6results about How to "Improved noise suppression" patented technology

The application discloses a power supply noise suppression circuit of a voltage-controlled oscillator, which comprises a power supply input end, a mean value unit, a noise sampling unit, an integral unit and a proportional addition unit, wherein the power supply input end provides an input voltage; the mean value unit is connected with the power supply input end, and the mean value unit obtains a power supply voltage average value according to the input voltage; the noise sampling unit is connected with the power supply input end and the mean value unit respectively, so as to obtain a power supply voltage instantaneous value according to the input voltage, and obtain a noise signal according to the difference between the power supply voltage average value and the power supply voltage instantaneous value; the integral unit is connected with the noise sampling unit, and the integral unit processes the noise signal to obtain a compensation signal; the proportional addition unit is connected with the integral unit, so as to obtain a voltage control signal of the voltage-controlled oscillator after the compensation signal is compensated; thus, the noise suppression effect is good, and the on-chip integration is easy.

The application provides a motor efficiency reduction heating control method and device and a vehicle. The optimal balance between efficiency and noise is achieved by shortening the noise deterioration interval and combining real-time feedback adjustment. The method comprises the following steps: in response to the motor efficiency reduction heating function being turned on, determining the motor efficiency reduction heating target speed under the current driving working condition; before the target speed of the motor changes to the efficiency reduction heating target speed, reading a set of noise reduction parameters matched with the current driving working condition from the pre-stored control parameter set and preloading; making the current target speed of the motor change to the efficiency reduction heating target speed according to a preset rule; during the current target speed changing process and the running stage after reaching the efficiency reduction heating target speed, collecting the running state feedback signal of the motor in real time and constructing an evaluation function; taking the noise reduction parameters as optimization variables, and taking the minimum value of the evaluation function as the optimization target, the specific value of the noise reduction parameters is adjusted in real time within the preset parameter constraint range of the noise reduction parameters.

The present application relates to the technical fields of electromagnetic noise suppression, and relates to a brushless motor electromagnetic noise suppression method and system based on harmonic current injection, comprising: confirming a noise brushless motor and a motor monitoring device, obtaining motor data of the noise brushless motor, using the motor monitoring device to analyze the noise of the noise brushless motor, obtaining a motor noise signal, performing frequency spectrum feature analysis on the motor noise signal, obtaining noise order, electromagnetic noise amplitude and electromagnetic characteristic frequency, performing phase-sensitive detection on the motor noise signal based on the noise order, the electromagnetic characteristic frequency and the electric angle time signal, obtaining the motor relative phase, performing adaptive fine tuning on the preliminary harmonic current data set based on the motor monitoring device and the vector voltage time signal set, obtaining a target harmonic signal set, performing harmonic injection on the noise brushless motor based on the target harmonic signal set, obtaining a noise suppression motor, and completing electromagnetic noise suppression of the brushless motor. The present application can reduce the electromagnetic noise level of the brushless motor.

The application provides a semiconductor test image denoising method and system based on Taylor expansion, and relates to the technical field of image processing.The method flow is as follows: an array test image of a semiconductor is acquired, and frequency domain analysis is performed on the array test image to obtain periodic characteristics and directionality characteristics of the array; a structure-aware Taylor expansion model is constructed based on the periodic characteristics and the directionality characteristics of the array; a structure-aligned sampling network is established based on the periodic characteristics and the directionality characteristics of the array, and pixel reconstruction is performed based on the structure-aware Taylor expansion model to obtain pixel reconstruction values; multi-scale image fusion is performed based on all the pixel reconstruction values to obtain a final denoised image.The application realizes effective suppression of complex noise while perfectly maintaining the periodicity and directionality structure characteristics of the semiconductor array through the structure-aware Taylor model and intelligent multi-scale fusion.

The application provides a tablet touch signal recognition and processing method. Through a dynamic noise suppression formula, a time attenuation factor and an adaptive adjustment coefficient are used to realize dynamic adjustment of noise suppression strength according to signal time characteristics and strength. Compared with the existing static filtering algorithm, the noise suppression effect is improved by more than 30%, and the signal distortion rate is reduced to less than 5%. According to a feature adaptive fusion weight formula, feature weights are dynamically allocated according to real-time interference strength. In the interference scene of water stains, dust and the like, the recognition accuracy still remains more than 95%, which is improved by 15-20% compared with the fixed weight fusion algorithm. A dynamic decision threshold formula combines real-time confidence and historical correct recognition rate to avoid the scene adaptation defects of the fixed threshold. A fuzzy classification judgment formula solves the fuzzy judgment problem of the touch signal. The average delay of the whole signal processing process is controlled within 8 ms, which is reduced by more than 40% compared with the prior art (15-20 ms), and the fluency of touch response is improved.

The present application belongs to the technical field of medical image processing, and proposes a brain function image noise suppression method based on space-time features. The present application provides a brain function image noise suppression method and system based on space-time features. Compared with the traditional noise suppression method, the present application aims to independently implement targeted noise elimination and signal enhancement in the time domain and the spatial domain. Compared with the existing method which only focuses on global changes and overall trends, the present application adds a sliding window to process the segmented time-varying features, and uses methods such as independent covariate regression to effectively identify and remove the noise of the time and space features, thereby achieving better noise suppression effect.