113 results about "Differential operator" patented technology

A semiconductor device analyzer has a substrate model reading module, a Y-matrix entry module, a discriminating module, a matrix reduction module, and an output format discriminating module. The substrate model reading module reads a substrate network model of three-dimensional meshes representing the substrate of a semiconductor device. The substrate network model is a network of resistive and capacitive elements and is used for the simulation and analysis of the semiconductor substrate. The Y-matrix entry module prepares a Y-matrix from the substrate network model, each element of the Y-matrix being expressed with a polynomial of differential operator "s". The discriminating module discriminates internal nodes to be eliminated from external nodes to be left among the nodes of the substrate network model. The matrix reduction module eliminates the internal nodes, thereby reducing the Y-matrix. The output format determining module determines an output format for an operation result.

The invention relates to a based method for improving seismic data resolution based on a seismographic record varitron wave, which is characterized by comprising the steps of: 1, constructing a molecule-Gabor window, adaptively dividing an instable seismographic record into a plurality of stable segments, wherein each segment has an approximately unchangeable equivalent wavelet which is easy to extract from the segment; 2, converting the instable seismographic record into a molecule-Gabor domain by using a molecule-Gabor frame generated by the molecule window obtained by the construction in the step 1; 3, carrying out frequency extension and energy compensation processing on molecule-Gabor coefficients corresponding to the seismographic record segments in each molecule-Gabor window; and 4, inversely transforming the processed molecule-Gabor coefficients into a time domain to obtain the seismographic record after the resolution ratio is increased. In the method, on the basis of the modern quasidifferential operator principle, an adaptive time-frequency analyzing method is used as a tool, and the processed seismic data has high resolution rate and relatively keeps amplitude characteristics.

The invention discloses a method for precise positioning of a license plate in strong light conditions. The method comprises the following steps: (1) using the picture of a license plate to be processed to conduct preprocessing by self-adaptive median filtering; (2) using a differential operator to conduct edge detection of the license plate; (3) converting an image after the edge detection to a binary edge image; (4) de-nosing the binary edge image in a morphological manner and forming a plurality of communicated regions; (5) performing morphological processing on the communicated regions; and (6) positioning the region of the license plate according to the results of the communicated regions. The method for precise positioning of a license plate in strong light conditions can effectively solve the problem of interference to the positioning of the license plate under irradiation of strong light, enable the positioning accuracy to be improved, and is applicable for extracting license plates of passing vehicles from pictures taken at places such as a flowing speed measurement point or a crossroad.

The invention discloses an iris splitting method suitable for low-quality iris images. The prior art can not carry out robust splitting to the low-quality iris image with mass interference and noise. The invention uses a human eye detection algorithm to preliminarily determine a subimage of the human eye and is applied to image splitting based on interdependent histogram and cluster and ellipse Hough conversion to accurately determine the subimage of the human eye; improved Hough conversion is adopted to position the outer contour of the iris and output the integrodifferential operator value CID of a detection result; if the outer contour of the iris is not accurately positioned, parabola approximation is carried out on the image to judge whether the image is an eye-closed image; for the non eye-closed image, complexion information is utilized to re-determine the outer contour of the iris; the palpebra superior is detected by one-dimensional signal detection and parabola integrodifferential operator; the palpebra inferior is detected by one-dimensional signal detection and an RANSAC algorithm; the histogram in the iris is calculated; and a threshold value is found to remove a highly bright spot. The invention is used for iris splitting of low-quality iris image in a complex application context.

The method comprises: accessing the multi-dimensional dataset; generating a plurality of differential operators for the multi-dimensional dataset using a discrete approximation of an analytic function; and forming a plurality of geometric responses based on a plurality of differential operators resultant from the generating. The method optionally further includes isolating a selected region of interest from the multi-dimensional dataset; the selected region of interest comprising a subset of the imaging volume.

The invention discloses a road border detection method based on an infrared image, comprising the following steps: converting an input image into an image with specific scale and size by proper pretreatment; selecting a line segment more than a certain length under each threshold value by a threshold value exhaust algorithm; analyzing the line segment to obtain an accurate gradient; removing a second-order differential operator to obtain a weak line segment; removing a pseudo line segment obtained by the threshold value exhaust algorithm via the second-order differential operator; mutually combining two line segments to jointly extract the border line segment; and finally, obtaining a final road border according to a road border model. With the method, the road border can be accurately and uninterruptedly detected day and night, the method has the advantages of high instantaneity and robustness, and is easy to popularize to application fields of intelligent robot navigation, the active safety of automobiles, video monitoring and the like.

The invention provides a time domain analysis method for a transient response of lossy nonuinform multi-conductor transmission lines and aims to solve the problem that the coupling among the lossy nonuniform multi-conductor transmission lines interferes with the computation in the field of integrity of electronic circuit signals. The method comprises the following steps of: performing differential dispersion on space differential operators in an electric wave equation; and integrating time differential operators in the electrical wave equation by a trapezoidal integration method to ensure that the oscillation, which is caused by a central difference method, of a computed result can be eliminated effectively, voltage and current transient response waveforms of any point on the transmissionlines can be acquired; and the transient analysis of the transmission lines in a longer time period is effective, the waveforms can be analyzed in a longer duration without large errors, and the coupled transmission lines are not needed to be decoupled when a model of the transmission lines is built. By the method, the computational load is reduced, and the simulation efficiency is improved. The method can be used for analyzing the transient response of the lossy nonuinform multi-conductor transmission lines.

The invention relates to a weak luminescence image processing method based on regional augmentation and regional extraction in the technical field of image processing. The method comprises the following steps: converting unidimensional original data sequence of a background image and an original weak luminescence image under the lighting condition into a two-dimensional array structure, and carrying out logarithm transformation on the two-dimensional array structure; then removing noise of the weak luminescence image through morphological weighting median filtering, extracting a boundary of the weak luminescence image by a Canny differential operator, and then filling a luminescent region by a boundary closely extracted by a morphological template; obtaining a binary image with a marked luminescent region; checking a luminescent region of the image, and superposing the region onto the background image after pseudo color treatment; adding a marker on the image brightness by an image luminescent illumination calibration method; and finally recording image experimental conditions, image source and other additional information. The invention provides the reliable weak luminescence image processing method and realizes a treating process from inputting original image data sequence to outputting an image result.

The invention provides a wave field separating method and device. The method comprises the steps that variation function values of anisotropy parameter distribution of initial models are calculated and fitted to obtain variation functions of the initial models; the variation functions and a reference point search strategy are utilized for selecting N reference models from the initial models; a vector elastic wave field of a spatial domain is converted into a wave number domain; following operation is carried out on each reference model selected from the N reference models, pseudo differential operators are truncated, the wave field separation is carried out on the wave number domain, the vertical and horizontal wave field is reversely converted into the spatial domain, and the wave field separation results of the reference models are obtained; the variation functions are utilized for calculating the weight coefficients of all the reference models relative to the initial models; weighting interpolation processing is carried out on the wave field separation results of all the reference models in the spatial domain to obtain the wave field separation results of the initial models. According to the method, on the basis of ensuring the accuracy of the wave field separation results, the effect of reducing the calculation amount is achieved.

The invention discloses a multiscale infrared target adaptive detection method based on the visual reception field, relates to a multiscale infrared target adaptive detection method, and belongs to the technical field of machine vision. A calculation differential operator of an edge detector is used to calculate the gradient direction theta of an image, and an orientation information distribution map of pixel points is obtained; a local background is predicted according to background information similar to local characteristic in the infrared image; a mathematical model Gabor filter in the simple cell reception field is used to filter an object image, an object is detected preliminarily, and a direction parameter theta of the Gabor filter is determined adaptively by orientation information distribution of the pixel points; and the gray scales of the pixel points are adjusted to obtain a background inhibited and object enhanced image, and the detection precision is improved. According to the invention, the robustness, anti-interference capability and adaptability, to different scales of object, of the infrared object detection method can be improved, and the operand is low.

The invention relates to an automatic matching system and method of pi-type impedance in a radio frequency energy collection circuit. The system comprises a sampling comparison module, a logic algorithm control module, and an adjustable impedance matching network. The sampling comparison module is used for consecutively sampling voltages output by a voltage doubling rectifying circuit twice under the control of a differential operator method of the logic control module and comparing the voltages consecutively sampled twice. The logic algorithm control module is used for determining, according to a comparison result of the voltages consecutively sampled twice, a capacitor adjustment direction of a pi-type adjustable capacitor array and adjusting a quantity of adjustable capacitors integrated in the adjustable impedance matching network according to capacitance weights by using a capacitance dichotomy according to the capacitor adjustment direction. The adjustable impedance matching network is used for matching impedances of an antenna and the voltage doubling rectifying circuit according to the quantity of capacitors integrated in the pi-type adjustable capacitor array. The circuit is simple, has extremely low power consumption, consumes energy only in an on and off process, and is applicable to a weak energy collection environment.

The invention discloses a foggy weather image enhancement method based on fractional differential and dark channel prior. The method herein includes the following steps: 1. inputting a foggy weather image I, conducting dark channel prior and Retinex algorithm processing on the I, obtaining an initial de-foggy image J (x,y); 2. segmenting the J (x,y) to a foreground image J1(x,y) and a background J2(x,y); 3. separately computing the optimal fractional differential order number v1 corresponding to J1(x,y) and the optimal fractional differential order value v2 corresponding to J2(x,y); 4. determining a mask coefficient and a mask size, constructing a fractional differential operator mask w (s,t); 5. separately introducing the fractional differential order number v1 and fractional differential order value v2 which are obtained from 3 to the w (s,t), obtaining w1(s,t) and w2(s,t), conducting convolution operation on the pixel points of w1(s,t) and J1(x,y), and conducting convolution operation on the pixel points of w2(s,t) and J2(x,y); and 6. outputting the image of I which after the image enhancement. According to the invention, the method herein addresses poor de-foggy effects which are often caused in the process of enhancing foggy images by using fractional differential algorithm which has single fractional differential order in the prior art.

The invention relates to an automatic first break picking method based on edge detection, in particular to an automatic first break picking technology based on edge detection, which comprises the steps of: first, inputting original seismic data and conducting graying processing on the seismic data, and then, carrying out seismic data edge detection by virtue of airspace differential operators and finishing the edge detection by corresponding templates and image convolution, finally, correcting the edge detection results with an edge tracking technology, completing the automatic picking of seismic data of the first break and outputting picking results; a manual selection method is used for selecting an edge point as a starting point; and the edge tracking technology mainly utilizes tracking 'bug' for tracking. When being used for picking up the first break from three-dimensional seismic data, the automatic first break picking technology based on edge detection can reduce time by 7 days to 10 days. Compared with the existing automatic first break picking technology with the accuracy rate of 80 percent, the automatic first break picking technology based on edge detection can realize the accuracy rate of 99 percent.

The invention discloses an infrared image detail enhancement and noise adaptive inhibition method. The method comprises the following steps of (1) acquiring an original infrared image Forg; (2) utilizing a differential operator to calculate a filter component Fd of the original infrared image; (3) calculating the background complexity of the original infrared image, and determining a noise inhibition threshold value T1; (4) calculating a region variance V of the original infrared image, performing binaryzation on a region variance image according to an initial threshold value T2, and utilizing a matrix BW to express the binarized image; (5) calculating a weighting matrix Coe of the filter component Fd; and (6) outputting a detail enhancement image Fout. Compared with the prior art, the infrared image detail enhancement and noise adaptive inhibition method has the following advantages that (1) the infrared image detail enhancement and noise adaptive inhibition method is particularly used for processing a signal-to-noise ratio image, and can effective inhibit the noise amplification of the image while the image detail is enhanced.

The invention discloses an autonomous navigation and obstacle avoidance system for a robot is disclosed. The autonomous navigation and obstacle avoidance system for the robot comprises a collecting device and a processing device, wherein the collecting device is used for collecting current nearby environment images of the robot according to an obtained voice command, and the processing device is used for subjecting the current nearby environment images of the robot to obstacle avoidance operation on the basis of a second order differential operator and a fuzzy reasoning algorithm so as to obtain obstacle information. The invention also discloses an autonomous navigation and obstacle avoidance method for the robot. By adopting a technical solution of the autonomous navigation and obstacle avoidance system and method for robot, intelligence of the robot can be improved, and the robot can autonomously avoid obstacles without human guidance.

The invention provides a blood vessel center line automatic extraction method based on parallel structure detection and clustering. The blood vessel center line automatic extraction method solves the problems that in a contrastographic picture, the grey level distribution is not even, and due to a large amount of background noise, the vascular structure is hard to extract. The method comprises the steps of utilizing three-order differential operators for calculating the direction of an image border by arranging the position of the detection border of a gradient response operator; combining a curve model on the basis of straight lines, circular curves and Euler spiral lines to build an intrinsic curve bundle of image border points, adopting the intrinsic curve bundle to conduct description of the geometrical features on the image border, and extracting all contours of blood vessels according to the geometrical consistency of the image border; utilizing the parallel features of the borders of the blood vessels for completely detecting two parallel borders of the blood vessels, searching for the positions with the same distance as the two parallel borders, connecting the centers of all the blood vessels, and finally obtaining the center lines of the blood vessels. The method is high in precision, strong in adaptability and suitable for the fields of cardiovascular disease computer-assisted diagnosis and treatment.

A feedforward signal of a drum water level control system of a drum boiler is used for overcoming the adverse impact of false water level on water level control. The feedforward signal fL(s) is specifically formed as follow, wherein s is complex variable of Laplace transform and is equivalent to differential operator in time domain, fL(s) is Laplace transform of feedforward signal fL, pf(s) is Laplace transform of furnace pressure pf, pd(s) is Laplace transform of drum pressure pd, Cb is boiler heat storage coefficient, Kf is furnace pressure gain coefficient and T is furnace pressure filter coefficient. The invention is simple and convenient in implementation, low in cost, good in control effect and high in reliability, can effectively overcome the adverse impact of false water level and greatly improve the control quality.

The invention discloses an image enhancement method based on local search differential evolution. A local search differential evolution algorithm is used to optimize the parameters of an incomplete Beta function. Then, an image is nonlinearly transformed based on the parameter-optimized incomplete Beta function, and thus, the quality of the image is enhanced. In the local search differential evolution algorithm, the basic individual of a differential mutation operator is generated based on the information of an optimal individual and a random individual to balance the population diversity and the convergence speed. In the process of search, a local search strategy is implemented to improve the effect of image enhancement. The method can avoid falling into local optimum to a certain extent and improve the effect of image enhancement.

The invention discloses a generative adversarial network-based remote sensing image fusion method, and the method comprises the steps: employing a difference operator to extract the spatial structureinformation of an original panchromatic image, and sampling the original multispectral image; splicing the spatial structure information and the sampled multispectral image in a feature domain to obtain a sample image; inputting the sample image into a generator of a generative adversarial network to generate a fused image; and inputting the fused image and the real image into a discriminator of the generative adversarial network for discriminating and distinguishing, establishing an adversarial rule and a fusion objective function between the generator and the discriminator, and optimizing the fused image. According to the remote sensing image fusion method based on the generative adversarial network disclosed by the invention, the spatial structure information of the original panchromatic image is reserved by adopting the differential operator, and the spectral information of the original low-resolution multispectral image is reserved by adopting the sampling method, so that the lossof detail information in the fusion process is effectively reduced; in addition, a confrontation rule and a fusion objective function are established between the generator and the discriminator, so that the fusion effect is greatly optimized.