14results about How to "Improved noise suppression" patented technology

The invention discloses a combined preprocessing and fusion decoding method based on electroencephalogram signals and functional near-infrared signals, which comprises the following steps of: synchronously acquiring the electroencephalogram signals and the functional near-infrared signals, taking a task trigger event as a unified time reference, and carrying out basic preprocessing of time alignment and modal self-adaption on two modal signals to obtain a functional near-infrared signal; a pre-trained cross-modal noise joint modeling module is utilized to perform joint modeling on cross-modal joint noise features caused by a common noise source, collaborative denoising processing is performed on multi-modal signals based on the cross-modal joint noise features, multi-modal denoising representation is obtained, a cross-modal feature interactive modeling mode based on an attention mechanism is obtained, and the multi-modal noise is obtained. And dynamically modeling the correlation between different modal features, realizing deep fusion of multi-modal complementary information, carrying out decoding processing based on the fused features, and outputting a corresponding brain-computer interface control instruction or task identification result. According to the method, the decoding accuracy and robustness of the brain-computer interface system in a complex task scene are enhanced.

The application discloses a kind of active shock absorption and steady control system and method based on voice coil motor, it is related to mechanical vibration control technical field.The method is by obtaining the phase signal synchronous with excitation source, directly from waveform look-up table index and output opposite phase drive instruction, drive voice coil motor to generate counterforce.Meanwhile, the system uses the residual acceleration of non-causal filtering processing in background, and adaptively updates waveform look-up table.The application adopts feedforward control, avoids the phase delay caused by filtering in traditional feedback control, can accurately suppress high-frequency periodic vibration with very low delay, significantly improves operation comfort.

The utility model relates to a stable power supply device for an airborne multispectral photoelectric system. The stable power supply device comprises an input filtering anti-reverse circuit, a peak surge suppression circuit, a DC-DC conversion circuit, a voltage acquisition reporting circuit and an output filtering circuit which are connected in sequence, the peak surge suppression circuit comprises a normal switching stage peak loop, an input power supply switching power-on loop and an ultrahigh peak power supply loop. The DC-DC conversion circuit comprises a first path of non-isolated output P1 and a second path of isolated output P2. According to the stable power supply device, on one hand, the dynamic response of the power supply is improved, the stability of the power supply is greatly improved, and meanwhile, the output precision and the anti-interference capability are improved.

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 application discloses a linear voltage stabilizing circuit based on NMOS regulating tube, comprising a bias voltage generating circuit, a voltage division feedback circuit, an oscillator circuit, a charge pump circuit and a pre-voltage stabilizing circuit, wherein the bias voltage is generated through the bias voltage generating circuit; the output voltage is divided to obtain a feedback voltage through the voltage division feedback circuit; the feedback voltage is amplified and then input to the oscillator circuit to generate an oscillation signal; the generated oscillation signal is input to the charge pump circuit; the gate voltage of the NMOS regulating tube is adjusted through the charge pump circuit, so as to obtain the output voltage; the pre-voltage stabilizing circuit widens the input voltage range, so that the linear voltage stabilizing circuit can work in a high input voltage environment; the linear voltage stabilizing circuit based on the NMOS regulating tube has the characteristics of wide input range and low voltage difference, fast transient response speed, and is fully compatible with the thin gate oxide process.

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 invention belongs to the technical field of vibration noise control, and particularly relates to a two-dimensional acoustic focusing structure based on a sound wave black hole effect, which comprises an upper structural plate, a lower structural plate and a sound wave black hole structure, an air domain is formed between the upper structural plate and the lower structural plate, and the bottom end of the sound wave black hole structure is arranged on the plates and used for gathering and dissipating sound waves. An existing one-dimensional sound wave black hole technology is expanded to a two-dimensional structure, incident waves are gradually gathered to the central area of the black hole, and therefore the sound wave focusing capacity of the two-dimensional structure is improved.

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 an airborne wind measurement laser radar dynamic adaptive attitude-position collaborative compensation system and method which can dynamically adapt to flight states and accurately couple attitude and position interference. The system comprises a GNSS positioning module (1), a MEMS-IMU attitude sensing module (2), a two-stage coordinate conversion module (3), a dynamic speed solving module (4), an adaptive collaborative compensation module (5) and a laser radar wind measurement module (6). The method comprises the following steps: S1, multi-source data synchronous acquisition, S2, ECEF coordinate system conversion, S3, ENU coordinate system conversion, S4, dynamic speed solving, S5, dynamic weight adaptive compensation, S6, data output and feedback storage. The application is applied to the technical field of wind measurement laser radar.

A cultivated land edge refinement detection method based on semantic guidance of RoI attention comprises the following steps: preparing high-resolution remote sensing image data containing intensive agricultural plots, and carrying out standardization and noise suppression preprocessing on the high-resolution remote sensing image data; the method comprises the following steps: constructing a shared encoder-double parallel decoder multi-task model, extracting multi-scale features through a shared encoder, outputting a cultivated land area semantic probability graph by using a semantic segmentation decoder, and outputting an initial edge strength graph by using an edge detection decoder; based on the semantic probability graph, generating a dynamic multi-scale RoI mask adaptive to the irregular form of the cultivated land through binarization, morphological optimization and adaptive resolution adjustment; semantic intermediate features and edge intermediate features are extracted, channel cascade fusion is carried out, differential modulation is carried out on the fusion features through an RoI attention mechanism, cultivated land area edges are focused, non-cultivated land noise is inhibited, and a refined edge intensity graph is output through detail optimization; and performing non-maximum suppression, fracture edge completion and vectorization processing on the refined edge graph to generate cultivated land edge vector data meeting geographic information business requirements. According to the method, deep collaboration of semantic information and edge features is realized, the omission ratio and the false detection ratio are greatly reduced, the method is adaptive to diversified cultivated land scenes such as fragmentation and connection, and refined detection of cultivated land edges is realized.

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.

Provided are a rotor, a motor, and a wiper motor with which it is possible to inhibit an increase in operating noise and deterioration in rotor characteristics, and to reduce material cost for permanent magnets. An arc center C2 of an outer circumferential surface 32b of a rotor core 32 and an arc center C3 of an inner circumferential surface 33b of a permanent magnet 33 are off-centered radially outward from a rotational axis C1, with the circumferential center disposed on the radially outermost side. An angle θ1 formed by salient pole side surfaces 35a facing each other of circumferentially adjacent two salient poles 35 is equal to an angle θ2 formed by magnet side surfaces 33a on both sides circumferentially of the permanent magnet 33. When the distance between the outer circumferential surface 32b of the rotor core 32 and the radially outermost end of the salient poles 35 is Lt, and the distance between the inner circumferential surface 33b of the permanent magnet 33 and the radially outermost end of the magnet side surfaces 33a is Lme, the distances Lt, Lme are set such that the relationship Lme < Lt is satisfied.