93 results about "Nonlinear parameters" patented technology

The invention provides an ultrasonic nonlinear static parameter monitoring method for creep damage of a high-temperature alloy component, and particularly relates to the technical field of material monitoring. The method comprises the following steps: S1, arranging an ultrasonic probe; s2, determining the emission frequency of the excitation end; s3, respectively calculating an incident angle and an emergent angle of the signal; s4, exciting fundamental frequency ultrasonic waves; s5, receiving the signal and uploading the collected signal to a cloud processing system; s6, carrying out fast Fourier transform and calculating a nonlinear parameter of a static component; s7, establishing a linear relation with creep time, and constructing a creep damage linear quantitative model; s8, calculating a static component nonlinear parameter of the healthy sample; and S9, completing quantitative analysis of the damage by using nonlinear parameters. The method solves the problems that a traditional nonlinear ultrasonic method depends on second harmonic nonlinear parameters, phase velocity matching conditions in the middle and later periods are seriously damaged, response shows a nonlinear trend, unique creep time cannot be determined according to the parameters, and then the unique damage state cannot be determined.

The invention belongs to the technical field of crossing of high polymer materials and artificial intelligence, and discloses a method for optimizing the proportion of a nano-composite flame-retardant master batch in engineering plastic based on machine learning. The method is used for solving the problems that a traditional experience trial and error method is low in efficiency in multi-target performance collaborative optimization, high-dimensional nonlinear parameter space search is difficult, and microscopic coupling effect modeling is missing. According to the method, a multi-dimensional input feature set containing material composition and process parameters is constructed, six key performance indexes are combined to form training data, a mixed model formed by cascading a multi-layer perceptron and Gaussian process regression is trained, an improved non-dominated sorting genetic algorithm (NSGA-II) is adopted for multi-target global optimization, and an optimal ratio meeting preset constraints is obtained. The method is an industrial internet technology system service, and solves the technical problem that multi-target performance is difficult to collaboratively optimize due to the fact that a traditional experience trial-and-error method cannot perform modeling and searching on a high-dimensional nonlinear parameter space of a nano-composite flame-retardant system.

Aspects relate to signaling relating to a non-linearity model for power amplifier circuitry of a transmitting device. The power amplifier circuitry may apply digital pre-distortion (DPD) to a signal prior to amplification and transmission of the signal. A receiving device may apply digital post-distortion (DPoD) to a signal received from the transmitting device where the DPoD is based on the non-linearity model. The transmitting device may send to the receiving device non-linearity parameters for the non-linearity model.

The invention relates to a direct current furnace machine-furnace coordination system dynamic modeling method suitable for a wet condition. Based on the law of mass conservation and energy conservation, a lumped parameter method is adopted to construct a dynamic model comprising a coal pulverizing system, a coal economizer-water wall system, a water storage tank system, a superheater system and a steam turbine system; identifying parameters are optimized step by step by only utilizing unit variable load dynamic operation data and combining with the mechanism constraint that the heat absorption capacity of a working medium is monotonically increased along with the coal quantity as fired: static parameters are determined through dynamic data regression, nonlinear parameters are optimized based on a preset water-cooled wall outlet flow and dryness function structure, and the heat absorption capacity of the working medium is calculated. And finally, identifying dynamic parameters step by step by adopting an immune genetic algorithm. The dynamic characteristics and the physical consistency of the established model are verified through open-loop simulation, and the technical problems that dynamic description of the water level of the water storage tank is missing and the modeling precision is low under the wet working condition are solved.

The invention discloses a sine frequency modulation harmonic error compensation method based on Bessel function modulation characteristics, and relates to the technical field of sine frequency modulation nonlinear parameter compensation and high-precision measurement of target absolute distance based on multi-wavelength interference. The problem that the constant phase demodulation precision is insufficient due to the fact that carrier harmonic waves, accompanying amplitude modulation and modulation depth errors cannot be effectively suppressed due to laser modulation nonlinearity in existing sine frequency modulation distance measurement is solved. According to the method, after sine frequency modulation interference signals are collected, high-pass filtering is carried out to remove low-frequency components, Hilbert transform is carried out to remove envelope suppression associated amplitude modulation, window function frequency mixing is carried out to extract modulation depth, a matched carrier containing second harmonics is constructed, and frequency modulation harmonic parameter optimization is achieved through baseband amplitude maximization. And finally, carrying out orthogonal demodulation on the compensated interference signal to obtain a high-precision constant phase. The method is suitable for high-precision multi-wavelength interference ranging, precision displacement measurement and optical metering systems.

The invention provides a gap nonlinear control surface flutter wind tunnel test system and method based on steering engine excitation. The system comprises a wind tunnel test section, a test object and a parameter-adjustable excitation mechanism outside a wind tunnel field, wherein the parameter-adjustable excitation mechanism is composed of a transverse clamping mechanism, a longitudinal supporting mechanism, an excitation system and an angle sensor. The excitation system comprises a steering engine, a steering engine rocker arm and a connecting rod, one end of a spring rod is fixed to the longitudinal supporting mechanism, and the other end is in clearance fit with the connecting rod. By adjusting the effective length of the spring rod, the fit clearance and the excitation of the steering engine, the clearance nonlinear rigidity applied to the test control surface can be changed. In a wind tunnel test, an angle sensor is used for collecting rudder shaft rotation angular displacement response in real time, excitation-response characteristic testing before and after flutter occurs is achieved, and the influence rule of gap nonlinear parameters on rudder surface dynamic characteristics is effectively studied. The test principle is simple, and a new way is provided for excitation-response characteristic measurement of the full-motion control surface under different gap nonlinear rigidities.

The invention discloses a composite material storage life prediction method based on variable transformation and a genetic algorithm, and relates to the technical field of composite material performance evaluation and life prediction, and the method comprises the steps: obtaining performance degradation data at different temperatures through an accelerated aging test, and building a semi-empirical performance degradation model; specific variable transformation is introduced, a nonlinear optimization problem is converted into a linear regression problem, partial model parameters are rapidly solved by adopting a least square method, and meanwhile, key nonlinear parameters are globally optimized by using a genetic algorithm, so that the defect that a traditional method is easy to fall into local optimum is overcome. And establishing a temperature-service life relationship by combining with an archenius model, and realizing storage life prediction at normal temperature. The method also integrates sensitivity analysis and uncertainty quantification functions, and provides reliability evaluation for a prediction result. The method fully considers the influence of the environment temperature, meets the requirement of efficient prediction, and improves the precision and stability of life prediction.

The invention discloses a nano-scale displacement real-time compensation measurement method and system based on double-frequency laser interference, and belongs to the technical field of precision measurement. In order to solve the problems that three error sources of environmental drift, periodic nonlinear error and dynamic vibration are mutually coupled and have high real-time requirements in dual-frequency laser interference measurement, a multi-source error unified state space model including measured displacement, an air refractive index parameter, a nonlinear error parameter and a vibration disturbance quantity is constructed. A high-dimensional state vector is divided into a displacement-refractive index group and a nonlinear parameter group by adopting an extended Kalman filter of a grouping updating strategy, the displacement-refractive index group and the nonlinear parameter group are alternately updated in an assembly line parallel mode, nonlinear parameters are identified in real time in combination with an online recursive least square algorithm, and the state of the filter is corrected through a state coupling injection mechanism. Real-time compensation with the end-to-end delay smaller than 80 microseconds is achieved, the displacement measurement residual error is controlled within + / -0.3 nm under the composite disturbance condition, and the method is suitable for precise assembly of intelligent glasses optical assemblies.

This model parameter estimation device comprises a state quantity calculator to calculate state quantities indicating a state of a target system with respect to a measured value of an input on the basis of a state equation obtained by assigning values to nonlinear parameters for a model that represents the target system using the nonlinear parameters and linear parameters, and time-series data of the input and an output of the target system, a linear parameter estimator to estimate the linear parameters that minimize an error between the measured value of the output and an estimated value of the output calculated on the basis of the model, the state quantities, and the measured value of the input, and a nonlinear parameter updater to repeatedly update the values of the nonlinear parameters so as to make the minimized error to be small until a convergence condition is satisfied.

This invention belongs to the field of ultrasound imaging technology, specifically relating to an ultrasound nonlinear parameter imaging method, system, medium, and program product. The method includes: calculating a fundamental wave signal and harmonic signals based on ultrasound echo RF signals; extracting the amplitudes of the fundamental wave signal and the harmonic signals, and calculating the fundamental wave amplitude ratio and harmonic amplitude ratio; calculating an initial value of the nonlinear coefficient based on the ratio between the fundamental wave amplitude ratio and the harmonic amplitude ratio, and estimating the range of values ​​for the nonlinear coefficient using Newton's iteration method; and generating an ultrasound image based on the range of values ​​for the nonlinear coefficient. In the process of ultrasound nonlinear parameter imaging, a method for solving the nonlinear coefficient using Newton's iteration method is further disclosed, thereby expanding the dynamic range of the estimated nonlinear coefficient values, resulting in a clearer distinction between normal tissue and lesion tissue in the obtained ultrasound image, and higher sensitivity.

The invention relates to a method for influence of dislocation dipole defects in an aluminum matrix on acoustic parameters, belongs to the technical field of discrete solution, and provides a novel molecular dynamics simulation method for researching ultrasonic sound velocity, sound attenuation and acoustic nonlinear parameter change on the basis of two dislocation dipole structures. The method specifically comprises the following steps: controlling the type and the number of dislocation dipoles in an aluminum matrix, carrying out atomic scale acoustic simulation on dislocation dipole models of different types and numbers by adopting a phase inversion technology, extracting sound velocity by adopting a cross correlation method, extracting sound attenuation by adopting a Hilbert transformation method and extracting acoustic nonlinear parameters by adopting an FFT method aiming at four-phase signals; and precise extraction of acoustic parameters is realized. And determining the contribution of the dislocation defect to the acoustic parameters based on the relationship fitting of the three acoustic parameters and the dislocation defect, thereby realizing the prediction from the acoustic parameters to defect characteristics.

The application relates to the technical field of wireless communication, and discloses a digital predistortion method for improving the linearity of a power amplifier in a phased array system, which comprises the following steps: step one, acquiring nonlinear parameters of a power amplifier under dynamic load in real time, wherein the nonlinear parameters comprise input signal amplitude and phase characteristics, temperature parameters and quantum tunneling current parameters; step two, generating a predistortion compensation signal based on the nonlinear parameters, wherein the predistortion compensation signal comprises a quantum phase compensation term and a dynamic phase change compensation term; and step three, superimposing the predistortion compensation signal to an original input signal to generate a predistortion modulation signal. The application improves the linearity of the power amplifier by introducing the quantum phase compensation term and the dynamic phase change compensation term, and improves the accuracy of predistortion compensation by accurately acquiring the nonlinear parameters in real time under the dynamic load environment.

The application discloses a bearing stress state measurement method based on a resonance attenuation method and related devices, and the bearing-main shaft system is loaded in the mode of electromagnetic loading. The resonance attenuation method in the nonlinear parameter identification method is used to obtain an attenuation response curve, and the instantaneous frequency and envelope amplitude are obtained based on a transient time-frequency signal analysis method, and then the main curve is identified from the measured bearing-main shaft system. A quasi-static model of the bearing is established to obtain the mapping relationship between the bearing stress state and the nonlinear non-time-varying stiffness, and the external loading state of the bearing is effectively and accurately detected through multiple tests on the nonlinear stiffness of the bearing system in the actual operation process. The application is suitable for multiple types of assembled angular contact ball bearings and is suitable for accurate measurement of the bearing stress state.

The present invention discloses a method for identifying nonlinear parameters of structural clearances. First, a mathematical model of the structural clearance nonlinear system is established; then, the frequency response function of the system under sinusoidal sweep excitation is obtained through the input-output response of the system; in the frequency response function, a pair of symmetric displacement points exist at any displacement response amplitude to define the same displacement frequency response function. By defining the real and imaginary parts of the displacement frequency response function through the symmetric displacement FRF points at each given displacement response amplitude, the natural frequency of the system related to the displacement response amplitude can be obtained; then, the expression of the nonlinear equivalent stiffness of the system is extracted through the simulation analysis of the model, and the equivalent stiffness curve of the system is further obtained through the model simulation data; finally, based on the particle swarm algorithm, the clearance characteristic parameters are obtained by curve fitting according to the equivalent stiffness expression obtained by integration and the equivalent stiffness curve obtained by model simulation; the present invention can identify the clearance nonlinear parameters more quickly and accurately globally.

The method for monitoring the resonant capacitor state of the medium-voltage direct-current LLC resonant converter comprises the following steps: closing the switch tube S 11 ~S 41 of the full-bridge at the initial moment when the LLC resonant converter is stopped, then turning on the switch tube S 31 and S 41 after the closing process lasts for 500 ns, forming a discharge loop of a resonant cavity independent of the latter stage, then collecting the time sequence data of the resonant current in the resonant cavity, and estimating the resonant capacitor by using a nonlinear parameter identification algorithm, wherein the estimation is sequentially performed by encoding, initializing the population, calculating the individual fitness, selecting the cross variation evolution, and iterative optimization, finally searching for the optimal resonant current estimation value, and calculating the resonant capacitor estimation value based on the corresponding resonant frequency and resonant inductance. The present application estimates the resonant capacitor value based on the discharge curve of the limited sampling data, has low cost and high reliability, and the present application estimates the parameters by using the nonlinear parameter identification algorithm, and has high estimation accuracy.

This invention discloses a pre-equalization compensation method for a terminal in a TDD-OFDM direct conversion system with known transmitter IQI and nonlinear parameters. The method includes: the base station cyclically sending P different training sequences to the terminal; the terminal using a sliding window least squares-based channel state information tracking algorithm to track and estimate the channel state information, where δ is a threshold representing the correlation of the channel within adjacent symbol periods; and pre-equalization compensation performed directly at the terminal. Using the pre-equalization compensation algorithm, a modified data sequence can be obtained and sent to the base station. This invention considers three factors in wireless communication systems: I-path and Q-path imbalance caused by the non-ideal nature of analog components in RF transceivers, power amplifier nonlinearity, and multipath channels. It enables distributed processing within the cell, effectively reducing the demodulation burden on the base station and has wider applicability than traditional compensation methods.

The present invention relates to the technical field of electro-hydraulic servo control. Provided is a backstepping sliding mode control method for a heavy-duty forklift pump-controlled lifting system and based on a non-linear observer. In the method, a non-linear robust sliding mode position servo controller with disturbance compensation is designed on the basis of the idea of a backstepping method. Aiming at the problem of the difficulty of controlling the precision of a heavy-duty forklift pump-controlled lifting position, the present invention realizes precise load observation, takes non-linearity and parameter uncertainty into consideration, and uses a sliding mode term to address non-linearity and uncertainty, thereby reducing the effects of abrupt load changes, external disturbance, and unmodeled dynamics on control precision, and achieving a high-precision tracking performance.

The invention belongs to the technical field of spectral analysis, and discloses a plant cell wall microfibril orientation polarization Raman spectrum measurement method, which comprises: 1, carrying out polarization Raman spectrum data acquisition on a sample to be measured; step 2, acquiring required data based on a data acquisition result of the polarization Raman spectrum; 3, performing nonlinear parameter fitting on the required data, obtaining an optimal parameter combination and a corresponding coefficient through a minimum error function, and performing forced symmetry post-processing on the optimal Raman tensor matrix; step 4, calculating a microfilament angle of a corresponding angle according to the symmetrical tensor parameter; in the fourth step, based on the symmetrical tensor matrix, the angle needed for rotating the tensor matrix to the main axis direction is calculated; and carrying out normalization processing on the calculated angle value. The technical problems that in the prior art, due to the fact that a nonlinear fitting algorithm is complex and prone to being affected by noise and experimental errors, the fitting convergence effect is poor, and the stability and reliability of a detection result are insufficient are solved.

The application is a method for the influence of dislocation dipole defects in aluminum matrix on acoustic parameters, belonging to the technical field of discrete solution, and provides a new molecular dynamics simulation method for researching the changes of ultrasonic velocity, acoustic attenuation and acoustic nonlinear parameters based on two dislocation dipole structures, specifically, the types and quantities of dislocation dipoles in the aluminum matrix are controlled, the atomic scale acoustic simulation is carried out on the dislocation dipole models of different types and quantities by using the phase inversion technology, the cross correlation method is used to extract the sound velocity, the Hilbert transform method is used to extract the sound attenuation, and the FFT method is used to extract the acoustic nonlinear parameters for the four-phase signals, so as to realize the precise extraction of acoustic parameters. Based on the fitting relationship between the three acoustic parameters and the dislocation defects, the contribution of the dislocation defects to the acoustic parameters is determined, and the prediction from the acoustic parameters to the defect characteristics is realized.

This invention discloses an adaptive control system for a coal mining machine cutting transmission system under complex working conditions. The system uses an extended state observer in the adaptive torque compensation controller to track the state variables of the cutting transmission system, and estimates in real time disturbances such as nonlinearity and time-varying parameters. The real-time effect of the total disturbance is compensated into the feedforward compensation disturbance term in the actual control quantity. A BP network adaptively adjusts the parameters of the second-order active disturbance rejection torque controller, and an adaptive convolutional neural network fuzzy module adaptively adjusts the output compensation of the active disturbance rejection torque compensation controller to obtain expert control rules that satisfy complex impact conditions. Nonlinear state error feedback, combined with the adjustment amount of the adaptive convolutional neural network fuzzy module, calculates the initial electromagnetic torque. After feedforward compensation, a compensated electromagnetic torque is generated, which is superimposed on the torque compensation amount generated by the PI controller. This achieves adaptive compensation control for suppressing the dynamic load of the system and effective suppression of the impact energy of the dynamic load on the cutting transmission system.

The application discloses a kind of metal material mechanics performance multi-parameter nondestructive evaluation method based on grating laser ultrasonic spectrum, the method utilizes high-energy pulsed laser beam to be irradiated on the surface of the metal material to be measured by micro-lens array and form periodic distribution transient grating, excite monochromatic ultrasonic Rayleigh wave of fixed wavelength in material interior, simultaneously, non-contact receive Rayleigh wave signal in the vicinity of the detection area by probe laser.The received Rayleigh wave signal is subjected to fast Fourier transform to obtain narrow-band spectrum, and the acoustic parameters such as sound velocity and acoustic nonlinear parameter can be calculated through the narrow-band spectrum.According to theoretical formula and experimental relationship calibration curve, the calibration relationship between the elastic modulus of metal material and sound velocity, hardness and acoustic nonlinear parameter, yield strength and acoustic nonlinear parameter, ultimate tensile strength and acoustic nonlinear parameter is established respectively, so as to realize the quantitative evaluation of the mechanical properties of metal material.

The invention discloses a mining subsidence prediction parameter solving method based on an improved center collision optimization algorithm, and belongs to the field of mine deformation monitoring data processing. Aiming at the defects that a basic center collision optimization algorithm is prone to premature convergence and insufficient in optimization precision when solving a mining subsidence parameter inversion problem, a Huber loss function is adopted to construct a fitness evaluation model to enhance the robust capability of the algorithm, and Cubic mapping is utilized to generate a random number to improve the stability of a search process, so that the method is suitable for the mining subsidence parameter inversion problem. And a self-adaptive elite-guided Cauchy variation mechanism is introduced to enhance the global exploration capability. According to the method, firstly, a probability integral method parameter inversion problem is constructed into an optimization model, and a population is initialized; performing double-space collaborative search in an original space and a decorrelation space constructed based on principal component analysis, and iteratively updating a population in combination with a dynamic space allocation strategy; and finally outputting an optimal parameter solution. According to the method, the convergence precision, stability and robustness of the algorithm in complex nonlinear parameter inversion are effectively improved.

The embodiment of the invention discloses a multi-center waste recovery scheduling method and device based on a mixed sine and cosine algorithm. According to one specific embodiment, the method comprises the steps that in response to parameter initialization completion, coding and decoding are carried out according to initialized parameters, an initial recycling line for a recycling center is generated, the initial recycling line is a one-way transport vehicle running line containing at least one to-be-recycled point, and the to-be-recycled point is a node to be subjected to waste recycling; constructing an initial solution set according to the initial recovery line and a chaotic mapping technology; processing is carried out according to the initial solution set and a hybrid evolution mechanism, a candidate solution set is obtained, and the hybrid evolution mechanism comprises a nonlinear parameter adjustment feature, a co-evolution feature and a random disturbance feature; and performing solution optimization on the candidate solution set through discrete domain search to obtain a final recovery line. The recovery scheduling algorithm of the embodiment has good performance.

The application discloses a point cloud rendering method and system, and relates to the technical field of computer graphics, and comprises the following steps: acquiring point cloud data of a detected object; S2, dynamically dividing a three-dimensional space into multiple rendering levels based on the real-time distance from the acquired point cloud data to a current observation point; based on each rendering level, respectively establishing a nonlinear smooth continuous function mapping relationship between rendering sampling probability and the observation distance of a rendering point radius, and respectively inputting a preset representative observation distance at each layer to obtain the rendering parameters of each layer; and applying the corresponding rendering parameters of the point cloud of different rendering levels to perform differentiated rendering operations. Advantageous effects: the hierarchical mechanism provides a structured framework for subsequent nonlinear parameter mapping, so that the adjustment of the rendering parameters can be based on an ordered spatial division closely related to visual perception, which is a prerequisite for the intellectualization of the whole method.

The present application relates to the technical field of unmanned aerial vehicles, and specifically relates to a method for simulating flight performance of unmanned aerial vehicles in multiple scenarios and evaluating data, comprising the following steps: firstly, a three-dimensional physical model of the unmanned aerial vehicle is established using computer-aided design, and aerodynamic and structural mechanics simulations are performed through computational fluid dynamics and finite element analysis; secondly, real-time meteorological data and terrain information are fused to simulate the flight performance of the unmanned aerial vehicle in complex flight environments; the simulation process is accelerated using high-performance computing, and machine learning algorithms are applied to optimize nonlinear parameters in the simulation model; finally, the actual flight data of the unmanned aerial vehicle is used for calibration, sensor data is processed through techniques such as Kalman filtering, the lift coefficient and drag coefficient are back-calculated, and a closed-loop optimization system is formed; this method can effectively improve simulation accuracy and adaptability in multiple scenarios, reduce the number of actual flight tests, reduce research and development costs and risks, and is suitable for performance evaluation and optimization of various unmanned aerial vehicles.

The invention provides a camera distortion correction method based on a spectrum correction iteration LM algorithm, and belongs to the technical field of distortion correction. The invention provides a novel camera distortion correction method based on a spectrum correction iteration LM algorithm, and aims to overcome the defect that a correction result is directly influenced due to the fact that a nonlinear parameter estimation value is not accurate in a nonlinear distortion correction model resolving process in the prior art. Specifically, a nonlinear function model of a camera imaging system is constructed according to a distortion correction model, and an observation value vector is acquired; constructing an error equation of the nonlinear least square problem by using a Taylor formula, and constructing a to-be-estimated parameter iterative formula of the nonlinear least square problem according to a spectrum correction iterative method; respectively calculating a spectrum correction estimated value, calculating a ratio of an actual decline amount to an estimated decline amount, and updating a parameter estimated value of secondary iteration; and setting a judgment threshold, and outputting an optimal estimated value of the parameter when a convergence condition is met.

The invention provides a nonlinear parameter calibration method and device, electronic equipment and a storage medium, and the method comprises the steps: dividing a nonlinear working range into a plurality of continuous sub-intervals, determining a target sub-interval to which an input parameter belongs according to the input parameter; and obtaining a group calibration parameter corresponding to the target subinterval, calculating a basic output value in combination with the input parameter, and correcting the basic output value by using a compensation parameter corresponding to the individual object to obtain a final calibration output. In the prior art, because complete calibration parameters are independently stored for each individual, the storage cost is linearly increased along with the number of the individuals, a table look-up method is easy to generate a step error, and the interval boundary is discontinuous to cause system oscillation; or global average parameter calibration is adopted to ignore individual differences, calibration precision is sacrificed, and the high-precision application requirement cannot be met.

This invention discloses a safety assessment system and method for pressure-bearing components based on nonlinear ultrasound, belonging to the field of component safety assessment technology. The invention controls a robotic arm to drive an automatic probe to acquire nonlinear signals; establishes a mapping benchmark library and calibrates the background nonlinear threshold; divides the detection area of ​​the pressure-bearing component under test into a grid, and acquires the original field detection signal corresponding to each grid unit; removes nonlinear interference from each original field detection signal and calculates effective nonlinear parameters; based on the effective nonlinear parameters and the background nonlinear threshold, filters out abnormal candidate regions; for all abnormal candidate regions, inversely calculates the equivalent emission source parameters of the abnormal nonlinear signals; based on the three-dimensional spatial coordinates of the equivalent emission source parameters, determines the abnormal location region and outputs the location characteristics of the abnormal location region; trains a safety assessment model, inputs the location characteristics into the safety assessment model, and calculates the safety assessment result of the pressure-bearing component.

Aspects relate to signaling relating to a non-linearity model for power amplifier circuitry of a transmitting device. The power amplifier circuitry may apply digital pre-distortion (DPD) to a signal prior to amplification and transmission of the signal. A receiving device may apply digital post-distortion (DPoD) to a signal received from the transmitting device where the DPoD is based on the non-linearity model. The transmitting device may send to the receiving device non-linearity parameters for the non-linearity model.