412 results about "Nonlinear distortion" patented technology

The invention provides a multi-band radio frequency power amplifier dynamic range adaptive test method and a system thereof. The method comprises the following steps: acquiring an output signal frequency spectrum of a tested radio frequency power amplifier, extracting characteristic frequency points including a center frequency and a bandwidth, matching the characteristic frequency points with a preset frequency band database, and automatically loading a test scheme of a corresponding frequency band. According to the method, the frequency bands are automatically matched through spectrum sensing, the test scheme is loaded, the multi-frequency-band characteristics can be rapidly adapted without manual parameter configuration, index missing test is avoided, and the switching efficiency is improved; dynamically optimizing test parameters by using a genetic algorithm, and accurately capturing a nonlinear distortion critical point while balancing coverage and efficiency; by combining multi-dimensional signal analysis and a deep learning model, the problem of missing detection of traditional single-domain analysis is solved, and the abnormal signal recognition capability is remarkably enhanced; through linear model correction, impedance dynamic matching and index threshold iteration, full automation and high precision of the test are realized, the environmental interference influence is effectively reduced, and a self-adaptive test system is constructed.

The invention relates to a retiming circuit applied to an ultra-high-speed and high-precision DAC (Digital-to-Analog Converter), which comprises an alignment module, a cross point adjusting module, a coding module, a phase detection module and a digital module, the coding module is connected with the alignment module, the phase detection module is connected with the cross point adjusting module and the coding module, and the digital module is connected with the phase detection module and the alignment module. According to the circuit structure provided by the invention, the sampling clock can be accurately aligned to the center of a data eye pattern, so that the delay difference between a clock tree and a data path caused by process deviation and the like is effectively reduced, the high-frequency spurious suppression performance is improved by eliminating nonlinear distortion caused by time sequence errors, the SFDR is greatly improved, and compared with a traditional scheme, the SNR is effectively improved.

The invention discloses an electroencephalogram signal artifact removal method and an acquisition system. The method comprises the following steps: synchronously acquiring sensor data of a testee and each lead electroencephalogram signal by utilizing a unified trigger signal; performing timestamp alignment verification on the two types of synchronous data; a motion state quantitative index is determined, and if the motion state quantitative index does not exceed a preset motion threshold value, the collected electroencephalogram signals are output; if yes, an exception processing flow is triggered and comprises the steps that self-adaptive filtering and nonlinear compensation are sequentially executed on the electroencephalogram signals, static electroencephalogram data of the testee serve as reference in the self-adaptive filtering process, an NLMS filter with the step length dynamically adjusted is adopted, a motion artifact linear part and base noise are restrained, a self-adaptive filter is constructed based on the second-order Volterra series in the nonlinear compensation process, and the motion artifact linear part and the base noise are restrained; a kernel coefficient is optimized through an RLS algorithm, and nonlinear distortion is processed; and outputting the electroencephalogram signal after the exception processing. The method is suitable for non-linear and non-stationary motion artifact signals, signal synchronism and quality can be improved, and processing efficiency is considered.

The invention provides an image correction method and system based on a nonlinear distortion distribution elliptical fisheye lens, and a medium. The method comprises the following steps: establishing a nonlinear mixed distortion imaging model based on a mapping relation between image coordinates and a spherical direction; defining a distortion vector, and performing fitting processing on the distortion vector based on a two-dimensional B-spline function to obtain a distortion function; the method comprises the following steps: acquiring images in a five-surface three-dimensional angle calibration space based on an elliptical fisheye lens, analyzing lens imaging parameters, and generating parameter values of a distortion function; analyzing parameter values of the distortion function based on a nonlinear mixed distortion imaging model to generate calibration parameters, and remapping pixel points in the distorted image based on the calibration parameters; performing image reconstruction on the remapped distorted image to obtain a corrected image; improving the sampling density of a target area by constructing a nonlinear mixed distortion imaging model; the system adapts to complex monitoring environments such as galleries and entrances and exits; and spatial distortion is flexibly expressed through a B spline, so that the modeling capability is improved.

The invention relates to the field of lithium battery intelligent monitoring, in particular to a low-temperature-resistant lithium battery BMS monitoring method and system based on cooperative sensing. The method comprises the following steps: acquiring surface temperature distribution, environment temperature and electrochemical parameters of the low-temperature tolerant lithium battery, and constructing a multi-source state characteristic matrix through space-time alignment and data fusion; applying a composite current excitation signal, and combining impedance analysis and spectrum analysis to extract impedance parameters, nonlinear distortion components and electrochemical stress factors to form a multi-dimensional feature vector; obtaining a state monitoring result by utilizing decision level fusion; through multi-sensor fusion and multi-dimensional feature fusion, the special internal state of the low-temperature tolerant lithium battery is comprehensively represented, early risk identification and early warning are carried out aiming at unique electrochemical behavior features of the low-temperature tolerant lithium battery, and compared with a common lithium battery monitoring method, the method has the advantages that the safety is high; and the accuracy, the robustness and the real-time performance of monitoring the state of the low-temperature tolerant lithium battery in the low-temperature environment are remarkably improved.

The invention relates to the technical field of digital image processing, in particular to an unmanned aerial vehicle image distortion correction and coordinate positioning compensation method, which comprises the following steps: collecting a large amount of unmanned aerial vehicle image data containing a damaged house, labeling the damaged house in the image, and generating a labeling file required by a YOLOv5 model; performing parameter calibration on the unmanned aerial vehicle lens to obtain a distortion coefficient of the lens, and constructing a nonlinear distortion correction model based on a lens parameter calibration result; establishing a dynamic affine transformation matrix in combination with the real-time flight attitude data of the unmanned aerial vehicle and the pixel coordinates of the detection frame; in a YOLOv5 detection stage, fusing feature maps with different resolutions, and fusing corrected coordinate data with a damaged house detection frame output by a YOLOv5 model; calculating coordinates of a center point of the damaged house according to the real-time latitude and longitude of the unmanned aerial vehicle; through dual optimization of image distortion correction and dynamic positioning compensation, the problem of coordinate misalignment caused by hardware limitation and unstable flight attitude in traditional unmanned aerial vehicle detection is solved.

The invention discloses a wide temperature range compensation method for resistive current of a lightning arrester, which belongs to the technical field of online monitoring of power equipment, and comprises the following steps: acquiring waveform data under a reference low-temperature working condition, and establishing an initial capacitive harmonic base; acquiring working condition data at any temperature in real time, performing harmonic decomposition, and analyzing to generate a nonlinear distortion feature vector; dynamically correcting the initial base by using the feature vector, and carrying out subtraction operation on the total current harmonic wave to obtain a final resistive current harmonic wave vector; and reconstructing an instantaneous resistive current waveform through inverse transformation and calculating a characteristic value. According to the technical scheme, the initial capacitive harmonic wave base is established, the nonlinear distortion feature vector is generated based on the harmonic distortion of the real-time working condition quantification temperature and valve plate nonlinear coupling, and dynamic feedback correction is conducted on the base, so that the real resistive current waveform in the wide temperature range can be accurately separated and reconstructed, and the accuracy of the real resistive current waveform in the wide temperature range is improved. And the accuracy and reliability of lightning arrester state evaluation are improved.

The invention discloses a high-frequency spark machine calibration method based on machining precision and stability control, and relates to the field of mechanical calibration, and the method comprises the steps: analyzing collected operation data, and building a data analysis model; the resonant frequency is dynamically adjusted based on the output frequency, and electromagnetic interference is eliminated through optical fiber transmission signals; an environment compensation mathematical model is constructed, and voltage deviation caused by environment change is automatically corrected; fundamental frequency and harmonic components are detected at the same time, and frequency deviation caused by nonlinear distortion is identified and compensated; a self-adaptive sensitivity adjusting mechanism is designed, a detection threshold value is dynamically adjusted based on the defect type and size, and sensitivity parameters of the high-frequency spark machine are automatically adjusted; the stability of the mechanical structure is predicted by simulating the assembly process; damping parameters of a mechanical structure are automatically adjusted, and the stability of high-frequency spark machine equipment is improved. The product quality and the production efficiency are guaranteed by improving the performance and the stability of the high-frequency spark machine.

The invention relates to the technical field of wireless communication, in particular to an OTA upgrading method and system for Bluetooth sound equipment. The method comprises the following steps: acquiring to-be-upgraded firmware data and currently played audio data, and acquiring power amplifier current feedback data of a sound speaker by sending a double-frequency detection signal containing 21kHz and 22kHz; acquiring equipment transmission capability confirmation data according to a silent response mode of the sound equipment to the preset handshake signal; and calculating a nonlinear distortion coefficient of the loudspeaker according to the intensity of the 1kHz difference frequency component in the power amplifier current feedback data, and obtaining real-time channel evaluation data based on current waveform deviation analysis. According to the method, the nonlinear distortion degree of the loudspeaker is accurately evaluated through the 1kHz difference frequency component generated by the 21kHz and 22kHz dual-frequency detection signals, so that the reliability of data transmission is more accurately predicted.

The invention is suitable for the technical field of semiconductor testing, and provides a data acquisition method and device based on a DDIC chip, and testing equipment, and the data acquisition method comprises the steps: receiving a test pattern, controlling the DDIC chip to output a corresponding gray scale voltage signal, and achieving the comprehensive testing of the response capability of the chip in a full gray scale range; secondly, a target acquisition link composed of functional units including impedance conversion, single-ended to differential conversion, programmable gain amplification, filtering, analog-to-digital conversion and the like is utilized, so that the signal driving capability and the anti-interference capability are effectively improved, meanwhile, high-frequency noise and nonlinear distortion are reduced, and the basic quality of sampled data is guaranteed; on the basis, sampling optimization processing is carried out on the sampling data based on the FPGA unit, and the data stability is improved. According to the scheme, through high-precision transmission of the signal link, the data acquisition precision of the DDIC chip is improved, and then the technical requirements of high-precision DDIC chip testing are met.

The invention relates to the technical field of surface mounting, and discloses an SMT (Surface Mount Technology)-based patch vision correction method, which comprises the following steps: S1, a calibration stage: constructing a double-coordinate system mapping model based on a PCB (Printed Circuit Board) plane, and establishing a nonlinear distortion compensation matrix according to the patch thickness; s2, a pickup stage: a CCD shooting camera is arranged at the top of the suction nozzle, a top CCD is triggered to shoot when the suction nozzle picks up an element, and pin coplanarity data is extracted; s3, a positioning stage: setting a reference point at the top of the PCB, scanning the PCB reference point through a CCD, and calculating a deviation between an actual position and a theoretical coordinate by using an algorithm processor; and S4, compensation execution: the motion shaft system dynamically adjusts the mounting path according to the deviation vector. The visual correction method based on SMT pasting has the advantages of accurate pasting and the like, and solves the problems of pasting position offset, low efficiency and unstable precision caused by factors such as vibration of an element feeder, mechanical transmission errors and thermal deformation of a PCB (Printed Circuit Board) due to dependence on manual calibration in the existing SMT pasting process.

The invention relates to the technical field of signal correction, in particular to a nonlinear distortion correction method for a vibration monitoring signal, and provides the following scheme: carrying out broadening and sparse reconstruction on a vibration signal through dispersion Fourier transform and compressed sensing, and extracting a high-frequency local structure; on the basis of phase-space reconstruction and a Lyapunov exponent, nonlinear distortion segments are identified; further performing orbit guiding modeling and degradation path reasoning on the orbit cluster corresponding to the segment, and selecting a reference orbit matched with the structure from the residual linear segments; and constructing an affine mapping relation between orbits and back-projecting the affine mapping relation to a time domain to generate a correction signal. According to the invention, high-precision identification and low-error correction of millisecond-level local nonlinear distortion are realized, and the stability and accuracy of vibration signal analysis are improved.

The invention relates to the technical field of aluminum alloy forming processes, and discloses an intelligent optimization method of an aluminum alloy round aluminum rod forming process. The method comprises the following steps: acquiring process parameter monitoring data of smelting, casting and rolling stages, wherein the process parameter monitoring data comprises temperature gradient, pressure fluctuation value and alloy component real-time variation; based on the time sequence relevance of the technological parameter monitoring data of the smelting stage and the casting stage, the technological parameter transmission delay amount between the two stages is calculated, and the parameter fluctuation compensation factor of the casting stage is determined accordingly. And determining the energy interference intensity of each process stage in the corresponding frequency domain according to the temperature gradient difference value, the pressure fluctuation change rate and the alloy component offset of the adjacent process stages in the short-time window. And generating a process nonlinear distortion probability based on the energy interference intensity distribution of all adjacent process stages. And the pressure control reference value in the rolling stage is dynamically adjusted according to the process nonlinear distortion probability. By means of the method, intelligent optimization of the aluminum alloy round aluminum rod forming process is achieved.

The invention relates to the technical field of radio frequency signal processing, and discloses a digital filtering repair method and system for signal distortion, and the method comprises the steps: obtaining a frequency domain amplitude-frequency response and a phase response; constructing a phase compensation amount by adopting piecewise polynomial fitting and a phase inversion mechanism; a complex number logarithm domain mapping mechanism is adopted to execute composite frequency response inversion; constructing a switchable hybrid digital filter with an amplitude path and a phase path coupled in parallel; multi-band adaptive scheduling is executed; and outputting the radio frequency baseband signal stream. The technical problems that in the prior art, frequency response nonlinear distortion in a broadband range cannot be dealt with by adopting a fixed template or a single-path filter, and particularly, a high-precision and low-delay dynamic compensation effect cannot be realized in a scene that multi-band coupling interference exists in a radio frequency ADC channel with the bandwidth exceeding 800MHz are solved. Due to the fact that the switchable hybrid digital filter is constructed, accurate modeling and flexible recovery of distortion characteristics in broadband signals are achieved.

The invention provides a phase generated carrier demodulation method based on two-parameter estimation. The method comprises the following steps of: firstly, realizing estimation of a C value by extracting an amplitude ratio of a carrier frequency multiplication component in an interference signal frequency spectrum and combining a Bessel function characteristic; then, carrying out operation processing by utilizing a first frequency multiplication signal and a second frequency multiplication signal to extract carrier phase delay theta c; and finally, eliminating the influence through dynamic phase compensation. According to the demodulation method provided by the invention, the nonlinear drift of the modulation depth parameter C and the synchronous estimation and compensation of the carrier phase disturbance signal theta c can be realized, the cross interference error in the traditional demodulation system is effectively inhibited, the phase demodulation robustness is remarkably improved, and the harmonic nonlinear distortion is effectively inhibited.

The invention provides a method for automatically determining the content of main elements in lithium battery black powder, and belongs to the technical field of lithium batteries. Characteristic spectral line intensity is collected by adopting an inductively coupled plasma emission spectrometer, background signals are deducted through wavelet multi-resolution decomposition, and the content of the main elements in the lithium battery black powder is obtained. Spectral overlapping peaks are separated through Fourier transform, an internal standard element is used for correcting a matrix effect, signal fluctuation introduced by pulse of a peristaltic pump is eliminated by adopting Kalman filtering, and relative intensity subjected to filtering smoothing is input into a multi-scale concentration calibration model with a layered soft maximum value classification layer; according to the model, interval affiliation probability distribution is output through a coarse-grained classifier, a fine-grained classifier is selected to carry out local concentration prediction and weighted fusion is carried out to obtain a concentration prediction value, and quality control standard sample monitoring and an instrument recalibration mechanism are combined; the technical problem that the measurement precision is reduced due to nonlinear distortion of a calibration curve when the multi-element concentration in the lithium battery black powder crosses a wide concentration range is solved.

The invention provides an in-vehicle acoustic enhancement method and device fusing determinacy-randomness hybrid modeling, and the method comprises the steps: collecting a fitted vehicle acceleration sound sample, extracting audio data, carrying out the analysis, constructing a determinacy component synthesis algorithm, and associating with a vehicle working condition; the method comprises the following steps: constructing a multi-physics-field coupled random noise generation module, wherein the multi-physics-field coupled random noise generation module comprises an aerodynamic noise module for simulating air inlet turbulence, a low-frequency pulse module for representing mechanical shock, a detonation module for simulating combustion uncertainty and a nonlinear distortion module for enhancing exhaust roughness and generating high-order harmonics; each random noise generation module is matched with the deterministic component, and mixing of the deterministic component and the random component is realized through weight adjustment; details are enhanced through dynamic compression, and target sound waves are generated; through collaborative optimization of determinacy-randomness components, the naturalness and brand identification degree of synthetic sound waves are improved, the vehicle working condition and driving information can be converted into perceptible sound effect characteristics, and the problem of information perception simplification in the electric vehicle driving process is solved.

The invention provides an OTFS (Orthogonal Time Frequency Space) channel estimation method based on a bidirectional gating loop unit (BiGRU) and a multi-head attention mechanism, and belongs to the technical field of channel estimation. The method comprises the following steps: determining time delay-Doppler domain parameters according to a channel scene, and constructing a TDL (Tap Delay Line) channel model; designing a time-frequency domain pilot frequency structure; carrying out time-frequency domain modulation on a sending signal and adding high-power amplifier (HPA) nonlinear distortion; obtaining an initial channel state by using LS estimation; a BiGRU network and multi-head attention mechanism joint model is constructed, and channel state prediction is realized through bidirectional time sequence feature extraction and multi-dimensional attention weight distribution; and time delay-Doppler domain channel response reconstruction is completed by using the optimized model. Bidirectional dependency of channel time-varying features is captured through BiGRU, and a multi-head attention mechanism is combined to enhance the key path feature extraction capability, so that the channel estimation precision in a high-mobility scene is remarkably improved, and the influence of HPA nonlinear distortion on the system performance is effectively inhibited.

The invention discloses a visual compensation alignment method and system for a special-shaped screen, and belongs to the technical field of image processing, and the method comprises the steps: obtaining physical geometric parameters of the special-shaped screen, carrying out the mathematical simulation, and generating a physical perception deviation map; receiving a content image, performing multi-scale semantic analysis, and generating a content perception joint constraint tensor; constructing and iteratively solving an energy function, and generating an optimal visual compensation flow field; performing nonlinear distortion and reconstruction, and outputting a pre-compensated content image; and performing sub-pixel-level processing through the flexible edge mixed mask, and outputting a final display picture. According to the method, a joint optimization strategy fusing a screen physical perception model and content semantic analysis is adopted, the key visual content can be intelligently protected while the physical fidelity is maximized, and seamless and high-fidelity fusion of a display picture and a special-shaped screen physical form is achieved.

The invention relates to the field of supply chain optimization, in particular to a supply chain logistics efficiency collaborative optimization method and system based on artificial intelligence. The method comprises the following steps: obtaining a real-time supply chain logistics data stream, carrying out node coupling density analysis and self-adaptive layered mapping, and constructing a multi-layer logistics cooperation network; performing path node load response backstepping on the multi-layer logistics cooperative network, and performing nonlinear distortion evaluation to obtain a nonlinear distortion degree of a response curve; and carrying out sensitivity quantitative evaluation according to the nonlinear distortion degree of the response curve, carrying out topological association reconstruction among nodes, and constructing a supply chain logistics topological optimization network. And performing future load demand rehearsal according to the real-time supply chain logistics data flow, performing call operation path evolution analysis, and generating call operation path evolution data. According to the invention, the configuration of supply chain logistics resources is optimized, and the overall operation efficiency and response capability of supply chain logistics are improved.

The invention discloses a radio frequency fingerprint hiding method based on feature compensation. The method comprises the following steps: at a transmitter end, carrying out carrier frequency offset compensation, I / Q imbalance compensation and PA nonlinear distortion compensation on a to-be-transmitted signal in sequence by using a preset joint compensation model to obtain a transmitted signal after radio frequency fingerprint hiding; the joint compensation model is constructed by the following steps: carrying out carrier frequency offset estimation and compensation, I / Q imbalance estimation and compensation and PA nonlinear distortion estimation on a received signal of a receiver in sequence, and constructing the joint compensation model according to a carrier frequency offset estimation result, an I / Q imbalance estimation result and a PA nonlinear distortion estimation result. According to the method, a scientific and reasonable parameter estimation and compensation sequence is designed, an illegal receiver is effectively prevented from extracting radio frequency fingerprints from received signals, the classification precision of the RFFI technology can be effectively reduced, and the privacy protection and recognition resistance of a transmitter are remarkably enhanced.

The present disclosure provides a laser scanning device and a projection imaging device, which realizes real-time compensation of the outgoing direction of the scanning beam by adding a hardware level distortion correction component and its control module after the reflection of the galvanometer. In the nonlinear distortion area such as the pillow-shaped distortion and the tilt distortion generated by the galvanometer scanning, the distortion correction component can accurately adjust the beam deflection angle according to the pre-calibrated correction parameter sequence, effectively restore the geometric shape of the scanning pattern, significantly improve the linearity of the point cloud distribution and the overall imaging accuracy, and complete the distortion correction of the full field of view without sacrificing the field of view angle or the resolution, thereby ensuring a wider effective imaging area and more delicate image details. By integrating a special distortion correction component in the optical path, the dependence on the upper image processing algorithm is reduced, the demand for high-performance controllers and complex software operations of the entire system is reduced, and better cost effectiveness and engineering implementation are achieved.

The invention provides an intelligent audio power amplifier system and a working method thereof. The working method comprises the steps that a dynamic noise suppression module enables an input signal after reverse noise injection to enter a distortion compensation module; a distortion compensation signal is synthesized by using a distortion compensation module; the life cycle parameter self-calibration module calibrates parameters and inputs the parameters to the dynamic noise suppression module and the distortion compensation module; the dynamic noise suppression module is based on an intelligent learning method and adopts a frequency band channel network, a time sequence channel network and a fusion layer; the life cycle parameter self-calibration module provides the temperature and the working time for the dynamic noise suppression module to optimize the time domain channel network and provides the temperature and the working time for the distortion compensation module to update the predistortion coefficient of the dynamic nonlinear distortion model; the output of the dynamic noise suppression module is provided for the distortion compensation module; and the output of the distortion compensation module is fed back to the dynamic noise suppression module. The problems of high-frequency noise interference, nonlinear distortion degradation and insufficient long-term stability are solved at the same time.

The invention is suitable for the technical field of power electronics, and provides an intelligent management method and system for a power amplifier, and the method comprises the steps: obtaining the output voltage and current of the power amplifier, and determining the real-time load impedance; predicting the junction temperature of the power amplifier according to a coupling thermal model associating the effective thermal resistance with the load mismatch degree; based on the predicted junction temperature and real-time load impedance, stability compensation parameters for maintaining operational stability and pre-distortion parameters for compensating for non-linear distortion are cooperatively determined and adjusted. Through cooperative intelligent management, safety and reliability can be improved, performance maximization is realized, and high fidelity of all working conditions is ensured.

The invention discloses an image nonlinear distortion correction method and device and a storage medium, which are used for eliminating nonlinear distortion and improving the detection efficiency and quality. The method comprises the steps that a checkerboard image is input into a target image, the target image is segmented into a plurality of sub-regions according to the checkerboard image, and the target image is an image generating nonlinear distortion; extracting sub-region corner coordinates of the sub-regions; sorting the angular point coordinates of the sub-regions; according to the sub-region corner coordinates, the black-and-white lattice corner coordinates of the checkerboard image and the sorting result, a homography transformation matrix is obtained through calculation, and the black-and-white lattice corner coordinates are standard corner coordinates of a plurality of black-and-white lattices in the checkerboard image; and converting the target image into a corrected image through the homography transformation matrix.

The invention relates to the technical field of optical fiber wireless communication and mobile forward transmission, in particular to a digital analog optical fiber wireless forward transmission transmitting end parameter self-adaptive optimization method and system based on reinforcement learning. Decomposing the normalized wireless signal into digital parts of all levels and a final analog residual error part through multi-level modulation, and transmitting the digital parts and the final analog residual error part in a time division multiplexing manner; a receiving end represents inter-symbol interference caused by link nonlinear distortion and bandwidth limitation, and the signal-to-noise ratio of a recovery signal is calculated based on the error vector amplitude. Parameters of a transmitting end are optimized and modeled into a Markov decision process, states comprise rounding factors, scaling factors, constellation forming factors and pre-equalization filter tap coefficients of all levels, and actions are discrete increments of the parameters; a reinforcement learning agent is constructed by using a dual deep action value network, and training is updated in combination with experience playback and a target network. The reward function comprises a threshold satisfaction item and a signal-to-noise ratio change item; parameters are interactively updated in the training stage, and online self-adaptive adjustment is performed in the reasoning stage.

The invention discloses a signal nonlinear distortion compensation method, a model and a communication system, and relates to the technical field of wireless communication. In the present disclosure, based on a preset non-linear compensation fusion model, DPD processing, CFR processing and error compensation processing are performed on an initial OFDM signal, thereby obtaining an initial OFDM signal after non-linear distortion compensation; therefore, through a mode of connecting a BL-DPD module, a BL-CFR module and an error compensation module in parallel in a nonlinear compensation fusion model, the technical defects that in the prior art, after a DPD module is arranged behind a CFR module, the requirement for the sampling rate of ADC / DAC is high, the requirement for the convergence speed of hardware and an algorithm is improved, and the implementation difficulty and cost of a system are increased are overcome; therefore, not only is the requirement of ADC / DAC sampling rate reduced, but also the compensation performance of the DPD for the nonlinearity of the power amplifier is improved, and the communication performance and the sensing performance of the OFDM system are also improved.

The invention discloses a discharge detection method and system for adaptive registration of ultraviolet and visible light images, and belongs to the technical field of image processing. An ultraviolet image and a visible light image of a discharge area of power equipment are respectively captured through an imaging module; motion vectors of a visible light image sequence are calculated according to optical flow motion estimation in a motion scene through a registration module and mapped to an ultraviolet image for displacement compensation, translation compensation is determined by adopting histogram matching in a static scene, and the motion vectors of the visible light image sequence are calculated according to the compensated image. Zooming the ultraviolet image according to the zoom scale calculated by the focal length and the central point of the ultraviolet image, and zooming the effective registration area of the cut ultraviolet image to a target size; and the electric detection module carries out electric discharge detection on the discharge point area according to the registered image. According to the method, the robustness is improved, boundary offset and nonlinear distortion are avoided, edge linear fitting is realized while accurate alignment of the center points is ensured, and the calculation efficiency is remarkably improved in cooperation with integer operation.

A railway roadbed disease diagnosis method based on a convolutional neural network comprises the following steps: acquiring vibration acceleration signals of a train and a railway roadbed, and performing data cleaning on the acquired vibration signals; signal preprocessing, time-frequency domain transformation and feature vector extraction, convolutional neural network-based model training and feature extraction, feature classification and disease recognition, and real-time disease detection and location positioning are realized. According to the invention, a modern signal processing technology and a deep learning algorithm are combined to realize efficient and automatic detection of railway roadbed diseases; signal segmentation, time-frequency domain analysis, image segmentation and convolutional neural network technologies are adopted, a self-adaptive resolution adjustment mechanism is achieved, accuracy and high efficiency of signal feature capture and disease diagnosis are achieved, and the nonlinear distortion problem of multi-band signals can be effectively solved through signal segmentation processing and summarizing fusion.

The invention relates to the technical field of wireless communication, and discloses a sparse channel estimation method and system for 5G-A5G-A super-large scale MIMO. The system comprises a quantitative sensing preprocessing module, a layered sparse reconstruction module, a high-precision guide correction module and a dynamic threshold decision module, and realizes efficient and accurate recovery of channel sparse characteristics under strong quantitative interference through nonlinear distortion compensation, multi-resolution sparse recovery, high-precision reference signal guide correction and parameter adaptive adjustment. The estimation performance is improved; and the calculation complexity is balanced.