75 results about "Self adaptivity" patented technology

The invention provides a self-adaptive localization method, equipment and system which adopt a TOA and RSS fusion mode. The self-adaptive equipment comprises an observation result collector for collecting results of the TOA and the RSS of signals sent by an object, a TOA result counter for determining the number of the TOA results, and a position counter for selectively calculating the strategy of the position of the object and calculating the position of the object according to the selected strategy. The equipment can select the position strategy in a self-adaptive mode according to the number of the TOA results. Compared with the prior art, the self-adaptive method, equipment and system have the characteristics of self-adaptivity, reliability, accuracy, expandability, low cost, and the like.

The invention discloses a method and a system for topic keyword self-adaptive expansion on a social network platform. According to the method and the system for the topic keyword self-adaptive expansion on the social network platform, implicit keywords and keywords of relevant topics are extracted to build a keyword expansion vocabulary through the analysis of the correlation among social network information contents. The method includes the following steps: labeling a small amount of keywords to build a seed keyword vocabulary, collecting sample information to build a corpus through incremental self-feedback, obtaining word frequency through the sample information, obtaining relevant words which have high correlation with the seed keywords through the word frequency and multi-layer filtering algorithm, and selecting suitable words and adding the words to the keyword expansion vocabulary. The method and the system for the topic keyword self-adaptive expansion on the social network platform are different from a traditional webpage class keyword expansion mechanism, and are based on the characteristics of the social network information contents, and have higher flexibility and self-adaptivity to the selection of the keywords.

The invention discloses a track optimization method for an unmanned aerial vehicle relay broadcast communication system. The method comprises the steps of establishing the unmanned aerial vehicle relay broadcast communication system; establishing a three-dimensional rectangular coordinate system; transmitting signals to an unmanned aerial vehicle relay node by a fixed base station node; broadcasting the signals to user nodes by the unmanned aerial vehicle relay node; receiving the broadcasted signals by the user nodes; determining interruption probabilities of all user nodes; determining the interruption probability of the user node with the highest interruption probability; and establishing an unmanned aerial vehicle track optimization model based on a maximum-minimum criterion and searching the optimum course angle. The method has the effects that according to the method, influences of links from an unmanned aerial vehicle to the base station on the system performance are taken into consideration and the method has better completeness. Compared with an unmanned aerial vehicle position optimization method for the unmanned aerial vehicle relay broadcast communication system, the method has the advantages that a fixed wing unmanned aerial vehicle is taken as a relay communication platform, a position of the unmanned aerial vehicle can be dynamically adjusted by a relay unmanned aerial vehicle according to a change of an environment, and the method has better self-adaptivity and wider application range.

The invention discloses a polarimetric SAR image classification method based on a semi-supervised SVM and mean shift. The polarimetric SAR image classification method comprises the following steps of respectively establishing a polarimetric SAR image classification training set and an image classification testing set; obtaining a polarimetric SAR image classification result by using an S4VMs algorithm; selecting a sample set, with a high degree of confidence, of the S4VMs classification result; modifying the S4VMs classification result by using a mean shift result, and updating the sample set; updating the training set, the testing set and a classification model; classifying polarimetric SAR images by using the classification model. According to the polarimetric SAR image classification method, threshold value soft division is adopted, and self-adaptivity of the algorithm is improved; the sample set is modified through the mean shift result, image information is completed, the problem that manual marking is difficult is solved, the better classification result is obtained, and the polarimetric SAR image classification method can be used for target detection, identification and classification.

The invention discloses a cooperative communication multi-resolution self-adapting wave beam forming method which solves the codebook mismatching phenomenon and the problem of low backward channel frequency spectrum utilization ratio in the prior art. The method comprises the following concrete steps of: (1) building a plurality of codebooks of different resolutions according to performance requirements of a system, and storing at a transmitting end and a receiving end; (2) estimating an equivalent channel matrix from the transmitting end to the receiving end, and carrying out singular value decomposition (SVD); (3) searching an optimal wave beam forming matrix from the codebook set according to the performance requirements of the system, and feeding back index numbers to the transmittingend; and (4) finding out an optimal wave beam forming matrix from a local codebook set according to the received index numbers by the transmitting end, thus forming a wave beam. The cooperative communication multi-resolution self-adapting wave beam forming method has the advantages of stronger self adaptivity and smaller average feedback data amount on different channel scenes, realizes the channel adaptation as highest as possible, and improves the frequency spectrum utilization ratio of the backward channel of a cooperative communication system.

The invention provides a defrosting control method applicable to an air-cooling heat pump unit, and relates to the technical field of air-conditioning refrigeration. The method comprises the steps: (1) when in state of stable working condition, measuring the temperature of a first group of fins; (2) measuring the temperature of a second group of fins at intervals and calculating the temperature change rate of the fins in unit time; (3) setting a plurality of types of frosting areas, determining the frosting areas by the temperature change rate of the fins and the measured environment temperature; (4) continuously measuring the environmental temperature and the temperature of the fins, calculating the temperature difference, and defrosting when the temperature difference reaches a set defrosting enter temperature difference of the frosting area and a corresponding defrosting cycle comes; and (5) exiting the defrosting when the temperature of the fins reaches a set defrosting exit temperature of the frosting area, and entering a next defrosting cycle. The defrosting control method can automatically control the enter and exit of defrosting, improve the self adaptivity of the air-cooling heat pump unit on the change of the environmental temperature, and is characterized by accurate and timely defrosting and no need of manual operation.

The invention discloses a fabric defect detection method based on frequency spectrum curvature analysis. The method comprises the following steps: eliminating a texture background frequency fraction,namely performing masking shielding on frequency spectrum curvature characteristics of fabric images, and eliminating a frequency fraction of a periodic texture background part so as to obtain a residual frequency spectrum only with defect information; performing multi-channel filtering, namely performing frequency domain filtering on the residual frequency spectrum by using a multi-channel filterso as to separate and enhance defect characteristics at different frequency bands; performing threshold partitioning and fusion, namely performing threshold partitioning on the filtering output images, and fusing partitioning results according to position 'or' operation, thereby obtaining finally single detection result diagrams. By adopting the method, prior knowledge related to fabric texturesand defects is not demanded, good self-adaptivity and interference resistance can be achieved, and automatic on-line detection on fabric defects can be effectively achieved.

The invention relates to a temperature control method for reaching a set temperature at equal time intervals at the preheating stage of plastic machinery, in particular to a temperature control method for realizing various stages of a charging barrel and a handpiece die of the plastic machinery to reach a set temperature at equal time intervals by using a delay heating method on an original temperature control system, and the system temperature is controlled by the temperature control method provided by the invention before being controlled by a system PID (Proportion Integration Differentiation) or a fuzzy PID. The method mainly comprises the following steps of: firstly, finding a heating segment with the longest first time duration and recording times for various segments to reach the set temperature; and then, respectively subtracting the arrival times of other segments from the arrival time of the heating segment with the longest first time interval so as to acquire respective next heating delay times. The delay times are more accurate in the later boot process, the self adaptivity of the delay times is realized, the heat energy loss of the segments with low set temperatures because of waiting segments with the set temperatures for reaching the set temperature is avoided, the meaningless electricity waste on temperature control equipment is decreased, and the aim of energy saving is achieved.

The invention discloses a silence detection method based on a minimum energy wavelet frame. The silence detection method comprises the following steps that (1) analog voice signals which are polluted by additive white gaussian noise are sampled to obtain digital voice sampling signals; (2) in a discrete signal space, the minimum energy wavelet frame is used for decomposing the digital voice sampling signals into a plurality of sub signals; (3) framing processing is conducted on all sub signals decomposed in the step (2) simultaneously, the amounts of the frame energy in the same time shafts of all the sub signals are calculated respectively, then the amounts are added, and then the specific values of VAD judgment variables are calculated; (4) a judging device is used for judging the specific values of the VAD judgment variables, the primary judgment result of a three-stage judgment threshold is obtained, a judgment result smoothing algorithm is used, a final VAD judgment result is obtained, and therefore a voice signal silent area and a voice signal acting area in the signals are judged. The silence detection method based on the minimum energy wavelet frame has the advantages of being low in calculating complexity, strong in self-adaptivity, high in VAD effect accuracy and low in hardware cost.

The invention discloses an indoor auto-navigating Internet-of-things intelligent wheelchair and a control method thereof. The indoor auto-navigating Internet-of-things intelligent wheelchair has intelligent new functions of the establishment of an environmental map in a room without GPS, autonomous operation, autonomous environment exploration, autonomous location, autonomous navigation and automatic obstacle avoidance and the like, in addition to being capable of replacing ordinary wheelchairs, for users who are unable to handle wheels, have no eyesight to judge the environment, and are incapable of controlling ordinary electric wheelchairs, and for occasions where dynamic obstacles require flexible judgment and control, the intelligent wheelchair has prominent self-adaptivity and furtherhas the advancement of the remote monitoring and control and smart home Internet-of-things; the intelligent wheelchair is smart home which takes a battery as power, where a passenger can perform automatic control and plane omini-motion (move forward, move back, make a turn, move laterally and rotate in situ on the ground), and which can build an environmental map, perform autonomous navigation and automatic obstacle avoidance and can be remotely controlled through Internet and controlled by Internet of things.

The invention relates to a wave glider yawing information self-adaptive filter method, and relates to the motion control field of the wave glider, and specifically relates to a wave glider yawing information self-adaptive filter method. The wave glider yawing information self-adaptive filter method comprises a floating body yawing response self-adaptive filter method and a submerged body yawing response self-adaptive filter method which are operated in parallel; the wave glider yawing information self-adaptive filter method provided by the invention comprises the following steps: correcting adata model according to dynamic data of actual sailing of the wave glider to realize self-adaptive filter, wherein the heading angle and a bow-turning angular speed of the floating body and the submerged body of the wave glider can be estimated at the same time, and the good filter effect still can be achieved under the influence of the uncertainty environment interference and the model parameterperturbation. The self-adaptive filter method disclosed by the invention is simple in structure, easy to realize, good in self-adaptivity, and can be applied to a wave glider motion control system toeffectively improve a control effect.

The invention relates to a denoising method for a surface myoelectricity signal based on CEEMD and an improved wavelet threshold value. The method comprises the steps that complete ensemble empiricalmode decomposition is used for decomposing the surface myoelectricity signal to obtain intrinsic mode function components; then, through component correlation analysis, the proper intrinsic mode function components are selected, and all the selected intrinsic mode function components are subjected to improved wavelet threshold value processing; finally, the signal is subjected to signal reconstruction through the intrinsic mode function components processed through the improved wavelet threshold value and the intrinsic mode function components not processed through the improved wavelet threshold value, and a denoised signal is obtained. The method has self-adaptivity in signal processing and is suitable for analysis on the nonlinear and non-stable surface myoelectricity signal, the adverseeffect caused by mode aliasing can be reduced, useful information in the signal is reserved as much as possible, the influence caused by the noise is reduced, and it is proved through an experiment that compared with other denoising methods, the denoising method for the myoelectricity signal has a better effect.

The invention relates to a multilayer color-shifting key modulation method capable of realizing non-orthogonal multiple access. The method comprises the following steps: extending a single-layer constellation diagram of a CSK into multiple layers by combining the features of the CSK constellation diagram with the basic through of the PNDOMA, and then proposing a MLCSK modulation scheme. Each layerof constellation point is used for the use of single user terminal, and the power distribution of each layer of constellation point is decided according to a channel condition of each user terminal,thereby realizing a multi-user VLC communication system with channel self-adaptivity, thereby increasing the total throughput rate of the system.

A microwave signal inhibition device and method, an antenna assembly and a microwave ablation needle are provided. The microwave signal inhibition device comprises a composite structure. The compositestructure comprises non-metallic material with a low dielectric constant, and a plurality of metal thin films formed on the non-metallic material, wherein the length of each section of the metal thinfilm is one fourth to three fourths of wavelength of a to-be-inhibited microwave signal; an interval between the metal thin films is one tenth to one twentieth of wavelength of the to-be-inhibited microwave signal; and a relative dielectric constant of the non-metallic material with the low dielectric constant relative to vacuum is less than or equal to 5. The microwave signal inhibition device and the microwave ablation needle based on multi-stage choke flow technology have great self-adaptivity; upon small input power or short ablation time, or power decrease or ablation time reduction, anideal spherical ablation area can be achieved; and compared with a common design, microwave energy can be fully utilized and carbonization degree of a central area can be reduced.

The invention discloses an FDA-MIMO radar distance fuzzy clutter suppression method based on auxiliary multi-waveform pulses. The method comprises the steps that 1, a waveform having the ultralow cross-correlation property with a main transmitted waveform is selected; 2, the auxiliary pulses are transmitted within coherent integration time according to system parameters and designed OFDM signals;3, a fuzzy clutter covariance matrix of a main observation interval is obtained by utilizing the auxiliary pulses; 4, distance fuzzy clutters in the main observation interval are suppressed based on the minimum variance criterion; and 5, remaining clutters are suppressed according to a traditional non-side-looking mode. The non-self-adaptivity defect of fixed weighting of a traditional FDA-MIMO method is overcome by designing a matched filter through the auxiliary pulses due to the consistency of the auxiliary pulses and the distance fuzzy clutters of the main observation interval, and the stability of array errors is improved.

The present invention comprises light-splitting plate capable of splitting up the light transmitted by transverse Zeeman laser into two beams and reflecting them, compensating ring set perpendicular to optical axis and 1/4 wave sheet placed in the compensating ring, two length-different vacuum chambers placed between 1/4 wave sheet and right-angle tetrahedral reflector and parallel to optical axis, polarizing reflecting prism and fully-reflecting prism for receiving reflected returning light, two photo-electric delectors and one phaser and data processor connected with phaser. Said invention can raise measuing accuracy and resolution, and can be combined into portable instrument, and possesses self-adaptivity for environmental vibration and drift of optical beam.

The invention discloses a power distribution network fault section positioning method based on a FDM. The method comprises the following steps: firstly developing various measurement point zero-sequence currents after a single phase ground fault is existent in the power distribution network based on a generalized Fourier decomposition method (FDM) so as to obtain a series of orthogonal and mutually-independent Fourier intrinsic band functions (FIBFs) with self-adaptivity; and then defining Fourier-Hilbert spectrum (FHS) based on various band functions, and further constructing transient energydensity functions of various measurement point zero-sequence current after the fault based on the marginal spectrum, and forming fault positioning criterion. Through the positioning method disclosedby the invention, the effective technical support can be provided for the quick and accurate positioning of the single-phase ground fault of the power distribution network, and the positioning methodhas good engineering practical value.

The invention discloses a seismic data noise-reduction method based on multi-resolution singular value decomposition, and belongs to the field of the oil gas geophysical exploration. The multi-resolution singular value decomposition processing is performed on a signal by using the different characteristics of a seismic signal and a random signal, thereby reducing the noise in the seismic signal. Through the method provided by the invention, the seismic data is processed through the multi-resolution singular value decomposition, and the seismic data noise suppression is realized. The seismic data is processed through the multi-resolution singular value decomposition, and the seismic data noise suppression effect is realized; the method has self-adaptivity, and can avoid the importing of excessive artificial factors; the operation speed is fast and a requirement on the data processing speed on the industry can be satisfied; and the processed signal can satisfy the processing and explanation work of the deep seismic data.

The invention discloses a prediction model algorithm for biological toxicity of chemical molecules based on a fuzzy neural network. A model prediction method based on the fuzzy neural network predictsand controls the biological toxicity of the chemical molecules in advance. For the problem that in the synthesis process of the chemical molecules, the influence of the hydrophobicity of the chemicalmolecules with different molecular structures on the biological toxicity has uncertainty, nonlinearity and other characteristics, and a precise model is difficult to establish in the synthesis process of the chemical molecules, a biological toxicity prediction model based on the fuzzy neural network is designed; through the adjustment of parameters of the fuzzy neural network, the method improvesthe processing capability of the neural network and achieves high-precision front-end prediction of the toxicity of chemical molecules. It is shown through experimental results that the method has good self-adaptivity, can predict and control the biological toxicity during the synthesis of the chemical molecules in advance, the cost of chemical synthesis is reduced, the time for chemical synthesis is shortened, and the pollution to the environment is reduced.

The invention discloses an infrared thermal imaging all-weather anti-pirate on-board alarming system, belonging to the field of vessel anti-pirate technique. The system comprises a board inside and outside infrared photographing module, an image processing module and an alarming module, wherein the image processing module comprises an image dividing module, an image screening module and an image classifying module; an infrared image obtained by the board inside and outside infrared photographing module is input into the image dividing module to be divided so as to obtain a binary image; the binary image is further input into the image screening module to be screened so as to obtain characteristic vector information of the image; the characteristic vector information is subjected to SVM (support vector machine) classification training so as to obtain the recognition result and alarming information of the characteristics of the human body; and the alarming information is input into the alarming module to realize alarming. Depending on the integration of software and hardware, the system is stronger in self-adaptivity, good in instantaneity, low in false alarming rate and excellent in portability; and the hardware part of the system is minimized, portable, low in energy consumption and high in integration degree, and has sufficient identification processing and man-machine interaction calculation ability.

The invention provides a large-scale road network signal lamp estimation method, which comprises the steps of: acquiring road network information; dividing a road network map; carrying out self-adaptive timing on signal lamps; and conducting distributed calculation based on Hadoop. The large-scale road network signal lamp estimation method performs self-adaptive map division on a road network through calculating density of the signal lamps, achieves load balancing of signal lamp timing optimization time calculation in a plurality of blocks, greatly increases generating efficiency of road network map division by adopting the Hadoop distributed system, discloses a signal lamp timing scheme having self-adaptivity and real-time performance, is different in signal lamp duration at each periodic time segment and even each day, and can effectively optimize the timing duration problem of the original or newly-added signal lamps of roads.

The invention relates to an automatic labeling machine. The machine comprises a rack, a feeding unit, a fixing unit, a suction unit, a carrying unit and a compression unit are arranged in the rack, and the feeding unit conveys a labeling band to the fixing unit; the fixing unit takes down a label on the labeling band and fits the label to a product on the carrying unit, and the compression unit fits the label to the product. The automatic labeling machine is high in labeling efficiency, labeling stability and self-adaptivity, and the label is accurately separated.