70 results about "Noise band" patented technology

A method and system for tracking and updating bias in an inertial sensor by determining a maximum bias drift and a noise band for a sensor, determining a prior bias value of the sensor, and measuring a current bias value of the sensor. The method and system can further include calculating a bias difference between the prior bias value and the current bias value, and updating the prior bias value with the current bias value if the current bias value is within the noise band and the bias difference is less than or equal to the maximum bias drift.

There is disclosed a noise suppression device capable of improving the noise suppression accuracy while reducing the audio distortion. In this device, a suppression unit suppresses a noise component from the audio power spectrum by using the detection result of the audio-existing band and the noise band in the audio power spectrum including the noise component. A pitch harmonic structure extracting unit (105) extracts a pitch harmonic power spectrum from the audio power spectrum. An audio-existence judgment unit (106) judges whether the audio power spectrum has audio existence according to the extracted pitch harmonic power spectrum. A pitch harmonic structure repair unit (108) repairs the extracted pitch harmonic power spectrum. A per-band audio/noise correction unit (109) corrects the detection result according to the pitch harmonic power spectrum selected according to the result of judgment by the audio-existence judgment unit (106) among the repaired pitch harmonic power spectrum and the extracted pitch harmonic power spectrum.

A noise reducing circuit includes a denoising unit configured to eliminate a noise band from an input voice signal; a noise recognizing unit configured to recognize noise included in the voice signal; a denoising period generating unit configured to generate a signal indicating a denoising period in accordance with an occurrence period of the recognized noise; and a selecting unit configured to select an output of the denoising unit when the denoising period is indicated and select the voice signal when the denoising period is not indicated.

The invention discloses a noise suppression device, a noise suppression method, and a program. The noise suppression device includes a framing unit, a band dividing unit, a band power computing unit, a noise determining unit that determines whether or not each band is noise, a noise band power estimating unit, a noise suppression gain determining unit, a noise suppression unit that applies the noise suppression gains and obtains a band divided signal of which noise has been suppressed, a band synthesizing unit, and a framing synthesizing unit that synthesizes the frames of the framing signals; the noise suppression gain determining unit having an SNR computing unit that computes an SNR for each band, and a SNR smoothing unit that smoothes the SNR computed for each band; wherein the noise suppression gains for each band are determined based on the SNR of each band smoothed by the SNR smoothing unit; and wherein the SNR smoothing unit changes the smoothing coefficient.

An embodiment of the invention discloses a noise reduction device, which is applied to a cabinet. The noise reduction device comprises at least one noise reduction unit having a cavity. The cavity iscommunicated with an air channel generated by a fan of the cabinet through a connection hole. Each noise reduction unit comprises at least one separator plate extending into the cavity. Structure sizeof the connection hole and position information of the separator plate in the cavity are determined by a noise band range generated by the fan. The embodiment also discloses the cabinet.

The invention discloses an online cranial nerve spike potential signal detection method, device and system based on an adaptive threshold, and the method comprises the steps: 1, determining an initial position, screening cranial nerve signals from the initial position according to an initialized signal minimum value and a signal difference value, obtaining a test sample, and determining a test period according to the length of the test sample; 2, taking the standard deviation of the first test sample in each test period as a noise band threshold value of each test period; 3, for each cranial neural signal in the test period, determining an adaptive threshold of the cranial neural signal according to the noise band threshold and a previous section of historical cranial neural signal until the current cranial neural signal; and 4, screening a reference brain neural signal point according to the brain neural signal and the corresponding adaptive threshold, and extracting a spike potential signal according to the reference brain neural signal point. Therefore, the detection accuracy is improved while the online detection calculation consumption is reduced.

The invention provides a classification-oriented hyperspectral remote sensing image noise band detection method. The method includes: adopting a visual interpretation method to obtain a sample of a certain type of pure ground object in a hyperspectral remote sensing image; acquiring spectral information of the samples, wherein all the samples and the corresponding spectral information form a training sample set with the spectral information, and the spectral information corresponds to different spectral bands; performing training through the training sample set to obtain a plurality of decision trees, and aggregating the plurality of decision trees to form a random forest; calculating the importance of a spectral band in the random forest; determining an importance threshold P of the spectral band; and calculating the importance of Q spectral bands in a certain hyperspectral remote sensing image which is actually input, and automatically detecting a severe noise band according to the importance threshold P of the spectral bands. The method has the beneficial effects that the serious noise wave band in the hyperspectral remote sensing image is detected, and support is provided for improving the classification precision.

The invention is applied to the field of printed circuit boards, and particularly relates to an ultra-wide band electromagnetic band-gap structure applied to power planes of printed circuit boards. The elementary cell of the ultra-wide band electromagnetic band-gap structure consists of spinning branches and slots of square metal patches. The spinning branches of the elementary cell of the electromagnetic band-gap structure surround the square metal patches. The slots are etched on the metal patches of the elementary cell of the electromagnetic band-gap structure. Four sides of the metal patches of the elementary cell of the electromagnetic band-gap structure are grooved. The electromagnetic band-gap structure has wider bandwidth and lower cut-off frequency, basically covers noise band of noises of a synchronous switch, and can eliminate noises of the synchronous switch between the power planes and the ground plane omnidirectionally. The ultra-wide band electromagnetic band-gap structure produced by the conventional printed circuit board manufacturing process is easy to realize and has high benefit.

The invention relates to an audio signal processing method and device and a storage medium. The method comprises the following steps of: acquiring a to-be-processed band noise frequency power spectrumand a to-be-processed noise power spectrum; determining a first noise component according to the power characteristics of the band noise frequency power spectrum at each frequency point, the first noise component being a steady-state noise component contained in both the band noise frequency power spectrum and the noise power spectrum; subtracting the first noise component from the band noise frequency power spectrum to obtain a band noise frequency component; subtracting the first noise component from the noise power spectrum to obtain a second noise component; determining a frequency domainestimation signal according to the band noise frequency component and the second noise component; and performing time-frequency conversion based on the frequency domain estimation signal to obtain anoise-reduced audio signal. Through the technical scheme of the embodiment of the invention, the common steady-state noise component is removed from the band noise frequency power spectrum and the noise power spectrum, and then the noise reduction processing is performed on the audio signal, so that the processing deviation caused by the steady-state noise can be reduced, and the noise reduction effect is improved.

The invention provides a range hood noise reduction control method and system and a range hood. The method comprises the steps of detecting a primary noise signal generated by the range hood; performing signal processing on the primary noise signal to obtain a noise reference electric signal; calculating a secondary sound source electric signal corresponding to the noise reference electric signalby adopting an FxLMS algorithm; performing signal processing on the secondary sound source electric signal to obtain a secondary noise signal; and outputting the obtained secondary noise signal to besuperposed with the primary noise signal to realize noise reduction control. According to the method, secondary channel identification is added into an adaptive control algorithm, so that the processing capacity of background noise of an active noise reduction system is effectively improved, the controllability is high, the uncertainty caused by broadband noise of the range hood can be effectivelycoped with, the response speed and the strain capacity of the system are improved, and the working efficiency is improved.

The invention discloses a mine micro-seismic signal P wave first arrival moment extraction method and system, and the method comprises the steps: obtaining a micro-seismic signal, and carrying out the dimension raising of the micro-seismic signal, and obtaining a time-frequency-energy distribution diagram of the micro-seismic signal; determining a main frequency band of the microseismic signal according to signal and noise energy distribution in the time-frequency-energy distribution diagram; determining a P-wave first arrival approximate moment on the main frequency band; and selecting a time window in the micro-seismic signal based on the P-wave first arrival approximate moment, and further determining a P-wave first arrival accurate moment. According to the method provided by the invention, the time domain and frequency domain information of the micro-seismic signal can be fully utilized, the real moment when the micro-seismic occurs can be found through energy analysis, the serious error generated by P-wave primary positioning is solved from the source, the more accurate P-wave first arrival is picked up, and the influence caused by abrupt change noise is eliminated.

The invention discloses an adjacent point correlativity mean noise reduction method implemented for FFT data. The method comprises the steps of setting a reference value dRef; comparing to-be-processed FFT signal data with the reference value dRef; for the data with the value lower than the reference value dRef, calculating a mean of a set number of pieces of adjacent data, and replacing the data value lower than the reference value dRef with the mean; and reducing the amplitude of distorted data with the value lower than the reference value and reducing the noise band to enable signals with values lower than the reference value to gather to the center of noise. The amplitude of the distorted data with the value lower than the reference value can be reduced through an adjacent data mean method and the noise band is reduced, so that the signals with the values lower than the reference value can gather to the center of the noise, and the noise can be inhibited and the interference signal energy can be reduced to a certain extent.

A noise-reducing structure of a hermetic compressor, which can effectively reduce the noise in this frequency band caused by the vibration of the compression chamber caused by the pressure shock effect in the cylinder during the compression stroke of the cylinder, and can prevent the reduction Noise reduction in chamber volumetric efficiency. The structure has a noise-reducing chamber with a predetermined volume formed in the above-mentioned cylinder body; and a communication channel for communicating the above-mentioned noise-reducing structure with the above-mentioned cylinder.

The invention relates to an image edge detection method for splicing aerial correction images, which belongs to the field of computer vision. Non-ideal information such as pitch angle and roll angle of the unmanned plane can cause nonlinear distortion of the aerial image, and after geometric correction, the edge of the corrected image has a large amount of irregular noise. When a plurality of aerial images are stitched to form a seamless large-scale scene image, if each aerial correction image is directly cropped, a large amount of effective information is cut off, and if not cropped, obvioussplice noise can be generated. The method performs edge detection twice for an aerial correction image with edge noise, distinguishes invalid pixels from effective pixels by a certain rule, and determines the edge noise band. When correcting image stitching, stitching noise can be avoided by only clipping this noise band and at the same time, the effective scene of the image is maintained to the greatest extent.

The invention relates to a random noise suppression method for parallel epicentre seismic data based on PCA-EMD. According to the method, firstly, the spectral range of a useful signal is estimated according to spectrum analysis, secondly, modal components dominated by the useful signal in modal components obtained through EMD decomposition are selected according to the useful signal spectrum range, thirdly, the modal components dominated by the useful signal and the remainder are reconstructed to obtain the reconstruction result, and lastly, a Hankel matrix is constructed for the reconstruction result based on the phase space theory, and PCA decomposition and recovery of the useful signal are further carried out. As verified, the data processing speed is fast, compared with an EMD suppression random noise method, the random noise can be suppressed in the whole frequency range, in the signal-noise band aliasing process, not only can noise energy be suppressed, but also signal details can be effectively protected; through the good signal-to-noise ratio improvement capability, the target data positioning error after processing is smaller, data processing cost is reduced, the qualityof the parallel epicentre seismic data can be effectively improved, and the method is better than other methods under strong voice conditions.

A disk tray for a disk drive that slides in and out of the disk drive, one or more resonators mounted on a lower surface of the disk tray to selectively reduce noise of a predetermined frequency band. According to the present invention, the dominant resonance noise frequency band, which occurs at the peak sound pressure level, is reduced or removed from the noise generated in the disk drive. Also, by filling a resonance container of the resonator with a porous member, the high frequency noise band and the overall noise level can be reduced.

The invention discloses an ultra-fast ultra-bandwidth low-noise band agile frequency source which is composed of a shell and a synthetic frequency module. A Control/Power interface, an REFOUT interface, an REFIN interface and an RFOUT interface are arranged outside the synthesis frequency module, wherein the Control/Power interface is numbered XS1 and is used for a power supply and a control interface; the REFOUT interface is numbered XS2 and is used for referring to a signal output interface; the REFIN interface is numbered XS3 and is used for synchronizing a signal input interface; and the RFOUT interface is numbered XS4 and is used for a radio frequency signal output interface. The ultra-fast ultra-bandwidth low-noise band agile frequency source has the advantages of wide working frequency band, high frequency hopping speed and low phase noise.