33 results about "Fuzzy process" patented technology

An embodiment of the present invention provides a display device, a display method and a display apparatus that may control a user to play electronic products at a suitable distance and avoid myopia of the user. The display device comprises: a distance sensor, a display screen, a controller, and a fuzzy processing device, wherein the distance sensor is configured to determine the distance between a user of the display device and the display screen, and wherein the controller is configured to control the fuzzy processing device when the distance between the user of the display device and the display screen is not greater than a predetermined value such that the fuzzy processing device carries out a fuzzy process on the image picture displayed on the display screen and the processed image picture is demonstrated to the user of the display device.

An image restoration method based on a point spread function model for an asymmetric optical system uses a VPW model to approximate a point spread function of image degradation, and is used in an image restoration algorithm. As Gaussian PSF is a blurring process which cannot be very close to the reality, and approximate consideration is carried out from the form of optical system diffraction. Compared with a Gaussian model, the invention has the advantages that the selected VPW model is wider in adaptability, compared with the Gaussian model, four parameters are adopted to specifically describe the objective fuzzy process, the objective fuzzy process is closer to the actual fuzzy situation, the invention is obtained through theoretical analysis and experimental results, the model is used in a deblurring algorithm, and the image restoration effect is improved.

An embodiment of the present invention provides a display device, a display method and a display apparatus that may control a user to play electronic products at a suitable distance and avoid myopia of the user. The display device comprises: a distance sensor, a display screen, a controller, and a fuzzy processing device, wherein the distance sensor is configured to determine the distance between a user of the display device and the display screen, and wherein the controller is configured to control the fuzzy processing device when the distance between the user of the display device and the display screen is not greater than a predetermined value such that the fuzzy processing device carries out a fuzzy process on the image picture displayed on the display screen and the processed image picture is demonstrated to the user of the display device.

The invention relates to an improved method for measuring the Doppler frequency and belongs to the pulse Doppler frequency fuzzy processing technical field. The improved method is completed through 8 steps based on an FPGA programmable logic controller, a DSP (digital signal processor) core board and Visual DSP++ software. According to the improved method of the invention, a process in which phase change caused by the change of the work period of a radar under different work modes is judged, and a process in which recursive processing is performed on measured Doppler frequency according to azimuths and distances, are additionally adopted, and therefore, the measurement accuracy of a low-work frequency radar for the Doppler frequency of a target of which the radial velocity is below a specific value can be effectively improved under the premise that the overall performance indexes of the low-work frequency radar can be ensured. The improved method is suitable for practical engineering application, is simple and convenient in operation and can realize high-precision measurement of the low-work frequency radar for the Doppler frequency. With the improved method adopted, the problem that target distance precise determination of the low-work frequency radar is seriously affected which is caused by a situation that the measurement accuracy of the low-work frequency radar for the Doppler frequency of the target of which the radial velocity is below the specific value can be solved.

The present disclosure provides a planning method for learning applied to a planning system for learning, and the planning system for learning includes a storage, a monitor and a processor. The planning method for learning includes the following steps: recording learning information of a plurality of subjects and storing the learning information in the storage via the monitor; calculating weighting parameters of the subjects according to the learning information and calculating weighting scores of the subjects according to the weighting parameters via the processor; and performing a fuzzy process to the weighting scores via the processor to transform the weighting scores into score levels of the subjects, so as to establish a learning sequence of the subjects to establish a learning plan.The disclosed planning method for learning and the disclosed planning system for learning can provide adaptive learning planning service for different users according to the learning information so asto improve the user experience of the learning system, and can lower the operation complexity of the planning system for learning through the fuzzy process.

The invention provides an aquatic traffic safety risk simulation method. According to traffic safety risk factors, a function related to a factor matrix, each factor relative weight matrix and an evaluation matrix is built to be a traffic safety risk simulation model; parameter estimation is conducted to each factor of the simulation model according to probability distribution and each factor simulation values can be generated at random; the simulation values generated at random are substituted to the simulation model; single factor risk is calculated via a fuzzy evaluation method; according to relative weight of each factor, comprehensive risk of a plurality of factors are calculated via the fuzzy evaluation method; results of the comprehensive risk calculation for the plurality of factors can be defuzzy-processed; the process from the generation of the simulation value to the de-fuzzy process is repeatedly simulated for times; and aquatic traffic safety risk simulation results are output. Aquatic traffic safety risk random information and fuzzy information can be processed; and parameter value conflicts can be solved.

A workflow management system with continuous status management includes an apparatus for detecting fuzzy process definitions, an apparatus which controls activity stages in a workflow for the purpose of processing the process definitions, and a device for evaluating the process definitions for each process instance. A method is for implementing a workflow with continuous status management through fuzzy process definitions using continuous instructions and states and logic combinations or continuous mapping operations operating thereon.

The invention relates to a digital workshop process decision-making method based on a decision tree and an expert system, which performs binning processing on the process production data to generate intervalized fuzzy process production data; conducts training and learning on the fuzzy process production data based on a decision tree algorithm, Generate fuzzy rules and import them into the fuzzy rule base; the inference engine is based on the real-time parameter data in the process real-time monitoring database, and performs fuzzy reasoning through interaction with the fuzzy rule base to generate process decisions. The invention conducts training and learning on the process production data of the digital workshop, generates knowledge rules, and then realizes the discovery of process decision-making rules from the daily process production data of the digital workshop, and overcomes the bottleneck of obtaining expert experience knowledge; The added fuzzy facts are matched with the antecedents of the fuzzy rules in the fuzzy rule base, which improves the reasoning speed and avoids the problem of low reasoning efficiency when the number of knowledge rules is large.

The invention relates to an improved method for measuring the Doppler frequency and belongs to the pulse Doppler frequency fuzzy processing technical field. The improved method is completed through 8 steps based on an FPGA programmable logic controller, a DSP (digital signal processor) core board and Visual DSP++ software. According to the improved method of the invention, a process in which phase change caused by the change of the work period of a radar under different work modes is judged, and a process in which recursive processing is performed on measured Doppler frequency according to azimuths and distances, are additionally adopted, and therefore, the measurement accuracy of a low-work frequency radar for the Doppler frequency of a target of which the radial velocity is below a specific value can be effectively improved under the premise that the overall performance indexes of the low-work frequency radar can be ensured. The improved method is suitable for practical engineering application, is simple and convenient in operation and can realize high-precision measurement of the low-work frequency radar for the Doppler frequency. With the improved method adopted, the problem that target distance precise determination of the low-work frequency radar is seriously affected which is caused by a situation that the measurement accuracy of the low-work frequency radar for the Doppler frequency of the target of which the radial velocity is below the specific value can be solved.

The invention relates to a three-section cascaded fuzzy control method for the blanking equipment of a cooling bed in a production line of continuous-rolling seamless steel pipes, which belongs to the field of fuzzy control. The invention aims at solving the problems that the number of detecting elements adopted by a traditional conventional control method is much, the equipment cost is increased and the number of the damaged detecting elements is also increased simultaneously. According to the method disclosed by the invention, the running processes of all equipment are decomposed and summarized into a plurality of 'therbligs', and the cascaded prediction of the actions of starting and stopping of each 'therblig' is carried out and is also input to a programmable logic controller (PLC) for carrying out logical operation so as to obtain the cascaded prediction of starting and stopping of 'therbligs' managed by equipment at a next stage. Such a process is circulated and reciprocated. The number of in-situ on-line detecting elements is lowered, and the running stability of the equipment is also enhanced. By predicting the actions of the equipment and combining the thinning of the 'therbligs' of the action processes of the equipment with the PLC, the aim of fuzzy process control is realized, and the on-line number and the failure rate of the in-situ detecting elements are lowered.

The patent provides a high-performance temperature control system for an LED wire bonder, comprising, in heating blocks, a plurality of heating bars, wherein a temperature sensor is disposed between the heating blocks to collect temperature data of the heating blocks; a controller comprising a PID module, wherein according to a given temperature value and an actual output temperature value, a temperature control deviation parameter is formed and deviations constitute a control amount through linear combination according to proportions, integral and differentiation; a fuzzy module, wherein fuzzy processing is performed on the temperature control deviation parameter according to an assignment table of membership grade of each fuzzy sub-set; and a fuzzy inference module, wherein according tothe parameter after being fuzzy processed, a PID module is obtained through inference to acquire correction parameters of proportions, integral and differentiation of deviations. A heating bar drivercontrols heating bars which are heated fast according to the control amount after being corrected with correction parameters. Defects in temperature control of the wire bonder with adoption of PID control is overcome, so as to enhance dynamic and static characteristics of the system and improve adaptation and robustness of the system.

The invention discloses an image regularization super-resolution reconstruction method based on a Gaussian-like fuzzy kernel, and the method comprises the steps: comprehensively considering distortionand disturbance factors, i.e., a matching error between an existing model and actual degradation, carrying out the modeling of a fuzzy effect caused by the actual degradation by employing a Gaussian-like function model, and carrying out the super-resolution reconstruction of an image through a minimum mean square error as a criterion. According to the method, four parameters are adopted to specifically describe the objective fuzzy process, the objective fuzzy process is closer to the actual fuzzy situation, the model is obtained through theoretical analysis and experimental results, the modelis used in a deblurring algorithm, and the image reconstruction effect is improved.

The invention provides a method for detecting a region of interest of a color image, which is used for detecting the color image to obtain a rectangular region of interest and comprises the following specific steps of: 1, removing spare detail parts of the image by adopting a region-based fuzzy method and remaining a boundary of a foreground region and a background region, wherein an HSV (Hue, Saturation, Value) color model is adopted in the fuzzy process; 2, selecting 6 different color channels by adopting the HSV color model and a CIELUV color model for the image subjected to the fuzzy processing, respectively obtaining 6 characteristic patterns according to phase spectrums; 3, respectively detecting corresponding candidate regions of interest for the characteristic patterns so as to obtain 6 candidate rectangular regions of interest on the 6 characteristic patterns; and 4, building a remarkable pattern of the original image based on the 6 candidate rectangular regions of interest in the step 3, and detecting on the remarkable pattern to finally obtain a rectangular region of interest. The invention has high detection accuracy and robustness for the regions of interest and better application values.

This invention provides a FBFN fuzzy process method and its device for automatically rectifying beam pointing errors, among which the device prescribes the rectified volume of the erroneous angle according to the antenna beam pointing error distribution correspondingly produced by the wind intensity distribution, and the said device is allocated in LMDS system end users having the function of automatically rectifying beam pointing error of the multibeam array antenna caused by the wind, the device measures the base station signal direction influenced by the wind on multibeam array antenna, and then predetermines the rectified angle by 13 base functions and regular fuzzy base function network beam pointing error rectifying algorism to control the array antenna.

The invention discloses a single-pixel single-color displaying and signal receiving module and a device including the module. By utilizing the combination of a group of lenses and mixed-color screens, light rays emitted from a color light source are condensed by a light condensation sheet; and by utilizing a refraction and color-collection sheet including a group of curve surfaces, each condensed light ray is refracted on the mixed-color screens at the same position to form single color and be changed into the same pixel, and even though each light ray is observed after being amplified, not one pixel and three colors, but one pixel and one color, are observed. According to the single-pixel single-color displaying and signal receiving module and the device including the module disclosed by the invention, the traditional display concept is changed, and the physiologic problem of the eye and the brain caused by fuzzy processed color is reduced; meanwhile, through a micronization process, a display device can display a realer effect without the original combined color; and the single-pixel single-color displaying and signal receiving module and the device including the module can be applied to emission or reception of invisible electromagnetic wave signals, or can be applied to reception of electromagnetic wave signals in another waveband during displaying.

The invention puts forward a fuzzy detection method for SVD (Singular Value Decomposition) on the basis of an image DCT (Discrete Cosine Transform) domain. The method comprises the following steps that: firstly, calculating the gradient map of an image to be detected, wherein the edge information of the image can be obtained from the gradient map; then, carrying out partitioning on the gradient map, and carrying out DCT, wherein the alternating current coefficient of the DCT domain reflects the edge and the definition of the image; then, analyzing the alternating current coefficient information of the DCT domain by a difference matrix, calculating the singular value of the difference matrix, and constructing a response function to express the fuzzy degree of the image of a block; and finally, using a mean value and a variance to carry out normalization on an image block response sum to eliminate the influence of image contents. An experiment indicates that the fuzzy score obtained by the method is highly consistent with the subjective evaluation score of a human eye for the image. The detection model disclosed by the invention considers the characteristics that the edge becomes wide, the definition becomes weak and the like in an image blurring process, the influence of image contents is effectively eliminated, so that detection accuracy is high, in addition, detection efficiency is high, and integral performance is superior to the integral performance of a previous method.

The invention discloses a heterogeneous network selection method based on user quality of experience. The original decision matrix is ​​formed by candidate networks and attribute values ​​affecting QoE and normalized; the uncertainty of each attribute is obtained according to the entropy value method; according to The data fuzzification process judges the influence degree of each attribute of the candidate network on QoE, and obtains the degree of membership; determines the non-membership degree of the attribute according to the uncertainty and the degree of membership, and obtains the network QoE judgment matrix; the attribute of each candidate network QoE fuzzy metric assignment is performed on the relationship among them; the fuzzy integration operator is applied to the network QoE decision matrix of each candidate network for integration and sorting, and the decision result is obtained. The objective fuzzy process of the invention makes the QoE assignment simple and easy, and has strong portability.