121 results about "Linear modulation" patented technology

The invention provides an industrial defect image generation system and method based on deep learning, and relates to the technical field of artificial intelligence. A defect form adaptive module, a physical attribute modulation module and a multi-mechanism fusion module are integrated in a defect image generation module; dynamically selecting a feature extraction unit according to the defect type label based on a pre-constructed generative network model, and generating a defect feature map; generating an affine transformation parameter based on the physical attribute vector, and performing channel-by-channel linear modulation on a defect feature map of a middle layer of the generative network model, so that a multi-scale defect feature map finally generated by the generative network model contains specified defect type features and physical attribute features; and fusing the multi-scale defect feature image and the defect-free background image to obtain a fused defect image. The problems that in the prior art, industrial defect image generation is insufficient in sense of reality, poor in controllability and poor in fusion effect are solved, the method can be used for data enhancement of industrial visual inspection, and downstream model performance is improved.

The invention discloses an intelligent agent digital image interaction generation method based on multi-modal perception, which comprises the following steps: collecting multi-modal input data of a user, and respectively carrying out preprocessing and feature extraction on the multi-modal input data; inputting to an improved efficient modal cross learning network, and carrying out multi-modal feature fusion processing; constructing a semantic intention map, introducing a time index edge weight and an emotion driving edge weight, and encoding the map by using a structure perception map neural network; a modal style vector is extracted through a cross-modal style contrast learning mechanism, and a personalized style coding vector is generated through a hierarchical nested structure; inputting a personalized regulation and control gating mechanism, and regulating and controlling the middle layer representation in the interaction strategy generation process by adopting a feature channel linear modulation method; inputting the representation vector into a behavior strategy generation module to generate a multi-modal behavior output sequence; and the sequence is output to drive the digital image to perform synchronous response, and natural response generation in the user interaction process is completed.

The invention discloses a long-tail data generation method based on feed-forward stylized reconstruction. The method comprises the following steps: constructing multi-modal geometric perception input and feature codes; reconstructing a semantic guidance scene based on a feature-level linear modulation mechanism; the invention relates to 3D consistency controllable style migration based on a feedforward reconstruction model. According to the invention, a feedforward reconstruction network based on DINOv2 improvement is constructed. Multi-modal adaptation is performed on a backbone network input layer, and decoupled high-level semantic features are explicitly injected by using a feature-level linear modulation mechanism, so that the geometric accuracy of automatic driving scene reconstruction is improved. On the basis of a three-dimensional scene of feedforward reconstruction, a distillation strategy is adopted, and the generation capability of a 2D diffusion model is migrated to a 3D Gaussian field. According to the method, the phenomena of object deformation, disappearance and the like in the generated data are effectively avoided, and long-tail weather data with geometric consistency of rain, snow and the like can be generated through the text instruction.

The invention discloses a small sample crack recognition method and system based on transfer learning, and the method comprises the steps: constructing an innovative and deep-coupled neural network architecture, and enabling a self-adaptive crack perception attention module integrated with a parallel asymmetric convolution kernel to recognize the linear geometric features of a crack, and generating an attention graph; then, the attention map is adopted to carry out pixel-by-pixel signal pre-modulation on an original input image, the enhanced image is sent to a pre-training MobileNetV4 backbone network integrated with a feature-level linear modulation layer, and channel-level dynamic adaptation of feature flow in the network is realized by learning affine transformation parameters; and finally, the extracted depth features are sent to a Gaussian naive Bayes classifier for classification, and depth geometric analysis is carried out on the attention map so as to realize interpretable fracture severity evaluation. According to the method, the accuracy, robustness and interpretability of crack identification are remarkably improved, and the technical bottleneck in a small sample scene is effectively solved.

The invention relates to the technical field of optical fiber sensing, in particular to a distributed optical fiber vibration-temperature combined monitoring method and system. Comprising the following steps: carrying out linear frequency modulation on single-frequency light waves output by a light source to enable the single-frequency light waves to serve as probe light for distributed vibration and distributed temperature sensing at the same time; linear sweep frequency light is injected into an optical fiber to be measured, and Rayleigh scattering and Raman scattering light signals in the optical fiber are separated by using a wavelength division multiplexer. And the vibration information of each point along the optical fiber is recovered by combining a Rayleigh scattering light signal with a coherent detection architecture through algorithms such as back-end matched filtering and the like. And the Raman scattering light signal is combined with intensity detection and a dual-wavelength difference algorithm, so that the temperature information of all optical fiber lengths can be recovered. According to the invention, vibration and temperature measurement is realized in the same system, and the problems of temperature and vibration measurement time synchronization, sampling rate alignment and the like in different systems are avoided.

The invention belongs to the technical field of speech enhancement, and particularly relates to a controllable causal double-path speech enhancement method and system, and the method comprises the steps: taking noisy speech collected in an actual scene as input, carrying out the short-time Fourier transform, and obtaining a complex spectrum containing an amplitude spectrum and a phase spectrum; constructing a streaming encoder, taking the complex spectrum as input, and extracting local correlation of the noisy speech in a time dimension and a frequency dimension; a controllable causal double-path module is constructed, long-term dependency relationship modeling is carried out on the time dimension and the frequency dimension, and linear modulation is carried out on channel characteristics through control parameters; constructing a streaming amplitude / phase decoder, and reconstructing an amplitude spectrum and a phase spectrum of the enhanced speech; and performing short-time inverse Fourier transform by combining the reconstructed amplitude spectrum and phase spectrum to obtain the waveform of the enhanced speech. According to the invention, the real-time adjustment of the output characteristics of the voice enhancement network is realized, and the noise residue and the voice distortion level can be timely balanced according to the demands of a listener in the voice enhancement process.

The invention belongs to the technical field of frequency stabilization control of a semiconductor laser, and provides a frequency stabilization method and system based on acetylene molecule absorption spectrum characteristic feedback. Closed-loop locking of laser output frequency can be realized through current and temperature combined rapid control, extraction of acetylene molecule frequency discrimination curve characteristics and construction of a mapping relation between the frequency discrimination curve characteristics and a tuning frequency stabilization center point: timely correction before frequency lock losing, frequency stabilization time prolonging and rapid back locking after frequency lock losing. The method inherits the advantages of simple device and wide application range of a traditional linear modulation absorption semiconductor DFB laser frequency stabilization system, overcomes the defect that manual correction is needed after unlocking of a traditional frequency stabilization method, and has remarkable technical advantages in application scenes where laser frequency locking is needed for a long time without human intervention.

The invention discloses a high-spatial-resolution TGD-OFDR system and a working method thereof, relates to the technical field of distributed sound wave sensing, and is used for obtaining a large sweep frequency range by using relatively low modulation cost. The high-spatial-resolution TGD-OFDR system comprises a laser, an optical fiber coupler, a semiconductor optical amplifier, a broadband acoustic optical modulator, an optical isolator, a photoelectric detector, an optical fiber circulator, a photoelectric balance detector, a data acquisition card, a computer, a radio frequency signal source, a radio frequency correction unit and the like. The frequency sweeping range of the system is flexibly realized by repeated linear modulation of the low-bandwidth broadband acousto-optic modulator, the size of the frequency sweeping range is related to repeated modulation times, the frequency sweeping range can be flexibly controlled by controlling the repeated modulation times, and the spatial resolution of the system is improved; compared with a mode of using a large-bandwidth modulator and a high-performance radio-frequency signal source, the system provided by the invention has the advantages that the performance requirements on the radio-frequency signal source and the modulator are reduced, and the system cost is low.

The application discloses a kind of based on multiple exposure generation fusion's low-light image enhancement system, belong to low-light image enhancement technical field.System includes: adaptive multiple exposure adjustment module (AMEA), joint prediction gamma coefficient, linear modulation factor and compensation parameter, to input low-light image carries out nonlinear and linear combination transformation, generates multiple luminance, contrast and different color response multiple exposure candidate image;Multiple exposure fusion module (MEF), original low-light image and candidate image channel splicing are carried out, and preliminary enhancement image is obtained by fine-grained weighting fusion of channel fusion coefficient and introduction of perception compensation parameter correction;Color refinement module (CRM), using encoder decoder structure and introducing fast fourier representation in bottleneck layer, realize spatial domain and frequency domain joint modeling, carry out global color calibration and local detail optimization to preliminary enhancement image.The overall network uses lightweight design such as depth separable convolution and dense connection, inference is simple, and can be run in real time in edge device.The application generates by adaptive multiple exposure, structure constraint fusion and frequency domain refinement, effectively restores dark texture, suppresses over-enhancement and color deviation, improves visual naturalness and robustness in complex low-light scene.

The invention relates to a method and a system for detecting nonlinear modulation of tide to sea waves, processing equipment and a storage medium. The method comprises the following steps: acquiring an observation data set and preprocessing the observation data set; carrying out holographic marginal spectrum analysis on the preprocessed observation data set, and determining a holographic marginal spectrum of each piece of observation data in the observation data set; generating a plurality of groups of alternative data for the preprocessed observation data set; holographic marginal spectrum analysis is conducted on the generated multiple sets of replacement data, corresponding holographic marginal spectrums are calculated respectively, the # imgabs0 # percentile of the holographic marginal spectrum values of the multiple sets of replacement data serves as the # imgabs1 #%-confidence level of the holographic marginal spectrum values of the observation data, and # imgabs2 # is the preset significance level; and for the same modulation frequency, if the holographic marginal spectrum value of the observation data is smaller than # imgabs3 #%-confidence level, the modulation of the modulation frequency on the observation data is statistically incredible, otherwise, the modulation of the modulation frequency on the observation data is statistically credible, and the method can be widely applied to the field of signal processing.

This invention discloses a method for inverting sea surface wind speed from GNSS reflected signals based on mask perception and image-based Mamba-CNN. The method includes: performing spatiotemporal matching and interpolation processing on multi-source spaceborne GNSS-R observation data and ERA5 reanalysis data; gridding the processed observation parameters according to geographical location to obtain a multi-channel grid image and acquiring a binarized occupancy mask; inputting the multi-channel grid image and the binarized occupancy mask into a mask perception Mamba-CNN model; calibrating the grid features through a mask conditional encoder and a feature linear modulation layer, and performing spatial modeling using feature extraction blocks combining convolutional and Mamba state space paths to obtain the wind speed inversion result; aggregating the extracted features using center-perception pooling, and outputting the final sea surface wind speed inversion image through a regression network. This invention can significantly reduce computational complexity, effectively reconstruct the continuous wind field structure, and improve the inversion accuracy and robustness in high-wind-speed areas.

Provided in the embodiments of the present application are a speech enhancement method, a speech enhancement model training method and a computer program product. The speech enhancement method comprises: acquiring a speech data sample of a target speaker, and performing spectral feature extraction on the speech data sample on the basis of a bidirectional long short-term memory network layer and an attention statistics pooling layer, so as to obtain a spectral feature of the target speaker; inputting the spectral feature into a feature-wise linear modulation layer in a time-frequency narrow-band neural network, and by means of the feature-wise linear modulation layer and on the basis of the spectral feature, adjusting a spectral feature corresponding to mixed speech data extracted by the time-frequency narrow-band neural network, wherein the mixed speech data at least comprises speech data of a plurality of speakers including the target speaker; and on the basis of the adjusted spectral feature, performing speech enhancement processing on the speech data of the target speaker in the mixed speech data, so as to obtain the enhanced speech data of the target speaker.

The invention discloses a visual navigation method and system based on a denoising diffusion bridge model. The method comprises the following steps: acquiring initial image data; performing feature coding processing on the initial image data to generate a context vector; performing linear modulation processing on the context vector to generate a conditional variable; according to the context vector and a preset motion rule, a prior action is generated; inputting the priori action and the conditional variable into a denoising diffusion bridge model for diffusion training, and generating a target navigation action; wherein the priori action is used as an initial state of the de-noising diffusion bridge model during reverse de-noising processing. Redundant iteration in the diffusion process can be effectively reduced, accumulative errors are reduced, the efficiency and stability of action generation are greatly improved, and the method can be widely applied to the technical field of computers.

The present invention relates to a control system (20) and method for controlling the flow of current between a voltage source (22) and a multiphase motor or other application / load for controlling a multiphase motor (28). The control system includes, between each phase of the multiphase motor and the voltage source: a high-side diode (30A-C) and a high-side switch (34A-C) positioned in parallel between a positive terminal of the voltage source and the motor, wherein the high-side diode is reverse biased with respect to the positive terminal; and a low-side diode (32A-C) and a low-side switch (36A-C) positioned in parallel between a negative terminal of the voltage source and the motor, wherein the low-side diode is reverse biased with respect to the motor. The control system operates the high-side and low-side switches to provide efficient operation of the motor.

The invention provides a piezoelectric ceramic-based double-optical-comb-cavity modulated gas measurement system and method, a double-optical-comb output module is utilized to generate a detection optical comb and a reference optical comb which are coherent, the detection optical comb enters a resonant cavity to interact with gas to be measured, and the reference optical comb directly reaches a data acquisition and analysis module; the piezoelectric ceramic modulation module dynamically adjusts the length of the resonant cavity by applying a periodic voltage signal; and the data acquisition and analysis module demodulates spectral data of the to-be-detected gas through an asynchronous sampling technology based on double optical comb interference signals of the reference optical comb and the detection optical comb. According to the dual-optical-comb-cavity modulated gas measurement system based on the piezoelectric ceramics, the piezoelectric ceramic modulation module is used for dynamically adjusting the length of the resonant cavity according to the detection optical comb and the reference optical comb, dynamic modulation and transient coupling optimization of the cavity length are achieved, and the problems that in the prior art, the dispersion effect of gas can affect optical signal propagation, and the measurement precision is poor are solved. And non-linear modulation occurs in the ring-down process, so that the measurement precision is influenced.

The present invention discloses a graph embedding entity alignment method based on reinforcement learning enhancement. The present invention adopts the method of constructing heterogeneous subgraphs, and only performs message aggregation on the n-hop neighbors of the entity pairs to be aligned, which directly reduces the computing resource requirements. A graph embedding learning algorithm based on feature linear modulation is used, and the idea of ​​super network is introduced to complete the message transmission mechanism and node update mechanism with high computational complexity with a small number of parameters, so as to better utilize the interactive information between nodes. In addition, the present invention proposes a node selector enhanced by reinforcement learning, proposes and applies a reliability measurement method based on self-supervisory signals in the node selector, samples a certain number of reliable edges, filters problem edges while limiting the size of heterogeneous subgraphs, and ensures the reliability of edges participating in node updates. The present invention also implements a node sampling quantity update strategy based on reinforcement learning, dynamically optimizes the number of sampled nodes, and enhances the node selector.

The present application relates to the technical field of image processing, and more particularly to a lesion segmentation method of adaptive dynamic text prompt, comprising: acquiring a lesion image, and generating an adaptive dynamic text prompt based on the lesion image; constructing a multi-modal enhanced fusion text prompt adapter based on a FiLM global channel recalibration module, a spatial cross-attention interaction module and a zero initialization gate nonlinear integration module cascade; the global channel recalibration module of FiLM utilizes a feature linear modulation mechanism to perform channel-level weighting on a visual feature map; before the feature enters spatial interaction, according to the text semantic enhancement band response, the activation of the background noise channel is inhibited. The present application overcomes the problems of insufficient utilization of multi-modal prompts, dependence on artificial static labeling of text prompts, serious dependence on prior information in the reasoning stage and difficulty in multi-modal feature fusion in a low-contrast environment in the existing medical image segmentation technology.

The present invention discloses a pulse laser coherent ranging method and device based on linear frequency modulation local oscillator, comprising: when a first linear modulator is triggered, a linear frequency modulation signal of a preset frequency interval is generated; based on the generated linear frequency modulation signal, a target signal is linearly frequency modulated to form a first signal; the signal light is modulated; the modulated signal light is combined with the first signal; after the combined light signal passes through a detector, the acquired echo signal is sampled and matched filtered; and the distance is resolved according to the result of the matched filtering. The embodiment of the present application adopts different linear modulation modes for the local oscillator light and the output light, respectively, and uses the principle of coherent detection to match filter the linear modulation waveform after the echo difference frequency, thereby solving the problems of multiple blind points and distance ambiguity in high repetition rate integrated pulse laser ranging.

This invention provides a production monitoring system for mirror cabinet processing equipment based on multi-source data, relating to the field of process control. The system acquires multi-source data from the mirror cabinet through an acquisition module and constructs a discrete mesh model; a deviation topology construction module generates directional selective edge weights and a nonlinear modulation function; a propagation control coupling module achieves synchronous iterative convergence of deviation states and control components; a topology constraint module identifies structural boundaries and divides control sub-regions; a region control module generates region control vectors, which are then decomposed into processing adjustment quantities and coupled in by the instruction module; and a feedback reconstruction module optimizes parameters based on the processing results. This invention enables deviation propagation to match the processing path, achieving bidirectional coupling of state and control, thus improving accuracy and control stability in the processing of complex curved surfaces and multi-material mirror cabinets.

This application discloses a soft-start method, apparatus, device, and storage medium for a three-phase LLC converter. The soft-start method includes: responding to a start command, pre-charging the three phases of the three-phase LLC converter in a preset sequence; after the three phases have completed pre-charging, performing coordinated linear modulation on the duty cycle and frequency of the three phases so that the duty cycle of each phase approaches a preset target duty cycle, and the frequency of each phase approaches a preset target frequency; and controlling the three-phase regulated output when the duty cycle of each phase reaches the preset target duty cycle and the frequency of each phase reaches the preset target frequency. This application can achieve more stable and safer three-phase soft starting.

The invention discloses a motor linear overmodulation method and device, a vehicle and a storage medium, and the method comprises the steps: obtaining a reference voltage component and a DC bus voltage of a motor, and obtaining a reference voltage amplitude and a reference voltage phase angle according to the reference voltage component; a modulation coefficient is obtained according to the reference voltage amplitude and the direct-current bus voltage, the working area of the motor is judged according to the modulation coefficient, and the working area is divided into a linear modulation area, an overmodulation I area and an overmodulation II area according to the modulation coefficient; and when the working area is the overmodulation II area, obtaining a dynamic weight coefficient according to the reference voltage phase angle, and controlling the motor according to the dynamic weight coefficient. Therefore, when the working area of the motor is the overmodulation II area, the motor is controlled according to the dynamic weight coefficient obtained by the voltage phase angle, so that the voltage jump of the overmodulation II area is eliminated, the power performance of the electric vehicle driving system is improved to the maximum extent, and meanwhile, the output smoothness is ensured.

The invention discloses a direct-current-bias-free high-power LED visible light signal transmission method and system, and relates to the technical field of optical communication, and the method comprises the steps: carrying out 64QAM-OFDM modulation and IQ modulation on original audio and video data, carrying out AC coupling peak-to-peak value extraction and DC component filtering, and then carrying out single-power-supply amplification and pre-equalization; and a driving positive voltage signal is generated to drive a high-power LED to emit light, and an optical communication signal is generated. Through a low-loss alternating-current coupling transmission mode, the modulated real signal peak-to-peak value is subjected to coupling transmission and single positive power supply amplification, so that the signal is changed into positive voltage to control the LED light intensity and form an LED optical communication signal, direct-current voltage does not need to be introduced into a digital domain, the problem of bandwidth reduction is avoided, and the signal transmission efficiency is improved. The direct-current bias voltage of the LED can be kept stable, the LED works in a linear modulation area, bandwidth expansion is carried out through the pre-equalization circuit, and the functions of LED illumination and high-speed communication can be considered.

The invention discloses a small sample process monitoring method suitable for a multi-working-condition environment, which is used for solving the problem of small sample fault detection under different working conditions. According to the method, the prior knowledge of the working condition is embedded into the model-independent meta-learning framework, so that the learning ability is improved. A meta-learning framework is used to construct a plurality of small sample tasks, a convolutional neural network is used to carry out feature extraction on samples, an embedded vector representing working condition modes is constructed, a sample attention mechanism is introduced, and it is ensured that the samples containing more working condition mode information have higher weights in the process of generating the embedded vector. A plurality of condition layers are introduced into a basic classifier of meta learning, a characteristic linear modulation method is used, modulation parameters are generated by calculating embedded vectors, then the parameters of a basic classifier network are adjusted point by point, and working condition prior information is quoted.

The invention provides an intelligent DLP seamless large-screen dynamic adaptive adjustment system, and relates to the technical field of DLP large-screen dynamic adaptive adjustment, and the system comprises a precision sensing unit, a heterogeneous calculation module, a dynamic compensation execution mechanism and a self-diagnosis subsystem. Optical, mechanical and environmental data are collected in real time through a backside illuminated CMOS sensor array, a dual-wavelength infrared photoelectric encoder and a distributed temperature sensor which are coaxially mounted; using an edge detection-optical flow fusion processor to identify the rainbow pattern, and combining with a time frequency feature extractor to quantify the stroboscopic intensity perceived by the human eyes; dynamic adaptive adjustment is realized through color wheel harmonic drive, LED nonlinear modulation and DMD time sequence compensation. The system integrates fault mode matching and a multi-objective optimization algorithm, the problems of rainbow lines, stroboscopic lag, chromatic aberration deviation and environmental interference of a traditional DLP system are effectively solved, and the display consistency and the user experience are remarkably improved.

A method (100) for determining a power dissipation value of an electronic power circuit during an electrical period of a modulated control signal is disclosed, comprising: determining a linear mean switching energy value (110) of the electronic power circuit based on a modulated control signal with linear modulation; determining a nonlinear mean switching energy value (120) of the electronic power circuit based on a modulated control signal with nonlinear modulation, in particular overmodulation; determining a scaling factor value (130) based on the linear mean switching energy value and the nonlinear mean switching energy value; and determining the power dissipation value (140) based on the linear mean switching energy value and the scaling factor value.Furthermore, a computing unit designed and equipped to execute the procedure (100) is disclosed.

The application discloses a panoramic image depth estimation method combining spherical correction and semi-supervised learning, innovatively designs a spherical correction (SR) mechanism based on spherical coordinate Fourier coding and feature linear modulation (FiLM), a lightweight plug-and-play PanoAdapter adaptive module, a teacher-student semi-supervised cross-domain knowledge transfer framework and a joint optimization strategy fusing pseudo-label distillation and consistency constraint, realizes apparent correction of equidistant cylindrical projection (ERP) nonlinear spherical distortion, alleviates the contradiction between panoramic labeling data scarcity and perspective model cross-domain migration difficulty, and improves the geometric consistency and generalization ability of panoramic depth estimation in diversified real scenes.

This invention discloses a method for preparing epitaxial stress-controlled polarized metals, belonging to the field of functional oxide thin film preparation. The method includes: performing a special high-temperature annealing pretreatment on a YAlO3(111) substrate; calibrating the pulsed laser deposition rate and using a moving mask technique to prepare a wedge-shaped thin film with continuously varying thickness; and precisely controlling key process parameter windows such as growth temperature, laser energy density, oxygen partial pressure, and the distance between the target and the substrate. This invention obtains an ideal nucleation template by optimizing the substrate pretreatment process, achieves linear modulation of the thickness gradient by precisely controlling the matching of the mask moving speed and deposition rate, and obtains a high-quality polarized metal thin film with a room temperature resistivity as low as 173 μΩ·cm and stability across the entire temperature range by systematically optimizing key process parameters. This method has the advantages of high repeatability, high control precision, and wide applicability, and can be extended to the preparation of other perovskite oxide thin films, showing broad application prospects in the field of polarized electronic devices.

A system and method are provided for emulating an echo signal reflected from a diffuse target, having an indeterminate shape and range in a radar environment, in response to a frequency-modulated continuous-wave (FMCW) radar signal transmitted by a radar under test. The method includes receiving the FMCW radar signal from the radar under test, the FMCW radar signal having radar signal frequencies linearly modulated between a first frequency and a second frequency; generating a bandlimited noise-like signal having frequencies within predetermined frequency limits, and a spectral shape such that amplitudes of the noise-like signal vary in a predetermined manner with respect to the frequencies; mixing the noise-like signal with the received FMCW radar signal to provide an emulated echo signal reflected from the diffuse target; and transmitting the emulated echo signal of the diffuse target to the radar under test.

The invention discloses a liquid carbon dioxide phase change refrigeration system and method based on dynamic gas displacement adjustment, and relates to the technical field of refrigeration control and thermotechnical process automation, and the method comprises the following steps: S1, collecting temperature, pressure, cooling capacity and power data, and constructing an operation state vector; s2, setting the opening degree of an exhaust valve and the liquid injection rate as control variables, superposing periodic disturbance and nonlinear modulation signals, and constructing a disturbance input sequence; s3, fusing the disturbance input and the target response signal, and inputting the disturbance input and the target response signal into a control channel filter to generate a channel response signal; s4, estimating a disturbance response value through a generalized state filter; s5, constructing a nonlinear control law, and outputting a basic control quantity; s6, a regulation factor is generated according to the cooling capacity and the temperature change rate, and a control quantity is output; and S7, controlling the execution unit and feeding back the state to form a closed-loop process. According to the invention, the response speed and the temperature control precision of exhaust and liquid injection adjustment are improved.

The invention discloses a method, a device, a medium and a system for pulse-by-pulse rapid identification of an in-pulse linear frequency modulation signal, and belongs to the field of signal processing, and the method comprises the following steps: processing an intermediate frequency data stream of an input signal, and outputting frame data containing instantaneous phase, frequency, amplitude and azimuth information; collecting information of similar frame data, and performing signal parameter measurement to obtain parameter measurement information; obtaining intra-pulse linear modulation information of the signal pulse by using phase and frequency information of the frame data; and finally, gathering parameter measurement information and signal intra-pulse modulation information to form a PDW (pulse width modulation) so as to realize simultaneous processing of signal parameter measurement and signal intra-pulse feature extraction, thereby having the capability of identifying intra-pulse linear frequency modulation signals pulse by pulse. The method provided by the invention has a pulse-by-pulse intra-pulse linear frequency modulation characteristic identification capability, and can improve the signal sorting and identification capability.