32 results about "Noise band" patented technology

The invention discloses an ultrahigh-precision low-noise band-gap reference circuit, and relates to the technical field of integrated circuit design, the ultrahigh-precision low-noise band-gap reference circuit comprises a starting turn-off circuit, a reference core circuit, a high-order temperature compensation circuit and a digital trimming circuit, the starting turn-off circuit is connected with the reference core circuit, and the high-order temperature compensation circuit is connected with the digital trimming circuit through a Brokaw type band-gap reference topological structure. Accurate compensation of the voltage is achieved through deep negative feedback of the operational amplifier and a high-order temperature compensation circuit, and the temperature drift of the reference voltage is as low as 0.5-2 ppm / DEG C (-40 DEG C to 130 DEG C) and is increased by 5-10 times compared with a traditional band-gap reference (5-10 ppm / DEG C). The power consumption of the system can be saved by turning off the circuit when the circuit is not used, meanwhile, the digital trimming module is added to replace laser trimming in traditional engineering, the upper limit of the trimming range is improved, high-order temperature compensation and the digital trimming circuit are introduced, the precision of output voltage is improved, different devices are replaced, and the noise of the circuit is reduced. The problems that a traditional high-voltage band-gap reference temperature coefficient is high and noise is large are solved.

The invention relates to the technical field of logging, and discloses a logging-while-drilling mud pressure wave signal processing method and system, a terminal and a medium, and aims at acquiring noise signals of a mud pump, performing Fourier transform, determining working frequency band characteristics of the mud pump, acquiring and performing Fourier transform during pressure wave signal transmission, and determining current working frequency band characteristics. On the basis of the comparison result of the characteristics of the two sections of frequency bands, a proper filter is determined, quantitative and accurate filtering of noise signals is achieved, and the characteristics of original pressure wave signals are effectively recovered. The noise frequency band characteristic of the mud pump signal is determined by accurately analyzing the frequency band characteristic of the mud pump signal, and the recovery of the pressure wave signal is realized by combining the frequency spectrum characteristic of the pressure wave signal and based on the design and selection of a band-pass / band-stop filter; according to the signal processing method, noise filtering is carried out based on actual parameter adjustment to replace original experience-based setting, so that an engineer can rapidly debug instrument parameters based on operation parameters, and the instrument debugging time is shortened.

The invention discloses a multi-frame fusion fixed image noise dynamic compensation system and method, particularly relates to the technical field of image processing, and is used for solving the problem that fusion boundary noise has artifacts due to existing independent noise compensation. The method comprises the following steps of: establishing a mapping relation between pixel-level imaging parameter difference degree and fusion weight by acquiring a multi-frame image sequence of different imaging parameters and identifying a transition region of brightness gradient dramatic change; extracting a frequency domain energy skewness feature and a chroma phase change boundary feature of the transition region, and generating a noise visibility correction factor through nonlinear fusion; dynamically constraining the compensation intensity range to realize multi-frame noise compensation collaboration; and finally, performing cooperative compensation and fusion output within the constraint range. Fusion boundary noise discontinuity is effectively eliminated, and the visual quality of high-dynamic-range imaging is remarkably improved.

The invention discloses an anti-high dynamic Doppler low signal-to-noise ratio satellite signal blind detection method, which comprises the following steps of: performing frequency domain analysis on a delay correlation signal according to a signal symbol rate, and dividing a signal band and a noise band near the delay correlation signal to construct a detection quantity to perform constant false alarm rate (CFAR) detection; and finally, obtaining a final signal existence or disappearance result through time consistency judgment. According to the method disclosed by the invention, the analytic CFAR threshold and the state machine smoothing are combined, and the problem of detection failure in a low signal-to-noise ratio and high dynamic Doppler environment in the prior art is solved.

This invention provides a low-complexity multi-channel denoising and noise reduction method based on Kalman filtering, comprising: acquiring a signal and preprocessing the acquired signal to obtain a signal in the short-time Fourier domain; calculating a multi-channel noise covariance matrix; estimating multi-channel autoregressive parameters using the delayed, noiseless reverberant signal estimated in the previous frame and the acquired signal in the current frame, and determining the variance value of the Kalman state noise based on the sound source change detection result of the previous frame; estimating a noiseless reverberant signal using the estimated autoregressive parameters, the acquired signal in the current frame, and the estimated multi-channel noise covariance matrix; delaying the estimated noiseless reverberant signal and calculating the estimated noiseless late reverberant signal using the autoregressive coefficients; subtracting the noiseless late reverberant signal from the noiseless reverberant signal to obtain the desired direct sound and early reverberant signal. This invention reduces computational complexity and enables real-time applications in embedded products.

The application discloses a differential phase and attenuation joint estimation method for dual-polarized weather radar, improves the precision of phase and attenuation estimation by adaptively adjusting gamma H and gamma DP under high resolution, and reduces the deviation caused by delta HV and noise. The differential phase and attenuation joint estimation method can be applied to dual-polarized weather radar of any wave band, especially high frequency wave bands such as X, Ku and Ka wave bands, and the improvement effect is more remarkable. The application improves the precision of differential phase estimation and attenuation correction, and helps to improve the accuracy of quantitative precipitation estimation. In addition, the application does not introduce new parameters, only adaptively adjusts the relationship formula coefficient between attenuation and differential phase shift rate, and therefore can be applied to radar DSP to realize real-time processing of data.

The invention discloses a pulsating pressure measuring and processing method deducting wind tunnel noise, and belongs to the technical field of wind tunnel measurement tests. The problem of inaccurate pulsating pressure measurement caused by wind tunnel noise is solved. The method comprises the following steps: arranging a 10-degree cone model in a wind tunnel, collecting a pulsating pressure value of the air wind tunnel, carrying out Fourier transform to obtain a function of the pulsating pressure of the air wind tunnel in a frequency domain, and then constructing power spectrum functions of the air wind tunnel at different frequencies; the method comprises the following steps: arranging a test model in a wind tunnel, acquiring a pulsating pressure value on the surface of a measurement model, performing Fourier transform to obtain a function of the pulsating pressure on the surface of the test model in a frequency domain, and then constructing power spectrum functions of the surface of the test model under different frequencies; selecting the same frequency to obtain the amplitude of the corresponding frequency after subtraction, and then calculating the overall pulsating pressure coefficient after the pulsating pressure value of the wind tunnel is deducted; and acquiring pulsating pressure coefficients after the wind tunnel pulsating pressure values are deducted at different pressure points on the surface of the test model until all test states are measured and calculated.

The application discloses a multi-frame fusion fixed image noise dynamic compensation system and method, and particularly relates to the technical field of image processing, and is used for solving the problem of the existing independent noise compensation leading to the noise band artifact of the fusion boundary; a mapping relationship between the pixel-level imaging parameter difference degree and the fusion weight is established by acquiring a multi-frame image sequence with different imaging parameters and identifying a transition area with a dramatic change in luminance gradient; a noise visibility correction factor is generated by extracting the frequency energy skewness feature and the chroma phase change boundary feature of the transition area through nonlinear fusion; the multi-frame noise compensation is cooperated by dynamically constraining the compensation intensity range; finally, the cooperative compensation is executed within the constraint range and fused and output; the discontinuity of the fusion boundary noise is effectively eliminated, and the visual quality of the high dynamic range imaging is significantly improved.

This invention discloses a fault diagnosis method for elevator bearing components based on an improved empirical wavelet and wavelet packet convolutional neural network. The improved empirical wavelet method decomposes vibration signals into feature information of fixed frequency bands using a fixed bandpass filter design criterion. High-frequency filters in the filter bank are used as noise bands, and the corresponding sub-signals are filtered out and reconstructed as input samples for the network model. A multi-level wavelet decomposition full-component fusion structure is constructed using wavelet packet transform, resulting in a multi-level wavelet packet full-component residual module. This module is then embedded into a deep one-dimensional convolutional neural network. The elevator bearing component fault diagnosis model based on the multi-level full-component convolutional neural network is trained to diagnose faults in the sample signals, thereby achieving condition monitoring of the elevator bearing components.

The application discloses a single-photon laser radar fog-penetration three-dimensional imaging method based on synergistic photon processing, and relates to the field of single-photon laser radar three-dimensional imaging. The method solves the problem of how to reconstruct a high-quality target three-dimensional image by using a small amount of statistical frames under the interference of smoke and strong noise. The method comprises the following steps: through pixel-by-pixel signal accumulation compensation and a global noise suppression method, data preprocessing is completed, and a multi-scale superpixel three-dimensional imaging algorithm is used to generate a guide image; the denoised data is subjected to block processing, a depth image guided photon processing algorithm and a pure noise band noise isolation method of multi-dimensional Fourier transform are used, and accurate signal extraction is realized through synergistic photon processing in time, space and frequency; the denoised data is subjected to multi-scale block processing, reconstructed depth and intensity images under different scales are obtained, the obtained images are fused, and a three-dimensional image reconstruction result of smoke interference suppression is output. The method is suitable for the field of single-photon laser radar three-dimensional imaging under environmental conditions such as cloud and fog.

The application discloses a kind of based on audio time-frequency spectrum white band feature Hidden processing risk screening method, system and storage medium.This application collects the video or audio data and space semantic data of monitoring point and standardizes audio signal;It is generated decibel spectrum and time-frequency spectrum chart by short-time Fourier transform, and energy proportion is calculated in frequency band, and high-frequency weighted score is obtained in combination with gradient frequency band weight;Spectrum chart is grayed, threshold binarization, morphological processing and connected component analysis, extract white band quantity, density, time length and frequency width and other features;Fusion space semantics and acquisition time period calculate acoustic risk confidence, according to double threshold, divide low, medium, high risk level, synchronous output structured evidence, spectrum chart and original audio and video backtracking path.The application accurately identifies continuous processing abnormal sound according to noise band feature, and this method is suitable for non-contact hidden processing risk screening in urban village, old street, store back yard and closed courtyard periphery.

The invention provides a deep sea target line spectrum passive autonomous detection method and system, and the method comprises the steps: carrying out the frequency domain adaptive line spectrum enhancement of three vibration velocity channels through a vector coherent adaptive line spectrum intensifier, and filtering the broadband background interference; noise interference with the same frequency and different phases is filtered out through a vector sound intensity coherent detector; and carrying out background equalization on an output result of the vector sound intensity coherent detector by combining a two-pass separation filter, carrying out threshold judgment on a spectrum after background equalization, and outputting an autonomous detection result. The method has the advantages that the VCFB-ALE algorithm is used, broadband background interference can be filtered out, high-gain output line spectrums are reserved, and the method has high extraction capacity for the line spectrums under the deep sea complex background; by using a vector coherent detector, ircoherent noise interference in each direction can be further filtered out; the equalization algorithm based on TPSW filtering can effectively eliminate the influence caused by colored noise, and realizes the autonomous detection and extraction of line spectrum signals.

To provide a communication method in an encoder for determining which of two coding modes or groups of coding modes to use, along with related devices and nodes.SOLUTION: A method comprises: deriving a frequency spectrum of an input audio signal (1001); obtaining a magnitude of a critical frequency region in the frequency spectrum (1003); obtaining a frame peakedness measure (1005); obtaining a noise band detection measure (1007); determining which of two encoding modes or groups of encoding modes to use based on at least the peakedness measure and the noise band detection measure (1009); and encoding the input audio signal based on the determined encoding mode to use (1011).SELECTED DRAWING: Figure 10

The invention discloses a soil heavy metal hyperspectral remote sensing inversion method, device and system and a storage medium. The method comprises the following steps: acquiring indoor hyperspectral data, heavy metal copper content and hyperspectral remote sensing image spectral data; removing noise wave bands from the indoor hyperspectral data, and then carrying out SG spectrum smoothing; correcting spectral data of the hyperspectral image according to the indoor hyperspectral data subjected to SG spectrum smoothing processing; performing fractional order differential spectral transformation on the corrected spectral data of the hyperspectral image; taking the content of heavy metal copper as a dependent variable, taking spectral data of the hyperspectral image after fractional differential spectral transformation as an independent variable, inputting the dependent variable into a Transform feature selection framework, and establishing a soil copper content inversion model by using XGBoost to verify the effectiveness of Transform feature selection. By adopting the technical scheme of the invention, the characteristic waves of the heavy metals can be quickly and effectively identified and extracted.

The application discloses an electric toothbrush sound effect control system and method and an electric toothbrush. A pressure acquisition module is used to acquire the current pressure of the brush head of the electric toothbrush. When the pressure value of the pressure is within a preset first pressure range, a preset first note sequence is acquired. A first working frequency is obtained according to the note frequency of the first note sequence, and a first working beat is obtained according to the note playing time length of the first note sequence. The first pressure range is smaller than a second pressure range in which the brush head is attached to the teeth during tooth brushing. The working frequency is used to represent the vibration frequency, and the working beat is used to represent the vibration time length. The motor vibrates according to the first working frequency and the first working beat, so that the sound generated by the vibration is converted into a preset audio. The audio is a multi-frequency sound and has a melodious tune, and the discomfort caused by noise during tooth brushing can be reduced.

Provided is a technique capable of improving the quality of an electronic component unit. Shield layers (50) are disposed on a first surface (11a), a second surface (12a), and a third surface (13a) of a housing (10) of an electronic component unit (current sensor). The shield layer (50) employs various pastes (carbon paste and magnetic paste). Since the paste can be freely applied to a desired site, it is possible to configure an optimal shield structure, and it is possible to easily achieve both improvement in both dV / dt characteristics and EMC characteristics. In addition, by adding the magnetic paste, shielding of a radio noise band (a band having a frequency of about 0.1-5.0 MHz) is also possible. Furthermore, since the shield layer (50) is formed by a paste, the shield layer (50) can be configured at low cost compared with a metal shield (vacuum film formation such as vapor deposition or sputtering).

The invention relates to a spectral classifier for audio coding mode selection. A method in an encoder for determining which of two encoding modes or which of two sets of encoding modes is to be used is provided. The method comprises deriving (1001) a spectrum of the input audio signal. The method comprises obtaining (1003) an amplitude of a critical frequency region of the spectrum. The method includes obtaining (1005) a kurtosis measurement of the frame. The method comprises obtaining (1007) a noise band detection measurement. The method comprises determining (1009) which of the two coding modes or which of the two sets of coding modes to use based at least on the kurtosis measurement and the noise band detection measurement. The method comprises encoding (1011) the input audio signal based on the encoding mode determined to be used.

The present invention provides a method and device for eliminating electromagnetic radiation, and an electronic device. The method for eliminating electromagnetic radiation includes: detecting a first noise frequency band of electromagnetic radiation noise in a noise reduction area in an electronic device, obtaining a noise reduction device that matches the impedance of the first noise frequency band; arranging the noise reduction device in the noise reduction area, and absorbing the electromagnetic radiation noise based on the noise reduction antenna in the noise reduction device. The method for eliminating electromagnetic radiation provided by the present invention can eliminate the electromagnetic radiation noise in the noise reduction area in a targeted manner, thereby helping to improve the effectiveness of eliminating electromagnetic radiation noise.

The present disclosure describes aspects of adaptive energy limiting for transient noise suppression. In some aspects, an adaptive energy limiter sets a limiter upper limit of an audio signal to full scale and receives a portion of the audio signal. For the portion of the audio signal, the adaptive energy limiter determines a maximum amplitude and evaluates the portion with a neural network to provide a speech likelihood estimate. Based on the maximum amplitude and the speech likelihood estimate, the adaptive energy limiter determines that the portion of the audio signal includes noise. In response to determining that the portion of the audio signal includes noise, the adaptive energy limiter reduces the limiter upper limit and provides the limiter upper limit to a limiter module to effectively limit the amount of energy of the audio signal. This can effectively prevent the audio signal from bringing full energy transient noise into the conference audio.

The invention discloses a novel low-noise band-gap reference circuit, and belongs to the field of analog integrated circuits, the novel low-noise band-gap reference circuit comprises a band-gap reference core module and an operational amplifier module, the band-gap reference core module uses the difference of VBE of a BJT tube working under different current densities as PTAT voltage, the PTAT voltage is superposed with CTAT voltage to generate reference voltage with a zero temperature coefficient, and the operational amplifier module is connected with the operational amplifier module. The operational amplifier module adopts a double-pair operational amplifier structure to increase delta VBE, so that the amplification coefficient of band-gap reference voltage noise is reduced, noise suppression is achieved, and compared with a traditional band-gap reference source achieving the same noise suppression degree, the power consumption requirement is reduced. The circuit has the advantage of being easy to use, and is suitable for low-noise and high-precision application scenes.

To provide an art capable of enhancing the quality of an electronic component unit. A shield layer 50 is placed on a first surface 11a, a second surface 12a, or a third surface 13a of a case 10 of an electronic component unit (current sensor). For the shield layer 50, various pastes (a carbon paste and a magnetic paste) are adopted. Capable of freely coating a desired place, the pastes can form an appropriate shielding structure, making it possible to easily improve both a dV / dt characteristic and an EMC characteristic. Further, adding the magnetic paste enables the shielding of a radio noise band (a frequency band of around 0.1 to 5.0 MHz). Further, being formed of the pastes, the shield layer 50 can be formed at a lower cost than a metal shield (film formed by vacuum deposition such as vapor deposition or sputtering).

The invention relates to the technical field of seismic data processing, and discloses a signal-to-noise ratio optimization method and system for post-stack two-dimensional seismic data. The method comprises the following steps: performing well-to-seismic joint calibration on original two-dimensional seismic data to determine main target stratum distribution, and performing spectral analysis to identify a noise frequency band; based on the main target layer distribution, performing segmented Q compensation processing on the original data to obtain a seismic data volume after Q compensation processing; on the basis, spectrum shaping processing is carried out according to the identified noise frequency band so as to suppress the noise and preliminarily improve the signal-to-noise ratio; and finally, diffusion filtering processing is carried out on the data volume after spectrum shaping processing, and a final two-dimensional seismic data volume with an improved signal-to-noise ratio is obtained. According to the method, through series application of Q compensation, spectrum shaping and diffusion filtering, the continuity of the event is effectively improved, the definition of fracture imaging is improved, and a more reliable data basis is provided for structural interpretation and trap evaluation.

A quadrupole transmitting window applied by a quadrupole mass filter is characterized by a method that utilizes the noise band of a transmitted chemical noise ion signal. The mass filter may be utilized in a mass spectrometry (MS) system.

This invention discloses a noise processing method, apparatus, medium, and device for inertial navigation systems, relating to the field of inertial navigation system design. The method includes: conducting random vibration tests on the inertial navigation system to obtain test data; performing noise band testing on the test data using low-pass filters with different initial cutoff frequencies to determine multiple initial noise band ranges; within each initial noise band range, performing noise band testing on the test data using notch filters with different initial frequencies to obtain multiple target noise band ranges; the target noise band ranges are the noise band ranges generated by frequency aliasing; within each target noise band range, designing notch filter parameters for the target noise band range to obtain a target notch filter; and using the target notch filter to filter out the noise signal output by the inertial navigation system. This method can process noise signals generated by frequency aliasing in inertial navigation systems.

The invention relates to a noise reduction control method and system for an infant incubator and a storage medium, and relates to the technical field of noise reduction. A noise bandwidth filter used for filtering noise is decomposed into a plurality of narrow-band sub-filters in advance; collecting noise input of the incubator; analyzing the noise input through a pre-trained convolutional neural network to obtain a narrowband sub-filter weight vector adapted to the noise input, wherein the narrowband sub-filter weight vector comprises filter weights corresponding to all narrowband sub-filters; and carrying out weighted summation on the narrowband sub-filters and the corresponding filter weights to obtain a total filter, processing the input noise through the total filter, and superposing a processing result with a corresponding result of a primary path of noise input after the processing result is responded by a secondary path so as to realize noise reduction. The total filter adapts to dynamic adjustment of noise input, can adapt to different kinds of noise, meets the requirement for noise reduction of the baby incubator, provides a quiet environment for babies, and prevents the babies nursed in a centralized mode from affecting each other.

This application provides a real-time processing system for edge nodes of fluorite geological data, relating to the fields of intelligent power system inspection and non-contact fault diagnosis. First, it performs time alignment on heterogeneous data streams such as triaxial vibration acceleration, X-ray fluorescence pulse counting, and near-infrared spectral reflectance. Then, it adaptively adjusts the filtering intensity using the power spectral density of the vibration components, suppressing mechanical noise while preserving the narrow pulse characteristics of grade abrupt changes, thus solving the problems of detail loss and signal distortion caused by the overlap of noise bands and effective signals. Based on the energy spectrum characteristics of calcium and fluorine elements in fluorite, it performs significant weighted extraction, compressing the high-dimensional signal into a compact feature vector. Real-time grade inference is then completed through an edge-side quantization neural network. Finally, the compression ratio is dynamically adjusted according to the fluctuation amplitude of grade prediction: increasing the compression ratio to save bandwidth when the grade is stable, and decreasing the compression ratio to preserve key information when the grade changes abruptly, achieving an adaptive balance between transmission load and data fidelity.

There is provided a wind duct with a silencer that can efficiently reduce sound propagated to a blowing target including noise generated in a wind duct during blowing. The wind duct with a silencer of the present invention includes the wind duct that is connected to a blowing source and a silencer that reduces sound released from an exit of the wind duct. The silencer is disposed at a position closer to the exit among the blowing source and the exit, and a frequency of a primary silencing peak of the silencer is within a frequency band of sound generated in the wind duct due to blowing in the wind duct.

This invention discloses a hyperspectral inversion method for soil heavy metals based on a CNN-TabM model, belonging to the field of quantitative inversion of soil heavy metal content via hyperspectral remote sensing. The method includes: collecting soil samples and measuring hyperspectral data and heavy metal content; sequentially performing noise band removal, SG smoothing, and fractional derivative transform on the hyperspectral data, and using the CARS algorithm to select feature bands; inputting the selected bands into the CNN-TabM model, which uses a one-dimensional convolutional neural network to extract local spectral features, and after feature fusion, inputting the results into the TabM model for global feature interaction and ensemble prediction, outputting the heavy metal content inversion result. This invention achieves complementary advantages of local spectral detail perception and global feature modeling by coupling convolutional neural networks and tabular deep learning models, significantly improving the accuracy of soil heavy metal inversion and providing effective technical support for soil environmental monitoring.

The application discloses a power grid adaptive pre-regulation frequency method and device, equipment and storage medium, and belongs to the technical field of power system automation and control. The method comprises the following steps: wavelet transform is performed on historical fluctuation data of a net load and initial prediction data of a next period, noise bands are suppressed and main characteristic bands are corrected, and a net load prediction sequence of a plurality of future pre-regulation frequency execution points is obtained after reconstruction; equivalent power-frequency sensitivity is obtained, estimated frequency offset and resource sensitivity decomposition results are obtained in combination with the net load prediction sequence; the estimated frequency offset, the resource sensitivity decomposition results and scenario prior characteristics are taken as states, candidate pre-regulation frequency schemes are simulated and constraint checking is performed, a deep Q network is trained to obtain a pre-regulation frequency comprehensive ranking strategy; a target pre-regulation frequency scheme is selected and is mapped into a pre-regulation frequency power trajectory and a pre-regulation frequency parameter adjustment amount of the future pre-regulation frequency execution points. The embodiment of the application can improve the foresight and robustness of new energy power grid frequency control.