49 results about "Guess value" patented technology

The invention provides a block balancing method for an orthogonal frequency division multiplexing (OFDM) system on the condition of a fast time variant channel. The method comprises the following: at a sending terminal, a bit signal subjected to cyclic redundancy codification is subjected to channel codification, interlacement, symbol map, serial / parallel conversion and IFFT conversion to be converted to a time domain signal; the time domain signal which is subjected to serial / parallel conversion and is inserted with a cyclic prefix is sent to a radio channel; at a receiving terminal, the signal is received by a traditional first-order frequency domain equalizer, and the signal guess value is checked after the signal is subject to serial / parallel conversion, demap, deinterlacement and signal path decoding; if the check is correct, the signal is outputted; if the check is not correct, the block balancing process is performed, during which, firstly, a time domain OFDM sending signal is restructured; secondly, the received time domain OFDM symbol is divided into a plurality of equilong signal receiving subblocks, the loop restructuring and the interference removing processes are performed by a time domain OFDM restructured signal; and finally, each subblock is subjected to frequency domain balance, the balanced guess values of sub blocks are merged to obtain the block balance output serving as the input of the serial / parallel conversion.

The invention provides a method for estimating a MIMO-SCFDE system channel based on an orthogonality training sequence, comprising the following: (1) at a sending terminal, firstly, the orthogonality training sequence is designed according to the number of sending antennas; secondly, the designed training sequence is sent out by each sending antenna according to the designed sequence; (2) the received signal is stored temporarily at each receiving antenna, after all the signals of the training sequence are received, the signals are converted to the frequency domain first; and linear system of equations is solved to obtain the state information on a subchannel in each frequency domain corresponding to the sending antenna and the receiving antenna between each receiving antenna and sending antenna according to the subchannel in each frequency domain; and (3) the received channel state information corresponding to the receiving antenna and the sending antenna is transferred to a time domain to added a window to the time domain channel to remove the influence of noise on the channel guess value, and is transferred to a frequency domain to obtain the channel guess value. The method is suitable to the characteristic of the MIMO-SCFDE system, has low complexity and improves the estimating accuracy of the channel.

The invention relates to an elevator non-load traction capacity detecting method, belonging to the elevator detecting technical field. The method comprises the steps as follows: firstly, a carriage and a counter-weight side wire cable are fixed, thereby preventing relative displacement between wire cables at the two sides of a traction sheave; secondly, an elevator tractor brake is released so that a reducer gear is in free status and the value of a sensor fixed on a counter-weight side wire cable is read; the traction sheave rotates along clockwise direction until the relative sliding between the traction sheave and a traction cable occurs, and then the valve on a counter-weight side pressure sensor is read; and finally, a traction sheave rotates along counter clockwise direction until the relative sliding occurs between the clockwise direction and the traction cable and the value on the counter-weight side pressure sensor is recorded. The detected data are treated so as to finally obtain maximum carriage static load of an elevator tractor system. The method has the advantage that the practically detected value is used in computing formula to the maximum and the theoretical value or the guess value is reduced as much as possible, thereby obtaining a more precise detected value.

The invention relates to a topographic surveying method, the method comprises: full polarizing synthetic aperture radar compound image by a single path and calculating to obtain a polarization position angle offset value of each earth's surface unit in the irradiation area adopting circular polarization algorithm; calculating an incidence angle and the resolution of each earth's surface unit by system parameters; calculating the grade guess value of each earth's surface unit by compensation Lambert algorithm; calculating the absolute elevation value of each earth's surface unit by the complete multiple gridding algorithm. A moderate accuracy grade and digital height model can be rapidly obtained by the single path full polarization synthetic aperture radar slant distance compound image data. The method of the invention is characterized in that, the limitation for acquiring radar data is less, the dependence on the exterior data is less, the automatization degree is high and the computational efficiency of the integral process flow is high, thereby the terrain is visible and the application field has larger application value.

The invention relates to a carrier wave aided tracking method used in a high-dynamic double frequency GPS, which is as follows: a carrier wave phase lock tracking loop and a pseucode delay locked loop are executed for regulating carrier wave NCO and C / A code NCO of local L1 frequency points to generate guess values deferred by an L1 carrier wave phase and a C / A code; a half codeless method is used for tracking L1-P (Y) signals by using a pseucode delay locked loop (DLL); an L2-P code generator is initialized; according to the guess value of an L1 loop carrier wave phase, reference oscillator frequency offset dissolved by a positioning resolving module, phase demodulation difference of an L2 carrier wave phase lock tracking loop (PLL), the carrier wave phase value of L2 frequency points is jointly estimated; a carrier wave NCO is regulated, and the local L2 signal carrier wave is recurred; the half codeless method is used for precisely tracking input L2 signals. The L2-P carrier wave tracking using the method can obtain higher tracking accuracy, lower tracking threshold and more stable loop in high-dynamic environment.

The invention discloses a recognition system and a recognition method for a verification code of a mobile platform. The recognition system comprises a mobile platform verification code intercepting module, a verification code de-noising module, a verification code binaryzation module, a verification code recognition core module and a self-learning module, wherein the mobile platform verification code intercepting module is used for intercepting an original verification code image from the mobile platform to a verification code recognition system; the verification code de-noising module is used for de-noising the original verification code image through a median filtering algorithm so as to acquire a secondary verification code image; the verification code binary module is used for converting the secondary verification code image into a black and white bicolor image and cutting into a plurality of verification code sub-blocks; the verification code recognition core module is used for recognizing the well-cut verification code sub-blocks, acquiring a character string represented by the verification code and calculating an equation value represented by the character string; and the self-learning module is used for speculatively trying the possible optimizing character string and automatically recording a speculative value into a self-learning database if the speculative value correctly passes. The recognition system provided by the invention can be used for quickly and automatically recognizing the verification code contained in an interface supplied by the mobile platform and promoting the user experience.

The invention discloses a sea surface wind speed inversion method based on a cross polarization model and CMOD5N. The method comprises the steps of: according to the CP model and a C-2PO method, utilizing VV polarization and VH polarization SRA images to carry out inversion and obtain an initial wind speed U0 and an initial wind direction [phi]0 of a reconstruction resolution unit; determining wind field vectors (U, [phi]) according to the initial wind speed U0 and the initial wind direction [phi]0, using the wind field vectors (U, [phi]) as a first guess value, and utilizing a CMOD5N algorithm to gradually traverse and calculate normalized radar scattering cross sections NRCS of corresponding VV polarization in upper and lower limit ranges of the wind speed and the wind direction with the first guess value serving as a center; and finding out the wind speed and the wind direction which have the smallest differences with the normalized radar scattering cross sections NRCS of VV polarization SRA images, wherein the wind speed and the wind direction having the smallest differences are the wind field vectors obtained by inversion. According to the invention, the wind speed inversion precision of the existing C-2PO method is generally improved in different SAR image reconstruction resolution scale situations.

The present invention discloses a turboshaft engine self-adaptive model building method based on a modified Broyden algorithm to solve an equation set. The method comprises: matching a self-adaptive model with a real engine by forming and solving the equation set. A non-linear equation set is established according to a principle in which a model outputs a tracked real engine output and in combination with a coacting equation between engine parts, and the equation set is solved by using a modified Broyden algorithm, to acquire a part performance degradation parameter and a turboshaft engine part level model guess value. The modified Broyden algorithm is based on a Broyden quasi-newton method and is combined with a computation divergence determination and correction mechanism, so that computation accuracy and real-time performance are improved. The performance degradation parameter acquired by solving the equation set is introduced into a turboshaft engine part level model as an adjustable parameter, so that the model has a self-adaptive capability.

The invention discloses an anisotropy-based sea surface temperature forecasting method for a high-current area. The method comprises the following steps: (1) giving an initial guess value of a controlvariable omega (x, y); (2) T is set as a research variable, and TS is obtained from a 'time' t = 0 forward integral advection diffusion model to t = S; obtaining a diffusion coefficient a by using aparameterization method; (3) performing integral tangent on the linear adjoint model to obtain a gradient g (omega) of the target function J (omega); (4) minimizing an algorithm optimization control variable omega (x, y); (5) circulating the steps (2) to (4) until the control variable omega (x, y) enables the target function J (omega) to reach the minimum value, and outputting the TS at the moment; and (6) establishing an analysis field according to the TS obtained in the step (5), wherein the established analysis field provides an initial field for forecasting the sea surface temperature of the strong current area. Aiming at the characteristic of isotropy of original diffusion filtering, a method of adding an advection term to a diffusion equation and parameterizing a diffusion coefficient is adopted, and the influence of ocean current is added to the whole assimilation process, so that an assimilation result is closer to a true value.

The invention discloses a method selecting strong path, which selects a plurality of strong paths from the subdistrict according to channel impulse response (CIR) guess value of the subdistrict and a pre-set sets first threshold firstly; then the method selects a plurality of strong paths from adjacent subdistricts according to CIR guess value of each adjacent subdistrict and a pre-set sets second threshold; at last, when the total number of the selected plurality of strong paths is larger than upper limit Q of the number of the pre-set strong paths, Q strong paths are selected from the selected plurality of strong paths. When the invention is applied, selected path can be in line with the needs of multi-subdistrict joint channel guess value to the strong path, complexity of the multi-subdistrict joint channel guess value can be controlled in a certain range, and strong path selection with high accuracy is realized.

The invention discloses a J2 perturbation Lambert problem solving method based on a deep neural network and a targeting algorithm, and the method comprises the steps: obtaining initial speed values ofa start end according to start and tail end position vectors and flight time, carrying out the orbit recursion based on the obtained initial speed values of the start end, and obtaining a tail end position error under the interference of J2 perturbation; according to the tail end position error and starting and tail end positions and flight time in the initial condition, estimating an error of astarting end speed initial value by utilizing a deep neural network obtained by training, and correcting the obtained starting end speed initial value by taking the error as a correction value to obtain a corrected starting end speed initial guessing value; taking the obtained initial guessed value of the starting end speed as an initial value, and performing targeting correction on the initial guessed value of the starting end speed by utilizing a Newton iteration targeting algorithm based on differential approximation until the position precision of the tail end meets the requirement. According to the method, the problems that in the prior art, when the J2 perturbation Lambert problem is solved, the calculation efficiency is low, the convergence stability is insufficient, and the solvingeffect of the multi-circle Lambert problem is poor are solved.

The invention relates to a method for quantitatively detecting three-dimensional defects in a device. The method comprises the following steps of: 1) selecting K temperature sampling points on the measurement surface of a measured object, setting a defect geometric parameter vector P; 2) establishing a heat transfer model of the measured object according to the guess value of P, and employing thefinite element method to calculate and obtain a temperature departure ek of the K temperature sampling points, if the ek meets an iteration stop condition, finishing the iteration process, and takingthe guess value as a detection result of P, or else, entering the step 3); 3) establishing a fuzzy inference unit corresponding to the K temperature sampling points; 4) establishing a weighting comprehensive matrix of the fuzzy inference unit, and constructing a decentralized fuzzy inference module; and 5) performing decentralized fuzzy inference, and performing iteration correction of the guess value of the P according to the decentralized fuzzy inference result to replace the correction value as a guess value, and turning to the step 2). The method provided by the invention can quantitatively detecting the three-dimensional physical dimensions and depth information of the internal defects of the device to achieve the quantitative detection.

The invention discloses a side channel analysis method for rainbow signature. The method includes the following steps that: S1, N message-signature pairs, and N power consumption curves which are in one-to-one correspondence with the N message-signature pairs are generated, wherein N is a positive integer greater than 2000; S2, calculation formulas in the rainbow signature algorithm are obtained,and elements in GF(2k) are sequentially selected as the guess values of the keys in the calculation formulas, and the input values of the calculation formulas are acquired according to messages in each of the message-signature pairs, and operation is performed, output values are obtained; and S3, the N power consumption curves are analyzed based on N input values and N output values correspondingto each guess value, the keys in the calculation formulas are obtained. Correspondingly, the present invention also discloses a side channel analysis device for rainbow signature. With the method andthe device provided by the embodiment of the present invention adopted, the security problem of the rainbow signature can be found, and therefore, technical support can be provided for defense side channel attacks.

The invention discloses an equipment thermal stress field efficient detection method based on multi-parameter coupling, and the method comprises the following steps: S1, selecting N temperature sampling points on the surface of detected equipment, setting a guess value Pi of a thermal boundary condition P, wherein i is an iteration coefficient; S2, establishing a temperature / thermal stress semi-analytical solution model of the equipment according to the guess value Pi of the thermal boundary condition P; S3, establishing a constraint dispersion fuzzy reasoning model according to the temperature / thermal stress semi-analytical solution model of the equipment, and obtaining a constrained thermal boundary condition P and other to-be-inverted parameters; S4, according to the constrained thermal boundary condition P and other solved to-be-inverted parameters, reconstructing a temperature field mathematical model and a thermal stress field mathematical model of the equipment; and S5, calculating the thermal stress of the equipment according to the reconstructed mathematical models of the temperature field and the thermal stress field. The method optimizes the inversion algorithm, improves the calculation efficiency, and can achieve the real-time monitoring of the thermal stress of the equipment.

The inveniton provides a method for improving ocean forecasting precision based on analysis of four-dimensional set variation. The method comprises the following steps: respectively adding disturbance values to an initial field guess value and an external forced field to form a set sample, rewriting an evolution equation for analyzing the four-dimensional set variation according to the set sample, and expanding a disturbance quantity until recursion to an initial moment; when the initial field guess value is irrelevant to the external forced field statistics, obtaining two special background field error covariance matrixes respectively containing tangent linear evolution matrixes and corresponding adjoint matrix information; performing disturbance expansion near the initial field guess value to obtain a relationship between a state variable at any moment in the future and a tangent linear evolution matrix and a disturbance quantity, and constructing a target function after disturbance; solving the gradient of the disturbed target function to the disturbance quantity; and the obtained initial field guess value is the optimal initial field guess value until the gradient of the disturbed target function to the disturbance quantity infinitely approaches zero. According to the invention, the applicability of the four-dimensional set variation method is improved, and the prediction error is effectively reduced.

The invention discloses a design method of a spacecraft leveraging flight orbit. The design method comprises the following steps: determining a near-star-point speed calculation parameter of the spacecraft leveraging flight orbit; establishing a near star point velocity equation according to the calculation parameters and solving a velocity vector; determining a Hille sphere boundary state of the spacecraft by using a circular restrictive three-body dynamics model; establishing a mapping relation between a leveraging flight orbit boundary value constraint condition and an initial speed through an artificial neural network so as to obtain an artificial neural network model; using the artificial neural network model to complete the calculation of the initial speed of the three-body Lanbert problem of the spacecraft leveraging flight orbit; designing a leveraging flight orbit of the spacecraft according to the initial speed of the three-body Lanbert problem; the artificial neural network is adopted to solve the three-body Lanbert problem of the leveraging flight orbit, the problem that convergence is difficult due to the fact that the initial speed guess value is not accurate in a strong nonlinear system is solved, and when the initial speed is calculated, the calculation efficiency is high, and the precision is high.

The invention relates to a fast convergence ultra-short pulse waveform and phase reconstruction method, which comprises the following steps of: optimizing a pulse initial guess value, preprocessing multiple grids of a two-dimensional trace graph, and reconstructing a pulse waveform and a phase by using a ptychographic iterative algorithm. After the optimized pulse initial guess value is utilized and the two-dimensional trace graph is preprocessed, the reconstruction calculation time of the two-dimensional trace graph is greatly shortened, the rapid convergence of the waveform and phase reconstruction of the ultra-short pulse can be realized, the requirement of the single real-time measurement of the ultra-short pulse is met, the reconstruction speed and the accuracy are ensured, and the method also has good noise immunity and high resolution.

The invention discloses a parameter estimation method for a bioelectric impedance Cole equation, intelligent equipment and a storage medium. The method comprises the steps that according to amplitudevalues and phase values of potential differences measured under frequencies, real parts and imaginary parts of impedance values are calculated; according to the real parts and imaginary parts of the impedance values, an initial guess value and constraint range of each parameter are determined; according to the initial guess value and constraint range of each parameter, fitting parameters and fitting impedance values are determined; according to a threshold of an error sum of squares of the fitting impedance values and measurement values, an optimum fitting parameter value is determined. The parameter estimation method for the bioelectric impedance Cole equation, the intelligent equipment and the storage medium simultaneously use the real parts and imaginary parts of the impedance values, arithmetic solutions of an equation set are solved, the initial guess values and the constraint ranges are estimated to be used for NLLS fitting, and measures for avoiding noise risks are further adopted, the robustness is very good, the capacity of resisting disturbance is high, parameters of the Cole equation can still be fitted and estimated accurately under the serious situation of noise, thereby obtaining more accurate ECW and TBW values.

The invention relates to the technical field of aero-engine performance simulation, and provides a whole machine variable-dimension simulation performance simulation process control method. The method comprises the steps that relevant parameters of engine design points are obtained according to relevant parameters of the design points of a zero-dimensional engine model, and fan boundary conditions are obtained through calculation of the zero-dimensional engine model; based on the fan outlet static pressure initial guess value, fan performance parameters and zero-dimensional engine model performance parameters are obtained; whether the fan performance parameters and the zero-dimensional engine performance parameters meet the balance relation or not is judged, if not, the following steps are continued, Newton-Raphson algorithm iteration is completed, and engine variable-dimension simulation model performance parameters are obtained. According to the method, automatic calling of zero-dimensional and three-dimensional programs and automatic mutual reading of parameters are realized, complexity and low efficiency of manual calling of the model and input of parameters are avoided, control simulation precision is guaranteed, and calculation burden of a variable-dimension simulation model is remarkably reduced.

The invention relates to an aircraft reentry trajectory optimization method based on an intelligent parallel Gaussian pseudo-spectral method, which adopts an improved differential evolution algorithmto calculate a guessed value, improves a traditional adaptive pseudo-spectral method, performs discretization through the Gaussian pseudo-spectral method, and adopts an improved sparse differential sequence quadratic programming algorithm to perform trajectory optimization calculation. And meanwhile, a new trajectory optimization calculation construction method is combined, so that the solving speed of reentry trajectory optimization is increased through parallel calculation. According to the method, the triangular Gaussian variation differential evolution algorithm is combined, and the combined weight is added to adapt to the diversity of better individuals, general individuals and current individuals, so that premature convergence is avoided.

A specific signal random noise filtering method is provided; a conventional method comprises the following steps: assuming an observed value Am is the true value Zm according to the observed value Am; using a mapping relation f(m-n) to obtain a guess value Tm-n=Am+f(m-n) with certain precision; because random noise is stacked on the observed value Am, so the guess value Tm-n may have large deviations, or larger and larger deviations can be accumulated with the increasing of guess points. The filtering algorithm uses the basic principle that the observed value Am is assumed to be equal to Zm, so the difference value between a series of guess values obtained according to the observed value Am and the observed value should be equal to the random noise rm, and the amplitude 80% will fall into the range of [-R R]; increment or decrement adjustment are carried out for the Tm according to whether the difference value exceeds the [-R R] or not, and the Tm will more and more approach to Zm along with the increasing adjustments.

The invention discloses a key recovery device for UOV signature. The device comprises a message and signature module, a power consumption curve module, a key operation module, a key guess value module, and a central processing module; the message and signature module is used for generating N message-signature pairs; the power consumption curve module is used for collecting power consumption curvesgenerated during the generation process of each message-signature pair; the key operation module is used for sequentially selecting calculation formulas in which all keys participate during a UOV signature generation process; the key guess value module is used for sequentially selecting elements in GF(2k) as the guess values of the keys in each selected calculation formula; and the central processing module is used for analyzing N power consumption curves when a guess value is selected each time, so as to obtain keys in the UOV signature algorithm. Correspondingly, the present invention alsodiscloses a key recovery method for the UOV signature. With the device and method of the invention adopted, the security problem of the UOV signature can be discovered, so that technical support can be provided for the protection of the UOV.