292results about How to "Avoid complex calculations" patented technology

The invention discloses a behavior identification method based on a recurrent neural network and human skeleton movement sequences. The method comprises the following steps of normalizing node coordinates of extracted human skeleton posture sequences to eliminate influence of absolute space positions, where a human body is located, on an identification process; filtering the skeleton node coordinates through a simple smoothing filter to improve the signal to noise ratio; sending the smoothed data into the hierarchic bidirectional recurrent neural network for deep characteristic extraction and identification. Meanwhile, the invention provides a hierarchic unidirectional recurrent neural network model for coping with practical real-time online analysis requirements. The behavior identification method based on the recurrent neural network and the human skeleton movement sequences has the advantages of designing an end-to-end analyzing mode according to the structural characteristics and the motion relativity of human body, achieving high-precision identification and meanwhile avoiding complex computation, thereby being applicable to practical application. The behavior identification method based on the recurrent neural network and the human skeleton movement sequence is significant to the fields of intelligent video monitoring based on the depth camera technology, intelligent traffic management, smart city and the like.

The invention relates to a prediction device and a prediction method for the state of an emergency topic. The prediction device and the prediction method are provided based on the research of a microblog topic production mechanism and the influence of opinion leaders of emergency on the state of the emergency topic. The prediction device is provided with four components of a text acquisition unit, a topic clustering unit, a topic state recognition unit and a topic state prediction unit, and the topic state is predicted through the participation state of the opinion leaders, so that the prediction method of the topic state is simplified, the prediction accuracy is higher, and a basis can be provided for monitoring the tendency of the emergency topic. Through the calculation method of topic attention provided by the invention, the computation complexity of a traditional topic attention method is reduced. Moreover, the numerical value prediction of the topic attention is replaced by adopting the prediction of the state of the topic, so that the prediction content is more reasonable, and the prediction accuracy is higher. Furthermore, a prediction method of a hidden Markov model is provided, the set of the opinion leaders and the model of topic prediction are constructed through incremental iteration, so that the prediction operation can be obviously simplified, and the prediction efficiency is improved.

The invention provides a triangular grid tooth segmentation method based on path planning. The method comprises the following steps that 1, tooth anatomical feature points are selected so as to determine the plane of occlusion; 2, tooth feature areas are extracted by using curvature information of a dental model; 3, projection of the feature areas is performed so as to perform fitting of dental arches; 4, gum lines are searched based on a secondary path planning algorithm; 5, the gum lines are segmented and tooth slit lines are searched; and 6, the gum lines and the tooth slit lines are combined to form tooth segmentation lines and the teeth are segmented based on a region growing algorithm. The triangular grid tooth segmentation method based on path planning has less artificial intervention and parameter adjustment and is suitable for various dental models of the problems of the distorted teeth and the crowded dental arches so as to have important significance in enhancing the effect of orthodontic treatment.

A rotary-table servo system neural network control method comprises (1) building a mechanical dynamic model of a permanent magnet synchronous motor rotary-table servo system, and initializing the system state, sampling time and relative control parameters; (2) according to the differential mean value theorem, enabling a non-linear input dead zone in the system to linearly approximate to a simple time-varying system, avoiding complex calculation of dead-zone inverse compensation, and finally inferring a rotary-table servo system model provided with an unknown dead zone; (3) at each sampling moment, calculating and controlling a system tracking error, a fast terminal sliding mode surface and a first-order derivative of the system; (4) based on the rotary-table servo system model provided with the unknown dead zone, selecting a neural network approaching unknown trend, designing an adaptive robust finite-time neural network controller according to the system tracking error, the fast terminal sliding mode surface and the first-order derivative of the system, and updating a neural network weight matrix; and (5) entering the next sampling moment, and repetitively executing the steps from (3) to (5).

The invention discloses a target tracking method applied to the technical field of target tracking, and comprises the following steps: obtaining a search image based on a current frame image, and obtaining a confidence value and a coordinate box according to a network tracking model; selecting a first target number of candidate boxes according to the confidence value and the coordinate box; obtaining a tracking result according to the historical tracking value and the candidate box; obtaining a corresponding confidence value, and judging whether the confidence value is within a first preset range or not; if so, performing image cutting on the current frame image according to the target template image; and under the condition that the definition of the cropped image is not less than the preset definition, replacing the cropped image corresponding to the current video frame image with a new target template image. By applying the embodiment of the invention, when the template is updated,whether to update or not is judged by combining the result fed back by the tracking model and the quality of the target image in the current frame, so that the precision of the tracking result is improved, and the complex calculation amount is avoided.

A position-posture sensing system of movable robot is composed of a photoelectric sensor for detecting the change of position and posture and converting the change to digital signals, an elastic pressing unit for ensuring the proper distance between said photoelectric sensor and ground, and a controlling-processing circuit consisting of a single-chip microprocessor, a communication interface chip, and the firmed programs. Its method is also disclosed.

The invention discloses a method, a system and equipment for monitoring vehicles based on vehicle taillight detection. The method for monitoring the vehicles comprises the following steps of: sufficiently utilizing the color information and the motion information of vehicle lights; pairing tail lights by adopting a space symmetry strategy; identifying a single target vehicle; and introducing a position prediction mechanism for preventing the shielding condition of the tail lights of the vehicles so as to effectively prevent targets from being lost. The invention solves the problems of high time consumption and low accuracy when a morphological operator is computed in the traditional algorithm, prevents the complex computation, has higher processing speed, can meet the real-time requirements, greatly decrease the iterations of the algorithm, enhance the tracking efficiency and be convenient to apply to a real-time tracking scene.

The invention relates to a correction method for an incomplete or deformed quadrangular image. The method comprises the five steps of edge point detection, abnormal edge point elimination, linear fitting, vertex calculation and image correction. The correction method for the incomplete or deformed quadrangular image is applied to an identification method identification system for certificates such as valuable documents, notes, identification cards and the like, and can be used for rapidly performing edge detection and tilt correction on defect and deformed valuable documents, notes or certificate images.

The invention relates to an infrared image super-resolution reestablishing method based on the compressed sensing theory. According to the method, low-resolution images are used as a foundation and are subjected to partitioning, low-resolution image blocks are regarded as downsampling observation corresponding to high-resolution image blocks, a downsampling model is established, and a downsampling matrix is written. A sparse transformation matrix of the high-resolution image blocks is established and is multiplied by an observation matrix, and a sensing matrix is obtained. According to the low-resolution blocks and the sensing matrix, an OMP algorithm is used for reestablishing sparse coefficients of the high-resolution image blocks, then the sparse transformation matrix is multiplied by the sparse coefficients, and the high-resolution image blocks are obtained. Finally, all the high-resolution image blocks are spliced, and a high-resolution reestablished image is obtained. The method has the advantages of being easy to achieve, quick in operation, stable in performance and good in anti-noise effect, difference operation is used for generating a difference transformation matrix and achieving sparse transformation, complex computing of redundant dictionary training is avoided, shot noise of images can be well removed, and the noise reduction advantage is achieved.

The invention discloses an adaptive genetic algorithm-based single-frequency GNSS integer ambiguity acquisition method. The method includes the following steps: step 1: acquiring the observed data of a GNSS carrier phase, and establishing a double-difference observation equation for the GNSS carrier phase; step 2: according to the double-difference observation equation obtained in step 1, utilizing the least square method to acquire the float solution and corresponding covariance matrix of GNSS integer ambiguity; step 3: utilizing known base length as a constraint condition to determine the search space of integer ambiguity; step 4: utilizing the whitening filter method to decorrelate the float solution and covariance matrix of integer ambiguity obtained in step 2; step 5: according to anobjective function, determining a fitness function, determining each operating parameter in the adaptive genetic algorithm, finally, introducing the adaptive genetic algorithm into fast solution on integer ambiguity, and searching the optimal solution of integer ambiguity.

The invention discloses an elastic body aircraft adaptive constrained tracking control indirect method. The objective of the invention is to solve the technical problem of low possibility of realizing adaptive tracking of reference instruction signals when an elastic body aircraft has input and state saturation constraints. The method includes the following steps that: a feedforward system is designed based on an instruction former, and tracked signals and the pulses of the former are subjected to convolution, so that new forming signals can be obtained and are adopted as the input of a subsequent feedback system; the design of the feedback system is decomposed into a velocity subsystem, a height subsystem and an elasticity subsystem, and the influence of elastic modality in rigid body dynamic is considered as elastic interference, and uncertain parameters and an external disturbance introduction nominal model are used in combination, and therefore, a controlled system can be obtained; and a saturation constrained adaptive control method can be realized for the controlled system through utilizing an instruction filter and an auxiliary system, and tracking for the forming signals in the feedforward system can be realized, and closed-loop system signals can be uniformly and ultimately bounded, and suppression on elastic modality deformation and vibration can be realized.

The invention relates to a certificateless key agreement method on the basis of a mobile Ad Hoc network, which comprises the following steps of: 1, initializing a system network; 2, constructing a network main private key, i.e. selecting a (t-1)th-degree polynomial to exchange necessary information at each node, enabling random t nodes or more than t nodes to mutually cooperate to obtain the network main private key and simultaneously obtaining a network public key; 3, generating key pairs for the nodes by utilizing the main private key in the network; 4, carrying out secrete communication among the nodes by utilizing the generated keys so as to implement the encrypting and decrypting process. The certificateless key agreement method has no problems of certificate verification and key escrow when implementing key agreement; meanwhile, dangerous nodes can be detected; moreover, a recommended encrypting scheme can have fewer encrypting items on the premise of ensuring security and the calculated amount and the communication traffic are reduced, and thus, the certificateless key agreement method has good practicality and security.

The present invention discloses a single-frame cold rolling force model and front sliding model debugging method. Through adjusting the parameter of a deformation resistance model and the parameter of a friction coefficient model, the debugging of a rolling force model and a forward sliding model is carried out according to collected actual rolling process data, and the deduction of the complex algorithm of the calculating model parameter and the complex calculation process of the model parameter of a complex model are avoided.

The invention discloses a positioning method and apparatus for the liver scope in a medical image. The positioning method comprises the steps: acquiring a three dimensional medical image which is formed by a group of two dimensional medical images and covers the liver; determining the position the rib, in the three dimensional medical image, in the two dimensional medical images; based on the position of the rib, determining the position of the bottom of the liver in the two dimensional medical images; determining the position of the top of the liver in the two dimensional medical images; and according to the positions of the bottom and the top of the liver in the two dimensional medical images, determining the scope of the liver in the three dimensional medical image. The positioning method and apparatus for the liver scope in a medical image only need the current image data and have no demand for the prior information of a training sample or a probability graph.

The invention provides an expanded ellipsoid set-membership filtering method based on Chebyshev interpolation polynomial approximation. According to the expanded ellipsoid set-membership filtering method, the problems of complexness in computation and low efficiency and computational accuracy in a method based on Taylor-series linear approximation are solved. The expanded ellipsoid set-membership filtering method comprises the following steps: establishing a nonlinear strapdown inertial navigation system equation and an observation equation; computing an indeterminate interval of a system state parameter component of a (k-1) step; carrying out Chebyshev polynomial approximation computation on the nonlinear equation and the observation equation of the inertial navigation system; computing an error boundary of the Chebyshev polynomial approximation computation, so as to acquire outsourcing ellipsoids of the Chebyshev interpolation polynomial approximation computation errors of the nonlinear system equation and the observation equation; and by virtue of a linear ellipsoid set-membership filtering method, computing and predicting an ellipsoid boundary of a state variable, updating a computation state ellipsoid boundary, computing an estimation value of a state parameter variable of a k step, and estimating variance matrix. The expanded ellipsoid set-membership filtering method has the beneficial effects that a computational accuracy is relatively high, the computational complexness of an algorithm is reduced, and the computational stability of the expanded ellipsoid set-membership filtering method is effectively guaranteed.

Provided is a time delay system PID controller stabilization method based on data drive. The time delay system PID controller stabilization method based on the data drive comprises the steps of firstly using relay identification of multiple frequency points, giving input frequency domain response data of a controlled time delay object and output frequency domain response data of the controlled time delay object, and extracting characteristic parameters; then obtaining the maximum permissible stabilization range of proportional gain k

in a PID controller through necessary conditions of PID stabilization; for a fixed k

value, obtaining a necessary and sufficient condition which can enable a closed-loop system to be stable, and determining a two-dimensional parameter domain which can enable the closed-loop system to be stable and relates to differential gain k<d> in the PID controller and integral gain k in the PID controller; and determining a two-dimensional stabilization domain with a convex polygon characteristic of the (k<d>, k) to ergodic points of each k

through going through the maximum permissible stabilization range of the k

, and obtaining a stabilization set of the PID controller. As long as a control parameter is selected from the obtained stabilization set of the PID controller, the stability of the closed-loop system can be ensured. According to the time delay system PID controller stabilization method based on the data drive, under the condition that a transfer function of the time delay object or a state space model of the time delay object does not need to be obtained, the PID controller stabilization method is offered based on frequency response data, complex calculation processes of pattern identification are avoided, and an approach which is simple and effective is offered for the design of a PID controller without a model time delay system.