344 results about "Self feedback" patented technology

The invention discloses an intelligent video teaching system based on a cloud calculation model and expression information feedback. The system consists of a data cloud, a student terminal and a teacher terminal, wherein the data cloud is separated into video data and a self-feedback intelligent control subsystem. The self-feedback intelligent control subsystem has the following specific steps of collecting video signal, and reading the video images of current student states; face detection, detecting whether faces exist in the current area; expression identification, classifying and identifying the feedback expressions of the students, and judging whether sleepy expression, puzzling expression and satisfying expression exist or not; feedback expression processing, generating different processing measures aiming at different feedback expression systems; and feedback information statistics and data report generation, centrally generating data reports for the feedback information. The intelligent video teaching system adopts the technical scheme that a user is taken as the center in the cloud calculation model, and an intelligent software platform is adopted. The intelligent video teaching system has the advantages that the cost is low, the availability is high, and easy expandability is realized.

The invention discloses an overhead power transmission line running state assessment method based on a bidirectional Bayesian network. The method can be used for conducting a real-time assessment on the running state of an overhead power transmission line. According to the method, a Bayesian network structure for the assessment of the running state of the power transmission line is constructed with various factors which influence the running state of the power transmission line serving as a condition attribute set and the running state of the line serving as a decision attribute, a conditional probability table is obtained according to sample training, and by utilizing the bidirectional reasoning technology dedicated to the Bayesian network, the running state of the line can be judged by means of causal reasoning, and the hidden danger of the state can also be recognized by means of diagnostic reasoning; when an assessment error exists, a self-feedback system can be used for conducting early warning and correction, an assessment database, the network structure and parameters can be modified dynamically in real time so as to be adapted to an update, and therefore healthy running of the power transmission line is truly guaranteed.

The invention discloses a fiber optic gyroscope temperature drift modeling method by optimizing a dynamic recurrent neural network through a genetic algorithm. The fiber optic gyroscope temperature drift modeling method by optimizing the dynamic recurrent neural network through the genetic algorithm comprises the following steps of (1) initializing network parameters, and establishing an improved Elman neural network model; (2) obtaining a training and testing sample; (3) training an improved Elman neural network, and optimizing model parameters through the genetic algorithm; (4) outputting forecasts of an fiber optic gyroscope, and compensating errors. The output of the fiber optic gyroscope processed through a denoising algorithm is trained by introducing the improved Elman neural model with self-feedback connection weight, constant iterative optimization is carried out on the model parameters through the genetic algorithm, and the optimal model is obtained according to the magnitude of the errors of the model under different parameters. According to the fiber optic gyroscope temperature drift modeling method by optimizing the dynamic recurrent neural network through the genetic algorithm, the complexity of the algorithm is taken into consideration, the accuracy of the fiber optic gyroscope temperature drift model is improved, the application of the fiber optic gyroscope temperature drift model in engineering is expanded, and certain practical significance is achieved.

The invention discloses a self-feedback junk information filtering method. Self-feedback updating of information filter regulation is implemented by self-analysis, self-decision and self-optimization according to the filtered junk information by constructing journal analysis module with manual operation as little as possible. The invention greatly improves information filtering speed and accuracy, overcomes detects of high manpower participation in traditional filtration of massive information, heavy workload, correlation of speed and accuracy with operating height of manpower, and realizes information filtering automation.

A system for making a pulse domain linear programming circuit. The inputs and the outputs to the pulse domain linear programming circuit are time encoded pulse signals. The circuit includes arrays of two types of cross-coupled time encoding elements. The first type of elements includes two integrators, adders, a hysteresis quantizer, and a 1-bit self-feedback DAC. The second type of elements includes a bias element, a leaky integrator, adders, a fixed memory-less non-linearity, a regular integrator, a hysteresis quantizer and a 1-bit self-feedback DAC. The cross-coupling signals between the two types of elements are pulse time-encoded signals. All of the cross-coupling weights are set via 1-bit DACs having variable gains. The cross-coupling weights are used to set a constraint equation of a pulse domain linear programming problem. Methods to make the foregoing circuit are also described.

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 provides a blast furnace liquid iron quality online forecasting system and method based on a multivariable online sequential extreme learning machine. The forecasting system is composed of a conventional measurement system, a data acquisition unit, M-OS-ELM online forecasting software and a computer system for running the software. The forecasting method comprises the following steps of (1) auxiliary variable selection and model input variable determination; and (2) M-SVR soft measurement model training and utilization. According to the forecasting system and the forecasting method, a multivariable liquid iron quality forecasting model having output self-feedback and considering the timing sequence and time lag relation of input and output is established by use of the online process data provided by the conventional detection system and based on the M-OS-ELM intelligent modeling technology, and the multivariable online dynamic determination of four major liquid iron quality indexes, namely Si content, P content, S content and liquid iron temperature, is realized simultaneously; in short, the model has the characteristics of good practicability, more accurate measurement effects and stronger generalization ability.

The invention discloses a mobile terminal and a filtering method of short messages thereof. A support vector machine algorithm is used for sorting short messages, and simultaneously, a self-feedback function is provided; simple address list or black list matching operation is carried out based on the sorted short messages; and wrongly sorted short messages are fed back and learned to update a support vector library. Thus, the support vector library is continuously perfected, and the filtering capacity is continuously adjusted automatically and enhanced. Because the support vector machine algorithm and the address list or black list matching operation are combined for use, the scheme of the invention can aim at the short messages in various formats and especially can filter the short messages which do not belong to a black list or an address list.

A neural network control-based reload robot position controller comprises a neural network controller and a plurality of servo drivers. The neural network controller provides control information for the servo drivers. Each servo driver comprises a speed controller, a position controller and a current controller. The neural network controller adopts an Elman network in a dynamic recursive neural network structure to overcome the dynamic system identification problems, guarantee convergence rate and simplify learning rule method. An input layer is connected with the output of a sensor, and input information including position, speed and current signals is detected and controlled through the sensor. The Elman network improves local feedback and self-feedback elements in the self-learning manner, thus the robot control network is imparted a memory function to adapt to complicated dynamic environment.

The invention relates to a robust random-weight neural network-based molten-iron quality multi-dimensional soft measurement method which belongs to the blast-furnace smelting automatic control field, in particular to a Cauchy distribution weighted M-estimation random-weight neural network (M-RVFLNs) based method for multi-dimensional parameter-dynamic soft measurement of the molten-iron quality in the blast-furnace smelting process. According to the method of the invention, the principal component analysis (PCA) method is adopted to chose main parameters which affect the blast-furnace molten iron quality as model input variables, a molten-iron quality multi-dimensional dynamic prediction model which has an output self-feedback structure and takes into account input-output data at different moments is constructed, and it is possible to carry out multi-dimensional dynamic soft measurement of the main parameters Si content, P content, S content and molten iron temperature which represent the blast-furnace molten iron quality. The method of the invention comprises the following steps of (1) choosing auxiliary variables and determining model input variables and (2) training and using the M-RVFLNs soft measurement model.

The invention discloses a cluster self-feedback type load balancing scheduling system and method. The method disclosed by the invention comprises the following steps that: a scheduling central server efficiently calls a cluster response service by utilizing self five tables; Master servers in various clusters notify the scheduling central server to update various cluster states in the tables in real time by sending Hello and Update messages; after receiving a user request, the scheduling central server checks a resource distribution table placed therein, determines related processible clusters, and makes the most reasonable processing scheme in combination with an idle table and a distribution historical record table; the Master servers in various clusters periodically send the Hello messages, and notify the scheduling central server of self states; and furthermore, in the event of newly creating or completing a processing task, the Update messages are sent in real time, such that the scheduling central server is notified to modify states of various tables. A feedback mechanism is combined with a reasonable task distribution method, such that the load balancing scheduling method is realized.

The invention belongs to the technical field of a memory, and discloses a write operation circuit of a resistive random access memory. The write operation circuit comprises a voltage feedback module, a feedback control logic circuit, a slope pulse generating circuit, a polarity selection circuit and a column decoding and column gating circuit, wherein the voltage feedback module is used for acquiring voltage at a drain terminal of a memory array transistor, comparing the voltage with reference voltage and outputting a feedback signal; the feedback control logic circuit is used for receiving a write enable signal and a write operation signal, outputting a control signal under the control of the feedback signal, and driving or ending the write operation of a lower circuit; the slope pulse generating circuit is used for receiving the control signal and generating a pulse signal which changes step by step; the polarity selection circuit is used for receiving the pulse signal and the write operation signal, and outputting an SL signal and a BL-pre signal; the column decoding and column gating circuit is used for receiving the BL-pre signal, decoding, and gating a column gating tube to enable the BL-pre signal to be written into a bit line of a memory array; the SL signal accesses a source line of the memory array. According to the write operation circuit, the self-feedback detection process is realized by detecting the voltage at the drain terminal of the memory array; with the step pulse signal, the phenomenon of over-writing can be avoided, and the reliability of the resistive random access memory is improved.

The invention discloses a human simulation dexterous hand based on shape memory alloy (SMA) flexible body intelligent digital composite structures. The human simulation dexterous hand is composed of the five different sizes of SMA flexible intelligent digital composite structures and flexible wrapping materials. The size of each SMA-flexible body intelligent digital composite structure corresponds to one finger and a metacarpal bone of the finger of a human hand. Each SMA flexible body intelligent composite structure is composed of two sections, one section is of a rigid structure simulating a metacarpal bone structure of the human hand, and the other section is of a flexible deformation structure simulating the finger part of the human hand. The SMA flexible body intelligent digital composite structures are composed of 3D metacarpal bones, intelligent digital driving skeletons, elastic sheets and the flexible wrapping materials. The SMA flexible body intelligent digital composite structures are composed of the intelligent digital driving skeletons, the sheets and the flexible wrapping materials, so that self-feedback control and digital bending motion can be realized. The dexterous hand has the advantages that the simulation degree of shapes and motion is high, cost is low, safety and compatibility are good, and controllability is high.

The invention discloses a neuromuscular electrical stimulation system with implantable automatic feedback adjustment, which can accurately feedback the executive condition of the implanted parameter, improve the therapeutic effects of the implantable electrode specific parameter, really realize improvement and repairing of the individual functions and improve the reliability, effectiveness and controllability of the implanted device. The invention adopts the technical proposal that an implantable electrical stimulation generator are combined with an in vitro controller which can control the stimulus wave parameters and instructions, thereby the online in vivo parameters can be effectively monitored, feedback and adjusted; the signal transmission in the in vitro controller are completed at the same time. The neuromuscular electrical stimulation system can be used in the neuromuscular electrical stimulation field.

The invention relates to a digital fluid cylinder with transformer ratio feedback, belonging to fluid cylinder technology area, especially feedback control technology of self-feedback digital driving hydraulic cylinder. As the piston of fluid cylinder moves in high speed and locates precisely. Feedback bar 7 in fluid cylinder is divided into feedback bar of piston 7-1 and feedback bar of control valve 7-2 and at one end of the feedback bar of piston 7-1 transmission 6 is set. Clutch 13 is set at one end of the feedback bar of controller 7-2 and set at the position where the clutch 13 is joined with the transmission 6. NC device 1 controls the running of driving motor 2 and different clutch terminals 12 of clutch 13 to join and release with the transmission 6. The piston journey is divided into high speed moving segment of long distance and low speed accurate moving segment of micro distance by NC device. In different moving segment different clutch terminal 12 is started so that the core of control valve 14 obtains different feedback energy and different moving speed and located accuracy of piston are controlled.

The invention provides a construction method of a full duplex relay system based on sparse code multiple access, and belongs to the field of communications. The invention aims to solve the problem of difficulty in meeting the requirements of spectrum efficiency and transmission rate in 5G in a conventional OFDMA (Orthogonal Frequency Division Multiple Access) system, and further provides a construction method of an interference cancellation full duplex relay system based on the sparse code multiple access. The construction method of the full duplex relay system based on the sparse code multiple access is implemented by the following steps that: I, a user A<J> encodes information in a sparse code multiple access way, and transmits the encoded information to a relay station; II, the relay station receives and transmits the information in a full duplex way, performs interference cancellation on self-feedback interference, and forwards the information to a user B<J>; and III, the user B<J> performs corresponding decoding after a signal forwarded by the relay station is received in order to obtain the information transmitted by the user A<J>. The construction method is suitable for the field of communications.

A phase mismatch compensation device comprises a first low pass filter unit, a second low pass filter unit and a phase compensation unit. The first low pass filter unit comprises a first input unit transferring the I-channel analog input signal to an input terminal of a first OP-amp, and the first self-feedback unit transferring the I-channel output signal to the input terminal of the first OP-amp. The second low pass filter unit comprises the second input unit transferring the Q-channel analog input signal to an input terminal of a second OP-amp, and a second self-feedback unit transferring the Q-channel output signal to the input terminal of the second OP-amp. The phase compensation unit comprises a first compensation unit transferring the Q-channel analog input signal to the input terminal of the first OP-amp, and a second compensation unit transferring the I-channel analog input signal to the input terminal of the second OP-amp.

The invention provides a true-random-number generator based on an autonomous boolean network structure. The generator is used to solve the technical problem of poor entropy source stability existing in existing true-random-number generators, and includes an oscillating circuit and a sampling circuit. The autonomous boolean network structure formed by N+1 logic gates is adopted for the oscillatingcircuit. One input port of one of the logic gates is connected with an output port of a right neighbor logic gate, another input port is connected with an output port of a logic gate after k left spacing logic gates, and the last input port is connected with an output port of the one of the logic gates through a time delay self-feedback circuit. The sampling circuit includes N+1 D flip-flops and an exclusive-or gate. Input ports of the flip-flops are connected with the output ports of the logic gates of the oscillating circuit. Input ports of the exclusive-or gate are connected with output ports of the flip-flops. An output port of the exclusive-or gate is used as an output port of the true-random-number generator. According to the generator, entropy source stability is not impacted by thenumber of nodes, and random-number output frequency can reach 300MHz. The generator is used in the field of secure communication.

The embodiment of the invention provides a soft robot system which is applicable to detection operation of complex environments and unknown fields, based on SMA, self-feedback and SSMA driving, combines external feedback, and matches soft joints and rigid joints. The modules namely an SSMAs driver element module, a flexible mechanism module and foot SMA driver modules are provided, wherein electric current flowing through SSMAs is adopted to control the telescopic length of the SSMAs so as to control the integral contraction of the robot; the parallel structure of SMA and SSMA realizes SMA self-feedback and the external feedback of the SSMA, so that the accurate control on the soft robot is realized; an external 3D shell is used for connecting the front rigid part with the rear rigid part of the robot, so that the soft robot system has better flexibility; a square spring supports a flexible silica gel shell to provide restoring force and other power; two groups of SMA driver modules in front of and at back of each foot structure are controlled respectively, so that the feet motion is realized, and the motion of the robot is realized along with other units.

The invention provides a photonic-filtering-based optoelectronic oscillator, which adopts an amplified feedback laser (AFL) as an optical domain filter instead of a conventional electric domain filter. A longitudinal intermode beat frequency microwave signal of the AFL serves as a drive source of a modulator for modulating laser injected into the AFL to form a self-feedback oscillatory system to further realize high-quality microwave and optical clock output functions.

The invention discloses a large-scale malicious domain detection system and method based on self-feedback learning and relates to the technical field of computer network security. For the deficiency of an existing detection technology on mass data processing and detection model updating, a malicious domain real-time detection system applicable to large-scale data is designed and realized. A methodof extracting a small data set for verification and updating is provided innovatively. The online learning efficiency is improved. Core algorithms comprise an algorithm of detecting malicious domainsbased on a support vector machine (SVM) in mass real-time domain detection, an online learning algorithm fSVM based on the self-feedback learning and an automatic calibration algorithm. Through theoretical demonstration and experimental verification, according to the algorithms provided by the invention, when the newly-presented malicious domains are copied with, the response can be carried out timely, and the excellent operation efficiency is achieved. According to the system and the method, the further analysis of the detected malicious domains is also realized. The system and the method play an enlightening role in perceiving malicious domain related threat intelligence.

The invention discloses a self-feedback type washing machine and a control manner thereof. The self-feedback type washing machine comprises a motor, a water pump driven by the motor and a water torch connected with the water pump; the self-feedback type washing machine further comprises a system controller used for controlling the motor; the water torch is provided with a spraying nozzle assembly used for switching, the system controller controls switching of the spraying nozzle assembly and detecting the working state of the spraying nozzle assembly, the water outlet pressure is changed after spraying nozzles of the spraying nozzle assembly is switched, the system detector detects the working state of the motor and calculates the power, the power is compared with preset power, then the rotating speed of the motor is adjusted to enable the power of the motor approaches the preset power, and therefore different water outlet flows are output from the water pump. By means of the above manner, the self-feedback type washing machine can generate different pressures according to the spraying nozzles with different calibers, and two parameters including the pressure and the flow are controlled to achieve mutual and automatic adjustment.

The invention discloses a magnetic sliding shoe pair for an axial plunger pump and a motor and a control method. The magnetic sliding shoe pair comprises plungers, coil sleeve pieces, sliding shoes and an inclined disc; closing coils are arranged in the coil sleeve pieces; micro modeling holes are formed in the bearing face, making contact with the sliding shoes, of the end face of the inclined disc and are in a semi-spherical shape; and the back face of the inclined disc is provided with a main iron core and two auxiliary iron cores, the iron cores are all wound with coils, and the coils areconnected with an external alternating current power supply. An electromagnetic force self feedback regulation mode is provided so that the stable working state of the sliding shoe pair can be ensured. When the axial plunger pump / motor works, the coils are powered on, a magnetic field is generated, accordingly, the sliding shoes are attracted to the inclined disc, meanwhile, the coil sleeve piecesgenerate an induced magnetic field, electromagnetic force applied to the sliding shoes is converted into attraction force or repulsive force along with moving of the sliding shoes, a hydrodynamic effect is formed when the sliding shoes are under a complex stressed condition, the bearing face of the inclined disc is subjected to micro modeling design, thus, the oil film rigidity is improved, and the friction coefficient is reduced.

The invention discloses intelligent electrical heating clothes with a self-feedback regulation function. A clothes base body is provided with a temperature control system, a power supply system and an electrical heating system, wherein the electrical heating system is arranged at a position corresponding to a human body portion needing to be heated, the power supply system is connected with the electrical heating system through the temperature control system, and the temperature control system detects temperature information of the heated portion and controls the working state of the electrical heating system according to the temperature information. According to the clothes, the temperature control system detects the temperature of the heated portion and controls the heating power of the electrical heating system according to the temperature information, so that the intelligent self-feedback temperature regulation function of the electrical heating clothes is achieved, and accordingly the requirement of people for the warmth retention property of the clothes is met.

The invention discloses a structured light depth camera self-correction method and device for a smart phone. The device is composed of an infrared laser speckle projector, an image receiving sensor, aself-correction module, a depth calculation module and a mobile phone application processing AP. According to the device and the method, a speckle pattern is projected by a projector; a feature blockis set in the reference speckle image, an input speckle image is acquired through an image receiving sensor; an optimal matching block corresponding to the feature block is searched in the input speckle image through a similarity criterion; the offset between the feature block and the matching block is obtained; once the optical axis of the projector and the optical axis of the image sensor change relatively. the offset can be changed along with the offset; and an optimal offset os solved according to a certain rule and the reference speckle image is reversely adjusted, so that the center ofthe input speckle image and the center of the reference speckle image can form a self-feedback adjustment closed-loop system, thereby realizing that the input speckle image and the corrected referencespeckle image can always find an optimal matching relation when an optical axis is changed in a relatively large range.

The invention relates to a self-feedback linear galvanostat integrating an adjustable thermistor, which belomngs to the technical field of a semiconductor power device. The self-feedback linear galvanostat comprises a junction-type field effect transistor (JFET) and an adjustable thermistor, which are integrated together, wherein one end of the adjustable thermistor is connected with a JFET source electrode, and the other end is connected with a grid electrode of the JFET. The self-feedback linear galvanostat is centralized on the adjustable thermistor, and the adjustable thermistor can obtain a resistance value meeting the requirement of the output current through a laser cutting way, so that different types of products can be obtained in the same batch. The thermistor is a positive temperature coefficient, under the working situation, the temperature is increased, the resistance is increased, the output current is reduced, and the reliability of an application system is protected. The self-feedback linear galvanostat has advantages of high integration, stability in output current, adjustability of the current and good temperature property and can be applied to the fields such as light emitting diode (LED).

Provided are a soft measuring system and method for the quality indexes of multielement molten iron of a blast furnace. The system comprises a data collecting unit, a data preprocessing unit and a soft measuring unit. The method comprises the steps that parameters needed for soft measurement of the quality indexes of multielement molten iron of the blast furnace are acquired; the parameters needed for dynamic soft measurement of the quality indexes of multielement molten iron of the blast furnace are subjected to filtering, noise removal and normalization processing; dynamic soft measurement of multielement molten iron of the blast furnace is carried out through a blast furnace multielement molten iron quality index dynamic soft measurement model; and the parameters needed for soft measurement of the quality indexes of multielement molten iron of the blast furnace obtained after filtering and normalization processing are adopted as input, the current quality indexes of multielement molten iron of the blast furnace are adopted as output, output self-feedback is adopted, and the quality indexes of multielement molten iron of the blast furnace are dynamically predicted through online recurrence. The sequential relationship between the hysteresis characteristic of the blast furnace melting process and input and output variables is considered, the recurrence subspace intelligent modeling technology is adopted, and dynamic online soft measurement of the quality indexes of multielement molten iron of the blast furnace in the smelting process is achieved.

The invention relates to an undervoltage release, which comprises a capacitive charging booster type starting power circuit, a self feedback dual-limit detection circuit, a relay switching circuit and an electromagnet coil. The starting power circuit is connected with the self feedback dual-limit detection circuit, the relay switching circuit and the electromagnet coil, and the control output end of the self feedback dual-limit detection circuit is connected with the control input end of the relay switching circuit; the relay switching circuit comprises a relay; when the voltage of a power grid is kept at a release voltage or higher than the release voltage after reaching a pull-in voltage, a relay coil and the electromagnet coil form a serially connected loop; when the voltage of the power grid is lower than the release voltage, the electromagnet coil is in a state of an open circuit; and when the voltage of the power grid restores to the pull-in voltage or higher than the pull-in voltage, the relay coil and the electromagnet coil form a serially connected loop again. The undervoltage release has the advantages of low calorific power, big release instant starting torque, very simple circuit, reliable work, high efficiency and the like.

The invention belongs to the field of pavement engineering machinery, and relates to a self-feedback floating scraping system of a pavement milling machine. The self-feedback floating scraping system comprises a scraping plate and a control system, wherein the scraping plate is arranged on the lower part of a turning body of the pavement milling machine and can lift by being driven by a scraping plate oil cylinder; the control system is used for controlling the lifting of the scraping plate, and comprises a pressure sensor which is arranged on the scraping plate and can detect ground pressure of the scraping plate; the detection signal output end of the pressure sensor is connected to a CPU (Central Processing Unit) capable of processing detection data; and the control instruction output end of the CPU is connected to a scraping plate valve group capable of controlling the action of the scraping plate oil cylinder. The self-feedback floating scraping system disclosed by the invention can keep the appropriate ground pressure all the time for milling in a pulling and scraping operation process by detecting and regulating the ground pressure of the scraping plate in real time, thereby being suitable for the change of pavements with different terrains and improving the construction effect and efficiency.