22 results about "Noise threshold" patented technology

The application belongs to the technical field of signal processing, and particularly relates to a non-coherent scattering ionospheric parameter non-ambiguous estimation method based on Monte Carlo, aiming to solve the problems of inaccurate parameter estimation and poor robustness in ionospheric parameter inversion in the prior art. The method comprises the following steps: receiving measured echo data, estimating the signal noise level and determining the prior information combination mode; obtaining an expected index based on a signal noise threshold mapping library, and judging whether a preset decision threshold is met; if the preset decision threshold is met, starting an optimization selection strategy based on Monte Carlo, and obtaining a candidate solution set; performing cluster analysis on the candidate solution set, selecting a solution with the optimal fitting degree from the solution cluster containing the largest number of solutions, and taking the solution as the final non-ambiguous estimation value. Through systematic Monte Carlo simulation, the application can quantitatively evaluate the inversion reliability under the current data condition, effectively avoid invalid calculation under adverse conditions such as excessive noise or insufficient prior information, and improve the robustness and success rate of estimation.

This invention provides an intelligent reminder method, device, and system for real-time noise detection and peripheral visual interaction, belonging to the field of human-computer interaction and intelligent environment technology. The invention uses a preset dual noise threshold and configures multimodal interactive device working mode switching rules. It collects ambient sound signals using an analog sound sensor and maps them to real-time decibel values ​​via an exponential conversion function. The real-time decibel value is compared with the dual thresholds to trigger a phased visual and tactile multimodal feedback strategy. Simultaneously, a supporting APP enables data interaction between the device and the cloud, completing multi-dimensional visual display, statistical analysis, and report generation of noise data. It also supports remote device control, personalized threshold settings, and non-confrontational social sharing of noise data reports. The invention also designs an integrated intelligent reminder device with a unified housing, integrating sound sensing, processing control, multimodal feedback, magnetic attraction, and Type-C power supply modules, enabling flexible switching between desk lamp, ambient light, decibel monitoring, and composite modes.

The application provides a hybrid vehicle engine output control method, a vehicle controller and a hybrid vehicle, and the method comprises the following steps: determining whether the noise data in the vehicle is greater than a noise limit threshold; if yes, reducing the output of the engine of the hybrid vehicle to a predetermined range and then executing the subsequent steps; if no, directly executing the subsequent steps. According to the scene parameter data, the current driving scene of the hybrid vehicle is determined, the noise threshold corresponding to the current driving scene is found from a preset scene-noise database, the noise data in the vehicle is compared with the noise threshold, and according to the comparison result, the current driving scene and the battery power, it is determined whether the preset noise control condition is met; if yes, the hybrid vehicle is switched to a pure electric driving state; if not, it is determined whether the preset noise control condition is met. According to the scene and the noise experience of the user, the state of the engine can be controlled, and the electric noise experience of the user is improved.

Systems and methods for noise reduction using synthetic audio are disclosed. One or more playback devices include first microphone(s) (e.g., air-conduction microphone(s)) and second microphone(s) (e.g., bone-conduction microphone(s)). In operation, based on a user voice input, first and second sound data streams are captured via the first and second microphone(s), respectively. The first sound data stream is evaluated to determine whether a noise threshold is exceeded. While the noise threshold is not exceeded, a synthetic sound data model is trained based on the first and second sound data streams. An audio output stream based on the first sound data stream is communicated to at least one second playback device. When noise is detected in the first sound data stream, a synthetic audio stream is mixed into the output audio stream. The synthetic audio stream can be produced based on the synthetic sound data model.

The application discloses a log intent recognition method and system based on semantic fusion and cross-view self-supervision, relates to the field of power internet of things safety monitoring, and comprises the following steps: inputting multi-source heterogeneous log data into a neural network model in the form of key-value pair sequences and training the neural network model; according to the causal correlation between sequence fields, performing masking on the result end field; driving the field name in the masked sequence to be soft-aligned to a semantic prototype; assigning a weight to the cross-view sequence and comparing the weight with a preset noise threshold to determine a noise suppression coefficient; using the soft alignment result and the noise suppression coefficient to construct a weighted sum loss and update the neural network model parameters; and inputting to-be-detected log data into the trained neural network model for intent recognition, thereby significantly improving the accuracy of log intent recognition.

The embodiment of the application provides a kind of earphone noise reduction method, device, wearable device and computer readable storage medium, belong to the field of noise reduction, the method comprises: detecting environmental noise;When the environmental noise is less than or equal to the first preset noise threshold, the ear canal parameter of user is acquired;According to the ear canal parameter, matching noise reduction filter parameter;According to the noise reduction filter parameter, the noise reduction processing in ear canal is carried out.In the environment of environmental noise less than the first preset noise threshold, ear canal adaptive detection function will be started, automatically detect the ear canal parameter of user, and automatically match noise reduction filter parameter, improve the effect of noise reduction, so that user can experience more suitable noise reduction effect.

The objective is to provide a power control device that can enhance resistance to power supply noise. [Solution] A power control device according to one aspect of the present invention is a power control device that controls a power supply to a display device including a touch panel, and comprises: a plurality of noise filters connected between the power supply and the display device, each reducing power supply noise of different frequency components; a determination unit that determines the power supply noise based on a signal value detected using a scan signal which is a first scan frequency for detecting a touch position in the touch panel and a predetermined noise threshold; and a modification unit that changes the frequency of the scan signal based on the determination of the power supply noise and changes the connected noise filters according to the changed frequency of the scan signal.

The application discloses a GNSS-SAR imaging method based on an iterative distance direction compressor mechanism, and comprises the following steps: S1, preprocessing received GNSS-SAR echo signals to generate initial distance direction compressed pulse signals; based on local direct signals, performing autocorrelation operation to generate an iterative distance direction matched filter; S2, using the iterative distance direction matched filter to perform one iteration on the distance direction compressed pulse signals; S3, if the noise of the iteration result is less than a noise threshold value epsilon, then entering S4; if the noise of the iteration result is not less than the noise threshold value epsilon, then entering S2; S4, based on the iteration result with the noise less than the noise threshold value epsilon, performing azimuth direction compression; and S5, splicing the results in each azimuth direction resolution grid to generate a final GNSS-SAR image.

This application provides a communication method and apparatus. The method includes: A first communication apparatus sends first information to a second communication apparatus. The first information may include at least one of the following: a first parameter, a second parameter, or a third parameter. The first parameter indicates a feedback manner of a CIR measurement report, the second parameter indicates a reference CIR tap, and the third parameter indicates configuration of a noise threshold. Therefore, in the method, at least one of the first parameter, the second parameter, or the third parameter is added to the first information, to support flexible configuration of a sensing control parameter, and help flexibly feed back the CIR measurement report. This meets requirements of different application scenarios.

This invention belongs to the field of urban noise management technology and provides a remote square dance sound noise control system, comprising: one or more speakers, each with an embedded volume control module, the speakers being distributed across one or more monitoring areas; a remote control terminal, which determines the noise threshold of the monitoring area and sends the noise threshold to the embedded volume control modules of the speakers within the monitoring area; after receiving the noise threshold, the embedded volume control modules within the monitoring area detect the noise volume inside the speakers, and when the noise volume inside the speakers is greater than or equal to the noise threshold, it shuts off the power supply circuit of the speaker motherboard of the speaker containing the embedded volume control module; this invention enables noise location and control to be specific to the speakers, achieving precise noise control and fairness. Simultaneously, the remote control terminal can set different noise thresholds for different monitoring areas, meeting the needs of regionally differentiated noise control.

The present application relates to a radar signal-to-noise ratio time series data denoising method, device, equipment and storage medium. The method comprises: adding adaptive white noise to the original signal to generate an adaptive noise-added signal; searching for extreme points in the adaptive noise-added signal; selecting key points from non-extreme points according to an adaptive selection strategy based on the extreme points; constructing an envelope line according to the extreme points and the key points, decomposing the adaptive noise-added signal based on the envelope line to obtain a set of intrinsic mode components; further decomposing the intrinsic mode components in the set of intrinsic mode components to obtain secondary intrinsic mode components; calculating the scale index of the secondary intrinsic mode components, and superimposing and reconstructing the secondary intrinsic mode components with all scale indexes greater than a noise threshold to obtain a final denoised signal. The method provided by the present application can reduce the degree of information loss, realize more complete decomposition of the signal, and improve the overall performance and practicality of signal denoising.

The application discloses a method for identifying indoor and outdoor scenes, which can be applied to the technical field of terminals and comprises the following steps: acquiring laser histogram information corresponding to each pixel point of a laser device; determining the mean value of noise level information detected by the laser device according to each laser histogram information; acquiring stroboscopic information of a light sensor; detecting whether there is an artificial light source in the environment where the electronic device is located according to the stroboscopic information; obtaining a detection result; and determining whether a target scene or a target object is in an outdoor scene or an indoor scene according to the comparison result of the mean value and a first noise threshold value and the detection result. Since the outdoor scene is greatly affected by ambient light noise and the indoor scene is less affected by ambient light noise, and whether the ambient light noise is caused by an artificial light source can be determined by judging whether there is an artificial light source in the environment where the electronic device is located, the target scene or the target object can be determined to be in the outdoor scene or the indoor scene.

Various aspects include active noise cancellation (ANR) headphones and methods for controlling such headphones. In some specific embodiments, a headphone includes: at least one electroacoustic transducer; and at least one control circuit coupled to the at least one electroacoustic transducer, the at least one control circuit being configured to detect acoustic interference in ambient sound, wherein the acoustic interference is characterized by a noise level in the ambient sound deviating from a noise threshold, and to disable an audio pass-through mode when the acoustic interference is detected.

This invention provides an adaptive high-frequency signal filtering and enhancement method for SAS imaging of subsea pipelines, relating to the field of signal processing. The method includes: performing acoustic propagation compensation on the original high-frequency echo signal; obtaining logarithmic domain distance data through range pulse compression and homomorphic logarithmic transformation; traversing the resolution cells to construct a joint discriminant factor; adaptively determining the global noise threshold set and classifying the resolution cells into noise-dominant regions, edge-textured regions, or flat regions; applying differentiated filtering strategies for different region types for range filtering; and combining the results with inverse exponential transform and azimuth-matched filtering to output an enhanced image. This invention achieves accurate region attribute identification through the joint discriminant factor, and by combining adaptive threshold segmentation and differentiated filtering, effectively suppresses speckle noise while preserving the pipeline edge structure, significantly improving the imaging quality of subsea pipelines.

This invention belongs to the field of industrial vision technology, specifically relating to a machine vision-based brushless controller production positioning method. The method includes: acquiring an original image and constructing a gradient structure tensor to extract gradient components; calculating local highlight skew features and local structural coherence features based on pixel distribution within a local window; obtaining a baseline noise threshold based on the background and highlight candidate regions, and then constructing a dynamic phase noise threshold with exponential amplification characteristics; using the dynamic phase noise threshold to perform spatial adaptive suppression on the phase information after two-dimensional logarithmic filtering in the frequency domain, obtaining a corrected phase consistency feature map; finally, calculating the translational deviation vector and rotational deviation angle through sub-pixel edge extraction and template matching, driving a robotic arm to complete positioning compensation. This invention improves the visual positioning accuracy of the brushless controller printed circuit board and the reliability of robotic arm compensation.

The application belongs to the field of variable frequency range hood, and discloses a noise reduction method and device. The method comprises the following steps: acquiring the current torque and the current rotating speed of a motor in a range hood; inputting the current torque and the current rotating speed into a pre-trained noise identification model to output a first noise identification result; if the first noise identification result is 0, outputting a noise prompt message to enable a user to adjust the torque and the rotating speed of the motor; and the first noise identification result being 0 indicates that the noise generated by the motor based on the current torque and the current rotating speed is greater than a preset noise threshold. The application can achieve noise reduction without structural changes.

The present application relates to the technical field of unmanned aerial vehicle detection, in particular to a segmented mean constant false alarm rate detection method based on FFT accumulation; first, the collected unmanned aerial vehicle digital signal is subjected to 75% time overlap FFT spectrum accumulation processing, then a segmented mean constant false alarm rate algorithm is used for dynamic threshold detection, a constant false alarm rate threshold V T is calculated, the size of the current frequency point data frame and the constant false alarm rate threshold V T is compared, and the index number and data frame of the frequency point greater than the constant false alarm rate threshold V T are output, the accuracy of noise threshold acquisition and the sensitivity of signal detection are improved, the problem of large noise variance fluctuation caused by non-uniform clutter such as GPS navigation, mobile phone communication signal and wifi signal in the environment is avoided, and more distant target detection is realized.

The application relates to the technical field of network space security and artificial intelligence application, in particular to a deep learning network security intrusion detection and response integrated method, which comprises the following steps: acquiring real-time service multidimensional feature data to be detected; inputting the semantic manifold reconstruction network to perform high-dimensional mapping and inverse mapping, and generating pure service ideal state data; constructing a differentiable attack simulator based on an attack feature knowledge base, determining a potential space gradient direction vector, superimposing the ideal state data features, and decoding to generate disturbed simulation state data; performing double-track differential calculation based on the data, extracting a real residual error vector representing the total amount of real anomalies and a theoretical residual error vector representing the corresponding attack theoretical difference; calculating the similarity of the two residual error vectors, comparing the difference between the real residual error vector module length and the preset noise threshold, and executing the intrusion judgment and response strategy for the real-time service multidimensional feature data; and the application effectively decouples the real anomaly and the theoretical attack difference, and reduces the false alarm rate.

The application discloses a kind of self-adapting noise threshold event detection method, system, equipment and medium, it is related to non-invasive load identification field, the method comprises: obtaining acquisition data sequence;According to acquisition data sequence, calculate active power sequence;Mean value window, event detection window and variance detection window are added to active power sequence;Mean value window and event detection window are moved, and self-adapting noise threshold is calculated once every time it moves, based on self-adapting noise threshold, determine whether there is event occurrence time, when detecting event occurrence time, variance detection window moves from event occurrence time, and the variance of power point in current variance detection window is calculated once every time it moves, and it is determined as steady state time node according to the variance and variance detection threshold value calculated;According to the power point before event occurrence time and the power point after steady state time node, feedback verification is carried out, and it is determined whether event occurrence time is event switching point.The application can improve the accuracy of event detection.

This invention discloses an intrusion prevention monitoring and early warning method and system, belonging to the field of image recognition technology. The invention performs Gaussian filtering with a noise threshold on motion difference images to obtain a structure separation map; then, contour extraction and filtering are performed on the structure separation map to obtain the direction enhancement weights for each pixel. The pixel values ​​are multiplied by the corresponding direction enhancement weights to construct a direction enhancement map; subsequently, the vertical continuity intensity of the direction enhancement map is multiplied by the width stability coefficient to obtain a human morphology continuous response map; simultaneously, a multi-scale morphological top-hat transform is performed on the structure separation map, and the significance coefficients are obtained through cross-scale saliency point statistics to modulate the structure separation map, constructing a salient structure response map; finally, a dual-channel neural network is used to process the salient structure response map and the human morphology continuous response map to obtain the human morphology recognition result. When the recognition result is a human body, an intrusion warning is triggered. This invention effectively improves the accuracy of intrusion prevention monitoring and early warning.

The application relates to the technical field of vehicle vibration, in particular to a mode coupling noise suppression method and device, a vehicle, a medium and a program product, wherein the method comprises the following steps: obtaining operation data of a motor and local modal data of the motor on a preset transmission path; based on the operation data and the local modal data, determining mode coupling noise of the vehicle; if the mode coupling noise is greater than a preset noise threshold, corresponding noise suppression instructions are generated, and the mode coupling noise is suppressed until the mode coupling noise after suppression is less than or equal to the preset noise threshold. Therefore, in the related art, the motor performance improvement and cost control are difficult to balance, the full working condition dynamic excitation under a wide speed range cannot be covered, structural changes lead to a long research and development cycle and increase the weight of the vehicle body, affect the endurance, lack of dynamic adaptive regulation and control ability based on real-time working conditions, and it is difficult to effectively solve the complex mode coupling noise and other problems from the source without sacrificing the core performance of the vehicle.