1309 results about "Signal modulation" patented technology

The invention relates to the technical field of organic display data processing, in particular to an organic display interface multichannel signal modulation method, which comprises the following steps of: generating a standardized data set through gamma correction and gamut mapping, and inputting the standardized data set into time sequence, amplitude and frequency sub-models deployed in a federal learning framework; and respectively analyzing the pulse width-refresh rate relevance, the driving voltage-brightness nonlinear relationship and the conduction period-mobility dynamic response, generating an optimized weight coefficient, and fusing the optimized weight coefficient into a boundary constraint condition of a cross-sub-model. A migration rate parameter index, amplitude gradient calculation and duty ratio correction service of chain calling is constructed based on a service grid, a reinforcement learning dynamic routing strategy is combined to avoid resource competition nodes, and brightness error characteristics are periodically fed back to reversely optimize gradient updating. According to the method, the conflict between time sequence deviation accumulation and local optimum is effectively suppressed, the color gradation continuity, the dynamic range and the edge sharpness are improved, and efficient cooperative modulation of multi-channel signals is realized.

The invention discloses a method for identifying a multi-model fusion signal modulation mode based on a time-frequency diagram, and belongs to the field of signal processing. Preprocessing the original signal to obtain a signal sample; constructing a data set by using the normalized signal samples; constructing a fusion model; training a modulation identification module in the fusion model; performing modulation mode identification on an input unknown signal by using the fusion model to obtain a preliminary identification result; and performing comprehensive judgment on the preliminary recognition result of the fusion model by using a comprehensive judgment device to obtain a final recognition result. According to the invention, by combining a plurality of time-frequency analysis methods, the time-frequency domain feature information of the signal is fully extracted; the reliability and robustness of a final decision are improved by adopting a multi-model fusion framework, and the modulation recognition performance of the system under the condition of a low signal-to-noise ratio is improved.

The invention provides an accurate flight path tracking control method, device and equipment for an unmanned aerial vehicle, and the method comprises the steps: generating fusion state data through the fusion of GPS flight path data and flight state information, and constructing a flight path-state phase space model through employing a phase space reconstruction technology; phase trajectory feature parameters are extracted based on dynamic trajectory analysis, and dynamic attractor features are determined through attractor recognition processing; analyzing and identifying the center position of an attractor and the position of a topological singular point by using phase space topology, and constructing composite potential field intensity distribution formed by overlapping a conventional gravitational potential field and a repulsion-attraction bipolar potential field; gradient calculation is carried out on the composite potential field, and adaptive modulation is carried out based on the relative relation between the current position and the attractor center; in a local coordinate system taking a singular point as an original point, decomposing a modulation gradient vector into radial and circumferential components, and forming a spiral potential field through selective rotation enhancement; and finally, generating a tracking control instruction and performing signal modulation output, thereby realizing accurate tracking control of the unmanned aerial vehicle on the preset route.

The invention relates to the technical field of high-frequency signal modulation, and discloses a high-frequency carrier synchronization signal modulation system. A carrier distortion compensation module of the system constructs a model based on a historical transmission data set, captures a phase jitter parameter, a spectrum leakage component and a modulation pulse sequence of a transmitting end carrier in real time, and outputs a reconstructed baseband parameter; the multi-dimensional distortion analysis module compares the reconstructed baseband parameter with a receiving end demodulation baseband parameter through composite difference detection, and generates a channel-level distortion coefficient tensor; the topological positioning network module is used for positioning signal out-of-step physical nodes and generating a probability distribution thermodynamic diagram by combining impedance characteristics of transmission nodes and signal path delay information; and the adaptive modulation strategy module starts a multi-band carrier injection mode for the high-probability out-of-step nodes according to the abnormal probability gradient of the thermodynamic diagram, and applies a phase disturbance test to adjacent transmission links. The system can improve the adaptability and accuracy of high-frequency carrier signal synchronous modulation.

The invention discloses an unmanned aerial vehicle radio communication frequency band countering method for automatic frequency identification and frequency writing, and relates to the technical field of unmanned aerial vehicle interference, and the method comprises a frequency band identification module which is used for scanning a 300MHz-6GHz frequency band in real time and identifying an enemy unmanned aerial vehicle communication signal; the signal analysis module is connected with the frequency band identification module, comprises a digital signal processor and an FPGA (Field Programmable Gate Array), and is used for analyzing signal modulation types and spectrum characteristics; the automatic frequency writing module is used for adjusting an interference frequency band through a direct digital frequency synthesis technology according to an analysis result; the multi-frequency-band interference transmitter supports synchronous interference in frequency bands of 1.2 GHz, 2.4 GHz, 5.2 GHz and 5.8 GHz; the intelligent control terminal integrates an adaptive interference algorithm, and the response time is less than or equal to 1 second. According to the unmanned aerial vehicle radio communication frequency band countering method capable of automatically identifying and writing the frequency, the radio communication frequency band used by the enemy unmanned aerial vehicle is automatically identified, and the corresponding frequency band is written in real time for accurate interference, so that the interference effect of an interference system facing the enemy unmanned aerial vehicle is improved.

The invention discloses a multi-mode SAR interference method and device, and belongs to the field of radar electronic countermeasure, and the method comprises the steps: respectively calculating a product matrix of each interference mode in an interference preparation stage; after entering a reconnaissance stage, intercepting a first section of receiving signal, judging whether the first section of receiving signal is an SAR signal or not, estimating parameters of the SAR signal, and extracting one frame of complete SAR pulse signal as a reference signal; intercepting a second section of receiving signal, and judging whether to enter an interference stage or not according to the PRF; after entering the interference stage, receiving a part of SAR pulse signals and recovering the part of SAR pulse signals into complete SAR pulse signals; multiplying the complete SAR pulse signal by the product matrix to obtain a baseband interference signal; and modulating the baseband interference signal into a radio frequency interference signal and transmitting the radio frequency interference signal. According to the invention, multiple modes of interference such as false target implantation, pseudo radio frequency interference and scattered wave interference can be realized, the interference signal modulation complexity is low, and the requirement of the interference device for the isolation of the transceiving antenna is low.

The invention discloses a dynamic unmanned aerial vehicle cluster electromagnetic characteristic modeling method and system based on a digital array radar, and the method specifically comprises the steps: setting radar system parameters, building a time-varying motion model of an unmanned aerial vehicle cluster, and obtaining the formation pose distribution of the unmanned aerial vehicle cluster under a global coordinate system; component decomposition is carried out on an unmanned aerial vehicle CAD model, shielding analysis is carried out under the radar sight line constraint condition, time-varying scattering center parameter extraction is carried out according to the dynamic electromagnetic effect between targets, scattering center space distribution of an unmanned aerial vehicle cluster is updated in a time sequence recursion mode, and construction of a time-varying scattering center model is completed; a radar system signal model is constructed according to digital array radar DAR parameters, multi-dimensional dynamic feature extraction and parameter mapping are carried out, digital array radar multichannel signal modulation and unmanned aerial vehicle cluster target radar echo construction are completed, and radar scattering electromagnetic characteristic modeling of a dynamic unmanned aerial vehicle cluster is realized. According to the method, the model description accuracy is improved, and the calculation process is more efficient.

The invention discloses a satellite signal modulation recognition method based on an enhanced multi-scale feature attention network, and the method comprises the steps: obtaining a to-be-recognized satellite signal, inputting the to-be-recognized satellite signal into a trained enhanced multi-scale feature attention network, and obtaining a satellite signal modulation recognition result. The training process of the enhanced multi-scale feature attention network comprises the following steps: acquiring a satellite communication data set, and performing sample expansion to obtain an augmented sample; performing noise removal processing and feature extraction on the augmented sample to obtain denoised data features; inputting the de-noised data features into a global context sensing module, extracting modulation features of different frequencies and time scales, and performing feature fusion on the modulation features and the de-noised data features to obtain fusion features; and performing feature reconstruction and channel recovery on the fusion features, inputting the fusion features into a Softmax classifier, performing classification prediction, calculating classification loss, and optimizing network parameters through the classification loss. Under a complete blind recognition scene, the accuracy of a satellite signal modulation recognition result can be obviously improved.

The invention discloses an insulation resistance and capacitance measuring circuit and method based on monopulse double-edge analysis, and relates to the related field of the electrical insulation online monitoring technology, and the circuit comprises a detected object and an insulation detection circuit. The insulation detection circuit comprises a controlled pulse voltage source, a coupling resistance network, a current sensor, a switch control module, a signal modulation circuit and a processor. The measurement method implemented based on the circuit comprises the following steps: injecting a common-mode voltage pulse into a transmission line of the power transmission system by adopting a pulse transmitter; pulse current response is collected in real time, a current oscillogram is drawn, and a three-point sampling method is introduced to record a current value for insulation impedance parameter calculation; according to a load condition, a double-edge verification method is applied based on a pulse current attenuation characteristic, and insulation impedance parameters including a resistive component and a capacitive component are independently calculated by analyzing a pulse current rising edge and a pulse current falling edge. According to the invention, non-intrusive synchronous monitoring of resistive and capacitive components of line-to-ground impedance is realized, and the detection precision is improved.

A device (100) and method for self-calibrating a radiofrequency transmitter are disclosed, the device comprising: first circuitry (120) for receiving a reference phase value (ϕ) and configured to output a first analog signal (AI) based on the reference phase value (ϕ); second circuitry (130) for receiving said reference phase value (ϕ) and configured to output a second analog signal (AQ) based on the reference phase value (ϕ); an IQ modulator (110) coupled to receive an input signal (LO), said first analog signal and said second analog signal, and configured to provide an IQ modulator output signal (RFout) based on said input signal, said first analog signal (AI) and said second analog signal (AQ); and compensation control circuitry (150) coupled to receive the IQ modulator output signal (RFout) and configured, during calibration, to output at least one compensation signal indicative of a compensation value based on the IQ modulator output signal (RFout); wherein at least one of said first circuitry (120) and said second circuitry (130) comprises: a digital signal generating portion (210, 310) for generating a digital signal (DI, DQ) based on the reference phase value (ϕ) and at least one said compensation value, a sigma-delta modulator portion (220, 320) coupled to receive the digital signal (DI, DQ) and configured, during calibration, for sigma-delta modulating the digital signal (DI, DQ); and a digital-to-analog converter (230, 330), coupled, during calibration, to receive the modulated digital signal provided by the sigma-delta modulator portion (220, 330) and configured to output said respective first / second analog signal (AI, AQ).

The invention discloses an optical interconnection system on an optical chip and the optical chip, relates to the technical field of communication, and aims to solve the technical problem of low system data capacity in the wavelength division multiplexing technology in the prior art. The system comprises a micro-ring modulation device, a polarization combiner and a demultiplexer, the output end of the micro-ring modulation device is connected with the input end of the polarization combiner; the input end of the demultiplexer is connected with the output end of the polarization combiner; the micro-ring modulation device is used for performing signal modulation on TE0 polarized light and TM0 polarized light in the light source; the polarization combiner is used for combining the TE0 polarized light and the TM0 polarized light output by the micro-ring modulation device and outputting combined light; and the demultiplexer is used for decomposing the combined light into signals corresponding to a plurality of wavelengths. By combining the polarization multiplexing technology and the wavelength division multiplexing technology, the number of multiplexing channels of the optical interconnection system is multiplied, and the data capacity of the optical interconnection system is improved.

The invention provides a harmonic reducer fault diagnosis method and system combining SAH with SSET under a time-varying rotating speed, and belongs to the field of harmonic reducer fault diagnosis. The invention aims to solve the problems of large time-frequency ridge line extraction error and inaccurate fault feature order extraction caused by the non-stable and signal modulation characteristics of a harmonic reducer vibration signal under a time-varying rotating speed. According to the SAH construction method based on sub-band rearrangement dual-tree complex wavelet packet transformation, a band elimination filter is designed according to an optimal frequency band, and a resonance frequency band where a fault impact component is located is filtered out; a time-frequency ridge extraction method combining SAH-SSET with a fast path optimization algorithm is provided, a frequency ambiguity phenomenon is improved, order analysis is carried out based on the frequency ambiguity phenomenon, and then the fault type of the harmonic reducer is judged according to an envelope order spectrum.

The invention relates to a signal-to-noise ratio adaptive signal modulation identification method. The method comprises the following steps: inputting IQ information and a signal-to-noise ratio (SNR) estimated value of a signal into a signal modulation identification model, and identifying to obtain a modulation mode of the signal; the signal modulation identification model is an MCLDNN of which the feature fusion module is provided with an SNR attention module; the SNR attention module can receive the SNR estimated value and obtain a signal-to-noise ratio attention weight according to the SNR estimated value; receiving a signal multi-channel fusion feature map output by the multi-channel fusion convolutional layer of the MCLDNN; weighting the signal multi-channel fusion feature map by using a signal-to-noise ratio attention weight, connecting the weighted signal multi-channel fusion feature map with a signal multi-channel fusion feature map residual error, and outputting a multi-channel fusion feature combined with SNR attention; and the multi-channel fusion features combined with the SNR attention are input to a time sequence module of the MCLDNN.

The invention discloses an LED liquid crystal display screen brightness and color difference detection and correction method and system, and belongs to the technical field of liquid crystal display. Initial brightness values and color values of all display units of a display screen are obtained; constructing a brightness and color difference reference model based on the convolutional neural network, and calculating a brightness deviation delta L and a color deviation delta C between the brightness and color difference reference model and a standard value; constructing a brightness-color difference error matrix W; according to the error matrix and in combination with a self-adaptive threshold algorithm, identifying a brightness-color difference abnormal region and corresponding coordinates of the brightness-color difference abnormal region; based on a deviation scoring result, introducing a gradient regression model to generate a brightness gain coefficient and a color adjustment coefficient, and constructing a correction parameter set P; the parameter set is issued to a control chip, dynamic image signal modulation and local frame level refreshing are executed, and point-by-point brightness and color difference correction is achieved; the method has the advantages of high precision, high automation, high adaptive capacity and the like, and is suitable for improving the brightness and color difference uniformity in various LED liquid crystal display screen scenes.

The invention belongs to the technical field of communication, and relates to a time-frequency multi-dimensional coding frequency hopping communication method and device based on Rydberg atoms. Comprising the following steps: exciting a cesium atom system from a ground state to an intermediate excitation state by utilizing probe light, and exciting the cesium atom system from the intermediate excitation state to a Rydberg state by utilizing coupling light; determining the resonant frequency and the non-resonant frequency of a carrier based on the energy level of the cesium atom system in the Rydberg state, and selecting the carrier of the resonant frequency or the non-resonant frequency according to the binary state of the baseband signal to perform time-frequency coding to generate a frequency hopping sequence; and radiating the frequency hopping sequence to a cesium atom system in a Rydberg state, and receiving a spectral signal of the transmissivity of the detection light passing through the cesium atom system so as to complete receiving of a baseband signal. According to the invention, frequency hopping sequence synchronization and signal modulation are not needed, the complexity of the system is reduced, and the method has the characteristic of tracking interference resistance.

The invention discloses a semi-supervised LPI radar signal modulation identification system and method based on entropy perception pseudo labels, and relates to the technical field of radar signal processing and mode identification. The system comprises a preprocessing module, a multi-scale reconstruction enhancer, a classification backbone network and a semi-supervised training module. The multi-scale reconstruction intensifier is used for reconstructing dual-channel separation through high-frequency detail enhancement and a low-frequency structure and enhancing discriminative characteristics in a noise environment; the classification backbone network introduces an adaptive contraction unit to realize channel-level noise suppression; and the semi-supervised training module dynamically evaluates the uncertainty of the unlabeled samples by adopting an entropy sensing mechanism, and generates weighted pseudo labels to carry out consistency regularization training. The method realizes signal modulation identification based on the system. According to the method, the problem of feature shielding under the condition of low signal-to-noise ratio is solved, the dependence of the model on labeled data is reduced through a reliable pseudo label generation mechanism, and stable and efficient modulation identification can still be realized in a severe channel environment with scarce labeled data.

The invention discloses a multipath effect suppression method for indoor visible light positioning, relates to the technical field of indoor visible light communication and positioning, and aims to solve the problems in the prior art, the method comprises the following steps: constructing a fractional order chaotic signal generator and starting to generate a chaotic sequence signal; the chaotic sequence signals are modulated and loaded to an LED array and a driving circuit thereof, and optical signals carrying fractional order chaotic characteristics are generated and transmitted; after being propagated indoors, the optical signal is acquired by a photoelectric detector, is preprocessed and then is transmitted to a field FPGA (Field Programmable Gate Array); in the FPGA, based on a compressed sensing theory, modeling the received signal and constructing an adaptive sensing matrix to obtain a compressed observation signal; iteratively recovering sparse channel response from the compressed observation signal by adopting a path focusing guide orthogonal matching pursuit algorithm; and the FPGA extracts main path information from the reconstructed sparse channel response, and calculates a final positioning coordinate in combination with an arrival time positioning model. And in indoor visible light positioning, the method has a good capability of resisting a multipath effect.

The invention discloses an intelligent signal modulation identification method and system fusing time-frequency characteristics. The method comprises the following steps: extracting time-domain characteristics and frequency-domain characteristics in a radio signal in a complex baseband form; fusing the radio signal, the time domain feature and the frequency domain feature to obtain a multi-channel fusion feature; training a convolutional attention network model comprising a stem embedding layer, a plurality of cascaded feature extraction stages and a classification head; inputting the multi-channel fusion features into a trained convolutional attention network model, and performing feature extraction on the multi-channel fusion features through a stem embedding layer to obtain first extraction features; performing deep feature extraction on the first extraction feature through a plurality of cascaded feature extraction stages to obtain a second extraction feature; and inputting the second extraction feature into a classification head for signal modulation identification to obtain a signal modulation identification result corresponding to the radio signal. According to the invention, the accuracy of signal modulation identification can be improved.

A method includes receiving a bit string at a processor, performing an error correction, and causing transmission of a modulated signal. The error correction includes identifying a set of binary strings based on the bit string, mapping each binary string from the set of binary strings to a first abelian group element from a set of first abelian group elements, and applying a generalization of polar codes to the set of first abelian group elements to produce a set of second abelian group elements. The error correction also includes mapping each of the second abelian group elements to an in-phase / quadrature (I / Q) point from a set of I / Q points and identifying real-valued points based on the set of I / Q points, each of the real-valued points representing an I / Q point from the set of I / Q points. The modulated signal has a modulation that is based on the real-valued points.

The invention belongs to the technical field of direct-current converters, and particularly relates to a sliding mode control-based dual-active bridge converter current stress optimization method, which is suitable for a direct-current micro-grid cluster interconnection converter which is a dual-active bridge converter. The method comprises the following specific steps: constructing mathematical models of transmission power and current stress of the dual active bridge converter in two signal modulation modes of single phase shift modulation and expanded phase shift modulation and soft switching characteristics under mode correspondence; constructing an order reduction model of the dual-active bridge converter; constructing an expression which takes the current stress as an optimization target and then adopts a Karush-Kuhn-Tucker (KKT) algorithm to solve an optimal phase shift ratio; and constructing a single-integral sliding mode controller and a double-integral sliding mode controller based on the double-active-bridge reduced-order model and carrying out equivalence. According to the method, single-integral and double-integral sliding mode control and single phase shift and expanded phase shift modulation are compared, and current stress optimization is adopted under integral sliding mode control, so that the converter has relatively good dynamic performance under integral sliding mode control, and meanwhile, current stress is relatively well reduced.

The invention belongs to the technical field of cognitive radio, and particularly relates to an open set modulation identification method based on time-frequency domain feature learning and fusion. The method comprises the following steps of: receiving a signal by adopting a receiving antenna through electromagnetic spectrum monitoring equipment, capturing a space electromagnetic radiation signal, converting the space electromagnetic radiation signal into an electric signal, amplifying the signal through a low-noise amplifier, performing frequency conversion and filtering through an analog receiver, and converting the received signal into an intermediate-frequency signal. Then, the signal is digitalized through AD sampling, and the intermediate frequency signal is converted into a baseband complex signal through frequency mixing and digital filtering in a digital receiver. Then performing time domain characterization calculation and frequency domain characterization calculation on the signal sampling data to form a plurality of time domain characterization vectors and a plurality of frequency domain characterization vectors; and then the vectors are sent to a trained deep neural network model, reasoning is carried out by using the network model, a reasoning result is post-processed, and a signal modulation identification result is finally obtained. According to the invention, the recognition accuracy of unknown signals is improved.

The invention discloses a directional communication radio frequency signal hiding processing system based on a geostationary orbit satellite link, and belongs to the technical field of directional communication, and the system comprises an analog signal interface module which is used for collecting an analog signal and converting the analog signal into a digital signal; the random directional communication channel generation module is used for dynamically generating a random communication channel which comprises sending time randomization and sending direction randomization; the dynamic signal modulation module is used for carrying out randomized modulation and coding on the target signal; the complex signal shielding module is used for generating shielding signals similar to target signal features and covering the existence and parameter features of real communication signals; and the direct radio frequency modulation module is responsible for modulating the digital signal to a radio frequency band and transmitting the digital signal through an antenna. According to the invention, the random directional communication channel is designed, so that the risk that a signal is interfered by adopting a conventional channel is avoided; secondly, complex signal shielding is carried out on the sent signal, so that the risk that the target signal is intercepted and cracked is reduced;

The invention provides a signal modulation method and a related device, and the method comprises the steps: obtaining a first symbol sequence, carrying out the single-carrier modulation of the first symbol sequence, enabling the phase difference between two adjacent symbols in the first symbol sequence to be 90 degrees, enabling the single-carrier modulation to comprise the frequency spectrum adjustment based on a first scaling factor and the frequency domain spectrum shaping FDSS, the spectrum adjustment comprises spectrum compression; and determining a signal generated after the first symbol sequence is subjected to single-carrier modulation. According to the method, the first symbol sequence with the phase difference of 90 degrees between two adjacent symbols is subjected to single-carrier modulation, a single-carrier modulation scheme for performing frequency spectrum compression in a frequency domain is provided, the frequency spectrum efficiency is improved, and a single-carrier signal with low PAPR is generated.

The invention discloses a photovoltaic optimization regulation and control method and device based on an MPPT technology, and particularly relates to the technical field of photovoltaic power generation control, and the method specifically comprises the following steps: S1, full-link operation state synchronous collection, S2, DC bus ripple feature extraction, S3, multi-source disturbance quantitative evaluation, S4, cooperative control parameter decision making, and S5, grid-connected signal synthesis modulation. A multi-source disturbance quantitative evaluation system is adopted, the irradiance change gradient, the frequency ratio and the switching noise contribution ratio are subjected to multi-dimensional fusion, a dynamic weight distribution mechanism is established, and parallel optimization of MPPT mode selection, disturbance step length adjustment and PWM phase shift angle is achieved through a cooperative control parameter decision architecture. A response delay bottleneck existing in a traditional serial decision mode is broken through, and a ripple compensation component is dynamically injected while stable output of fundamental current is maintained based on a grid-connected signal modulation strategy of vector synthesis.

The invention discloses a high-spatial-resolution distributed optical fiber sound wave sensing system based on FPGA real-time demodulation. The system comprises a narrow linewidth laser source module, a first coupler, a high-bandwidth sweep frequency signal modulation module, a circulator, a coherent receiving and photoelectric conversion module and an FPGA integrated module. A laser source emitted by the narrow linewidth laser source module is divided into about 10% of reference light and about 90% of detection light through the first coupler. The FPGA integrated module is connected with the high-bandwidth sweep frequency signal modulation module, and transmits a sweep frequency radio frequency pulse signal and a frequency shift radio frequency pulse signal to the high-bandwidth sweep frequency signal modulation module; the high-bandwidth sweep frequency signal modulation module is connected with the sensing optical fiber through the circulator so as to output sweep frequency optical pulses; the sensing optical fiber is connected with the coherent receiving and photoelectric conversion module through the circulator to transmit Rayleigh backscattered light; the coherent receiving and photoelectric conversion module is connected with the FPGA integrated module, and the FPGA integrated module carries out signal processing to obtain vibration information on the optical fiber.

The invention discloses a simulation verification method for an ASIC (Application Specific Integrated Circuit) control loop of a metal micro-resonance hemisphere-like gyroscope. The method comprises the following steps: based on an input angular velocity and a control signal, generating a vibration signal of a harmonic oscillator by using a pre-constructed dynamics simulation model; modulating and demodulating the vibration signal through a signal modulation and demodulation module, extracting a low-frequency component and removing high-frequency noise to obtain a parameter representing a modal precession state; an antinode control signal and a wave node control signal are generated through a PID controller module based on the parameters representing the modal precession state; an antinode control signal and a wave node control signal are decomposed to an orthogonal direction through a coordinate transformation and combination module to generate a driving signal, and the driving signal is applied to a harmonic oscillator to form a closed-loop self-excitation driving control loop; and verifying the dynamic performance of the closed-loop self-excitation driving control loop in a simulation environment. The technical problems of high power consumption, complexity and development cost of simulation verification are solved.

The invention belongs to the technical field of artificial intelligence, and particularly relates to an audio processing method, an audio processing device, a computer readable medium, electronic equipment and a computer program product. The audio processing method comprises the following steps: performing feature extraction on an audio signal to obtain frequency domain features of a plurality of audio frames; the audio signal carries a voice signal and a noise signal; serialized modeling is carried out on the frequency domain features of the audio frames, intra-frame sequence features are obtained, and the intra-frame sequence features are used for representing the frequency sequence relation among a plurality of frequency points in the single audio frame; serialization modeling is carried out on the intra-frame sequence features of the multiple audio frames to obtain inter-frame sequence features, and the inter-frame sequence features are used for representing the time sequence relation among the multiple audio frames; and performing signal modulation on the audio signal according to the inter-frame sequence features to obtain a voice signal after noise signal removal. According to the embodiment of the invention, the speech enhancement noise reduction effect can be improved.

The utility model discloses a background suppression photoelectric sensor realized based on double PD. The background suppression photoelectric sensor comprises an MCU control circuit, an LED drive circuit, an acquisition module, a target object, a differential amplification circuit, a voltage comparison circuit and a self-adaptive output circuit. The acquisition module is used for receiving reflected light signals of a target object and converting the reflected light signals, then the differential amplification circuit amplifies and converts PD signals received by the acquired signals, and then analog quantity signals are converted into pulse signals through the voltage comparison circuit, so that the MCU control circuit can be used for processing logic signals and modulating PWM signals. The LED driving circuit is arranged to drive the LED diode D6 to work; the background suppression photoelectric sensor realized by a photodiode PD1, a photodiode PD2, a differential amplification circuit, a voltage comparison circuit and an MCU control circuit adopts an automatic frequency conversion technology to solve the problem of optical crosstalk among multiple sensors, and is suitable for background suppression photoelectric sensing.

The invention discloses a radar signal intelligent sorting method based on a GraphGated graph convolutional neural network, relates to the radar signal intelligent sorting method based on the GraphGated graph convolutional neural network, and belongs to the field of information and communication engineering. The objective of the invention is to solve the problem of difficulty in signal sorting of unknown signal sensing in a high-pulse-density environment, complex inter-pulse signal modulation and transient conditions of a current passive radar, an electronic reconnaissance radar, a cognitive radar, frequency spectrum situation sensing and the like. The method comprises the following steps of: 1, assuming that V pulse description words are received within time T; 2, constructing an adjacent matrix A based on the V preprocessed pulse description words, and constructing a radar pulse description word graph marked with node category attributes based on the adjacent matrix A; 3, obtaining a trained graph convolution model; 4, acquiring B to-be-tested pulse description words, and outputting feature vectors of the B pulse description words based on the trained model; and obtaining a clustering result through a clustering algorithm.

The invention discloses a signal modulation identification method fused to Transform and a hybrid expert mechanism, and belongs to the technical field of wireless communication and artificial intelligence crossing. The method solves the problem that the model capacity and the adaptability to complex signals are limited by a fixed feed-forward network in the automatic modulation identification of the conventional Transform model. According to the technical scheme, the method comprises the steps of inputting dual-channel time sequence signals of in-phase components and orthogonal components; extracting preliminary features through convolution operation; the features are input into a Transform architecture integrating an attention mechanism and a hybrid expert mechanism; in the hybrid expert mechanism, calculating a routing weight through a gating network with noise routing and sparsely activating an expert network; merging expert outputs according to routing weights to obtain depth features; and finally, outputting a modulation identification result through the classifier. According to the method, the calculation efficiency is maintained while the model parameter scale is expanded, and the recognition accuracy in a complex channel environment is improved.