14 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.

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.

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.

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.

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 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.