process, the ICA processing unit separates noise components from observation sound data output from the microphone by independent component analysis, and stores data representing the separated noise components as statistical noise data (14). An adaptive filter (13), which performs an adaptive operation using the output of the microphone as an error, outputs, from the speaker, a sound represented by noise cancelling sound data obtained by applying a filtering process to the stored statistical noise data as a noise cancelling sound (NC). In addition, the adaptive filter adapts the filter coefficient of the filter processing using the observation sound data output by the microphone as an error.

The application provides a trapped personnel position state analysis method and system, and relates to the field of data processing. In the method, a background entropy flow base state is formed by constructing the building structure distribution, conductive fluid flow channel and metal component distribution in the disaster target area, and a background entropy flow field is generated by statistically analyzing the noise strength probability distribution, channel joint fluctuation relationship and time stability index. In the search and rescue stage, the background entropy flow field is converted to a controlled mode by active disturbance, and the multi-physical channel noise response before and after the disturbance is collected by relying on a multi-field passive sensing network to construct a multi-dimensional local entropy response vector. The initial suspected area is identified and the entropy anomaly core area is extracted by combining the consistency, directionality and duration of multiple noise channels. Finally, the metabolic activity and posture restriction condition are inferred according to the local entropy response coordination relationship under different disturbance modes, and the trapped personnel position state result is output. The technical solution provided by the application is convenient for accurately identifying the position state of trapped personnel.

A method and system for bandwidth reduction in a motion tracking apparatus are disclosed herein. The system includes an image sensor and a computing apparatus in communication with the image sensor. The method splits an input image into a 2x2 binned representation and a native-pixel clipped image, then applies a statistical noise modelling on each of them separately and then combines the results into one combined list of interesting points. The invention achieves a 50% reduction of bandwidth, neither sacrificing the launch precision or the distant resolution.

Systems and methods for estimating the accuracy, in the form of confidence intervals, of data released under Differential Privacy (DP) mechanisms and their aggregation. Reasoning about the accuracy of aggregated released data can be improved by combining the use of probabilistic bounds like union and Chernoff bounds. Some probabilistic bounds, e.g., Chernoff bounds, rely on detecting statistical independence of random variables, which in this case corresponds to sources of statistical noise of DP mechanisms. To detect such independence, and provide accuracy calculations, provenance of statistical noise sources as well as information flows of random variables are tracked within data analyses, i.e., where, within data analyses, randomly generated statistical noise propagates and how it gets manipulated.

The invention relates to the technical field of material dynamic mechanical property testing, and discloses an electromagnetic drive Hopkinson multi-field coupling data acquisition and calculation system and method, and the system comprises a physical loading subsystem and a multi-field resolving controller. The method comprises the following steps: firstly, performing ultrasonic signal decoupling based on Hilbert envelope and statistical noise features, and identifying a rough damage time window; then accurately positioning the crack initiation moment in the time window by using gray gradient entropy analysis; meanwhile, a conservation model of mechanical deformation work and heat dissipation energy is established in the plastic hardening stage of the test block, and the optimal lag parameter of the infrared temperature data is solved. And finally, aligning multi-field data by using the parameter, eliminating an adiabatic temperature rise effect, and generating a composition spectrum in combination with a crack moment. According to the invention, through acousto-optic heterogeneous cascade and energy conservation calibration, the problem that multi-physical field data time sequence dislocation and weak damage are difficult to identify is solved, and accurate characterization of the dynamic performance of the material is realized.

A continuous approximation register analog-to-digital converter includes sampling circuitry, comparator circuitry, and controller circuitry. The sampling circuitry generates first and second signals from a sampled signal. The comparator circuitry compares the first and second signals to generate a plurality of first decision signals. The controller circuitry generates a plurality of digital codes from the first decision signals and controls the comparator circuitry to repeatedly compare to generate a plurality of second decision signals, thereby generating a digital output from the digital codes, a statistical noise value, and the second decision signals. The controller circuitry also controls the sampling circuitry and the comparator circuitry during an initialization phase, wherein the comparator circuitry repeatedly compares from the sampled signal having an initial level to generate a plurality of third decision signals, and the controller circuitry performs a statistical operation from the third decision signals to obtain the statistical noise value.

The invention relates to the technical field of structure test, and relates to a full-field displacement calculation method based on self-statistical noise reduction and Gaussian enhancement, comprising the following steps: scaling a first image and a second image to obtain a first sub-pixel image and a second sub-pixel image; moving the first sub-pixel image based on a displacement threshold, storing a plurality of obtained first intermediate images as a multi-channel first tensor image, and performing edge expansion on the second sub-pixel image based on the displacement threshold to obtain a second tensor image; determining second intermediate data according to the channel data difference value between the single channel of the second tensor diagram and each channel of the first tensor diagram, performing pixel cross-correlation calculation based on each channel data of the second intermediate data, and determining sub-pixel displacement data; according to the regional pixel statistical values of the sub-pixel displacement data under different convolution scales, carrying out self-noise reduction on the sub-pixel displacement data to obtain noise-reduced displacement data; and performing Gaussian enhancement on the noise reduction displacement data to obtain a target full-field displacement result.

The invention relates to a vehicle partition statistical noise source prediction method, which comprises the following steps of: performing a wind tunnel test, synchronously performing whole vehicle wind tunnel noise source positioning and visualization test, and obtaining a vehicle wind noise source positioning result cloud picture under different working conditions and different frequencies; extracting 23 key parts from the wind noise source positioning result cloud picture according to a wind noise control strategy designed by a vehicle body; and performing partition statistics on the vehicle wind noise source positioning result cloud picture according to the divided key parts to form a unified standard table. According to the method, zoning statistics is carried out on a result cloud picture obtained by sound source localization and a visualization test in a wind tunnel test, so that generation parts of main noise sources and contribution of key parts to wind noise are made clear; noise sources can be accurately recognized, targeted measures can be taken to reduce noise, more importantly, control can be carried out in the automobile appearance design stage, the working efficiency can be greatly improved, time and resources are saved, the value in practical engineering application is high, and project development can be effectively supported.

The invention discloses a bridge damage identification method based on statistical noise reduction. The method comprises the following steps: step 1, obtaining bridge dynamic response data; 2, preprocessing the dynamic response data by means of a statistical algorithm, removing common factor components containing noise in the dynamic response data, and obtaining special factors; 3, performing secondary processing on the dynamic response data before and after damage to obtain a special factor matrix, and sequentially calculating a covariance index and an acceleration energy index; 4, performing data fusion on the covariance index and the acceleration energy index to obtain a damage identification index, and identifying a bridge damage position according to the damage identification index; the method has the advantages of high robustness, high recognition precision and difficulty in damage misjudgment.

The invention discloses a characteristic line determination theory electron transport calculation method based on continuous moderation approximation, and belongs to the technical field of radiation transport calculation and nuclear engineering numerical analysis. The method comprises the following steps of: depicting an electron transport process by adopting an electron transport equation containing a continuous moderated approximation operator; enabling a continuous moderated approximation operator to be equivalent to an energy group shift-out item and a lower scattering source item through rhombus difference approximation in an energy dimension, thereby reconstructing an electron transport equation into a standard multi-group Boltzmann transport equation form; and constructing multi-group pseudo cross-section data based on a discrete result, introducing an existing neutral particle characteristic line method solving framework, and realizing deterministic theory calculation of electron transport on the premise of not changing a solver core algorithm. Statistical noise of a Monte Carlo method is avoided, a mature solver can be directly reused to complete electronic transport calculation, and compared with a mainstream discrete longitudinal standard method, the method is more suitable for engineering calculation under complex geometric conditions and is easy to integrate with an existing transport analysis process.

The invention relates to a synthetic-datum-generating system (10) comprising a noising module (102), able to apply statistical noise to a training datum, iteratively for T iterations, in order to obtain a noisy datum based on which a generation module (103) is able to generate a synthetic datum by applying a generation model defined by first parameters. A partial noising module (104) is able to obtain a partially noisy synthetic datum based on the generated synthetic datum. A discriminator module (105) is able to determine a classification result for a set of data comprising a partially noisy datum issuing from the noising module after fewer than T iterations or the partially noisy synthetic datum issuing from the partial noising module. The first parameters of the generation model are modified according to the classification result.

A method (230) and system (100) for bandwidth reduction in a motion tracking apparatus are disclosed herein. The system (100) includes an image sensor and a computing apparatus (110) in communication with the image sensor (120). The method (230) splits an input image into a 2x2 binned representation and a native-pixel clipped image, then applies a statistical noise modelling on each of them separately and then combines the results into one combined list of interesting points. The invention achieves a 50% reduction of bandwidth, neither sacrificing the launch precision or the distant resolution.

The present invention relates to a method for determining the statistical noise level in the calculation of a subject's genetic copy number value in massively parallel nucleic acid sequencing data derived from a sample, as well as a method for determining a subject's genetic copy number value in massively parallel nucleic acid sequencing data derived from a sample and a method to determine a subject's genetic copy number value for stratifying the subject for cancer therapy.