79 results about "General algorithm" patented technology

The invention discloses a media access control (MAC) address hardware learning method and system based on a hash table and a ternary content addressable memory (TCAM) table, and relates to the MAC address learning field. According to the MAC address hardware learning method and system, when no MAC address conflict happens, the hash table is used for storing learned MAC addresses, and a static random access memory (SRAM) or a dynamic random access memory (DRAM) is applied to the hardware of the hash table; and when MAC address conflict happens, the TCAM table is used for caching conflicted MAC addresses, a TCAM storage is applied to the hardware of the TCAM, idle table items can be positioned through one-time searching due to the fact that parallel seeking is performed on the hardware of the TCAM, and the number of the table items of the TCAM is the number of the conflicted MAC addressed which can be practically cached. The MAC address hardware learning method is achieved on a general programmable exchange chip, does not need support of hardware circuits, is high in learning efficiency and small in occupied internal memory resources, is flexible in application due to the fact that the general algorithm is adopted, and can achieve complete control on conflict probability.

The invention relates to a method for applying a commercial on-spot programmable device to triple-modular redundancy anti-irradiation in an irradiation environment based on lookup table structure and a generic algorithm thereof, aiming at easing the problem that commercial FPGA chips are prone to cause overturning of programming point single particle in the irradiation environment due to irradiation energy energetic particles in the space. The method carries out classification according to user circuit logical type; the first type is input logic, the second type is non-feedback logic and the third type is feedback logic, the fourth type is output logic. In the method of the invention, different triple-modular redundancy anti-irradiation processing methods are proposed with regards to the 4 types of logic. The method of the invention is a universal method through which various user circuits are mapped to the commercial FPGA, features widespread representativeness, generality and practicability.

Methods for using modified single wall carbon nanotubes (“SWCNTs”) to detect presence and/or concentration of a gas component, such as a halogen (e.g., Cl₂), hydrogen halides (e.g., HCl), a hydrocarbon (e.g., C_nH_2n+2), an alcohol, an aldehyde or a ketone, to which an unmodified SWCNT is substantially non-reactive. In a first embodiment, a connected network of SWCNTs is coated with a selected polymer, such as chlorosulfonated polyethylene, hydroxypropyl cellulose, polystyrene and/or polyvinylalcohol, and change in an electrical parameter or response value (e.g., conductance, current, voltage difference or resistance) of the coated versus uncoated SWCNT networks is analyzed. In a second embodiment, the network is doped with a transition element, such as Pd, Pt, Rh, Ir, Ru, Os and/or Au, and change in an electrical parameter value is again analyzed. The parameter change value depends monotonically, not necessarily linearly, upon concentration of the gas component. Two general algorithms are presented for estimating concentration value(s), or upper or lower concentration bounds on such values, from measured differences of response values.

The invention relates to the field of advanced manufacture and automation, in particular to a low-temperature heat real-time optimization system based on the general algorithm sequential quadratic programming (GA-SQP) mixed optimization strategy, which comprises a real-time data base, a low-temperature heat system soft measurement module, an energy consumption optimization module, a user interface and a real-time information issuing module based on Flash. Compared with the prior art, the low-temperature heat real-time optimization system has the advantages that the flow process simulation technology and the exergy economics are used as the basis for building a low-temperature heat system simulation and optimization model, a mixed solving strategy of combining the classical mathematical programming sequence secondary planning SQP and the novel group intelligent optimization algorithm GA is adopted for solving the nonlinear optimization model, and the real-time data base technology is used for collecting real-time information in the production process, so the real-time monitoring, the off-line emulation, the on-line simulation and the real-time optimization are realized.

The invention discloses a Bayes' rule based multi-frame blind convolution super-resolution reconstruction method and device. The method includes steps of acquiring an interest area of a reference image and a matching area of a target image subjected to radiation correction through an image quality evaluation and frame selection algorithm for an image sequence of one scene; acquiring the radiancy and an accurate geometric distortion parameter through an image registration algorithm executed on the matching area of the target area subjected to radiation correction; acquiring a point diffusion function of image super-resolution restoration through execution of a multi-frame blind deconvolution image restoration algorithm on the accurate geometric distortion parameter; acquiring a super-resolution reconstruction image through execution of a maximum posterior super-resolution reconstruction algorithm on the radiancy and the point diffusion function of image super-resolution restoration. According to the invention, problems of insufficient consideration of point diffusion function, motion blur, image structure information, sparsity and the like of a traditional general algorithm are solved, automatic estimation on the system point diffusion function and multi-frame image registration parameters is performed, and the image resolution is improved.

A communication receiver which applies signal processing for quantitatively estimating receive signal factors such as communication channel quality, signal characteristics, and overall system received bit error rate (BER) or packet error rate (PER) and which applies a general algorithm for mapping these estimated factors to control receiver performance and minimize power consumption.

In Software defined elastic optical networks, modulation format and constellation size may be flexibly modified. As a result, digital signal processing (DSP) algorithm should be compatible with different modulation schemes or readily reconfigurable at the optical coherent receiver. Therefore we propose a novel cascaded adaptive blind equalizers based on decision-directed modified least mean square (DD-MLMS) algorithm for polarization separation and carrier phase recovery. The algorithm is square quadrature amplitude modulation (QAM) independent so that it could be applied in the elastic optical systems. The 28 Gbaud polarization multiplexing quadrature phase shift keying (PM-QPSK) and PM-16QAM back-to-back transmission is demonstrated. The results show that the performance is very close to the general algorithm but with a benefit of the reduced operation complexity. We transmit the 8×240 Gb/s PM-16QAM wavelength division multiplexing (WDM) signal over 1200 km standard single mode fiber (SSMF) based on the proposed blind equalization with a bit error ratio (BER) less than 2×10−2.

The invention provides a non-negative matrix factorization face recognition method and system based on kernel machine learning, which comprises five steps. The invention has the following beneficial effects: the invention avoids the learning of the inaccurate pre-image matrix by directly learning two kernel matrices, K_wx and K_ww, and avoids the derivation of the kernel function in the iterative formula by changing the learning object, so that there is no limit to the selection of kernel function and a general algorithm for any kernel function is obtained.

The disclosure is directed at a method and apparatus for determining virtual outputs for a multi-energy x-ray apparatus. Based on the application that the x-ray apparatus is being used for, a general algorithm can be determined or selected. Inputs received from the x-ray apparatus can be substituted into the general algorithm to generate a virtual output algorithm for the x-ray apparatus. Virtual outputs can then be calculated using the virtual output algorithm.

The invention discloses a message anomaly detection method based on deep learning. According to the method, firstly, data is preprocessed into a two-dimensional matrix form, and in order to reduce anoverfitting phenomenon easily occurring in a general algorithm model, a shuffle function is used for randomly disturbing the data to prevent local optimum, so that the model is easier to converge; then effective features are learned from the preprocessed data by using a convolutional neural network (CNN), and finally classification processing is performed on the obtained vectors through a supportvector machine (SVM) classifier. According to the method, the advantage of high-dimensional learning of the convolutional neural network of deep learning is utilized to learn the effective features ofthe network transmission message; the model provided by the invention is subjected to experimental verification on a Beijing University data set and is subjected to experimental comparison with othertwo models with better effects verified on the data set, experiments prove that the accuracy and the stability are greatly improved, and the training and testing time consumption is obviously reduced.

The present invention discloses an image denoising system based on a low-rank theory. An airspace image block matching technology is employed to preliminarily find image similarity blocks, performing matching of the image similarity at an SVD domain, improving the matching precision, and finally confirming the similarity blocks of a target image. According to the low-rand features of the similarity block, a matrix formed by the similarity blocks is subjected to singular value decomposition. About the weight determination problem of weight calculation of the singular value, the image noise intensity is considered, the complex degree of image details is considered, and the noise intensity and an entropy are employed to commonly determine the weight so as to finally realize the better denoising effect. The better matching effect can be obtained, the weight concept is utilized when the solution of a low-rank model, and the setting of the weight depends on the size of the singular value and also depends on an image entropy to allow the setting of the weight to consider the image details and the whole structure, obtain more accurate weight setting and obtain the denoising performance being higher than a general algorithm.

The invention discloses a face real time detecting method based on video and device thereof, belonging to the field of multimedia. In the invention, a video image frame is divided into a full detection frame and a predetermined frame; the type of the current input video image frame is judged according to the frame interval between the current input video image frame and the former full detection frame; and a corresponding detection way is adopted. As video sequence has predictable characteristics in a time-space domain, parts of the video image frame are detected by searching different regions by different step lengths, so that the method can efficiently reduce the searching time in the detecting process, avoid the shortage that the general algorithm based on AdaBoost cascade algorithm searches all the regions by fixed step length, greatly reduce the calculating complexity in the detecting process and guarantee the accuracy of the detection.

A system that facilitates composition of schema mappings. A general algorithm is provided for composing a broad class of mappings, where one or both mappings are not functions, such as constraints between two schemas and the inverse of functions. A composition component performs composition on schema mappings of disparate data sources, which schema mappings can be expressed by at least one of full, embedded, and second-order dependencies, wherein the second-order dependencies need not be in source-to-target form. The algorithm for composition further includes a procedure that tests whether the composition algorithm will terminate.

The invention discloses a real-time three-dimensional reconstruction method and system for a large-scale scene based on a line-of-sight updating algorithm, and belongs to the field of computer visionand robots. The invention aims to solve a problem of providing a method in which a light of sight is generated according to the current three-dimensional point cloud, data updating is realized and thus real-time reconstruction is performed in allusion to a problem that general algorithms cannot realize real-time reconstruction for large-scale point cloud data of laser radar. The real-time three-dimensional reconstruction method mainly comprises the steps of acquiring three-dimensional point cloud, calculating external parameter data of a sensor, calculating a symbol distance value of an implicit surface based on a line-of-sight algorithm, performing weighted fusion on the symbol distance value, performing volume rendering on volume data, storing the volume data and displaying a reconstruction effect in real time. The implicit surface is updated in real time through introducing the line-of-sight updating algorithm, so that real-time reconstruction for a large-scale scene based on depthsensors such as radar is achieved. The real-time three-dimensional reconstruction method and system not only have great advantages in speed, but also acquire good effects in reconstruction quality.

The invention discloses a method for rapidly searching frequency of a high transmission efficiency wireless electric energy transmitting system, wherein particle swarm sizes in a general algorithm are separated respectively as a maximum particle swarm size Nmax =30 and a minimum particle swarm size Nmin=2; the particle swarm sizes are gradually decreased with the increase in number of iterations; and the overall decreasing approach of the particle swarm sizes is similar to an exponential change curve. According to the invention, in the early stage of searching, the particle swarm sizes are slowly changed, which facilitates to universal search; in the later stage of searching, the particle swarm sizes are changed to be minimum, thus reducing redundant particles, simplifying the algorithm and quickening the convergence speed of the later algorithm; by adopting the algorithm of the invention, the selection of the particle swarm sizes has evidence to find; in the early stage of searching, the algorithm has great potential of self learning ability and social learning ability; and in the later stage of searching, the convergence speed is quickened, thus saving the searching time of the algorithm.

The invention discloses a road section recognizing and matching method based on decision-making circle and is mainly applicable to the path recognition of a vehicle navigation system and other path recognition fields employing positioning technology. The invention also solves the problem of inaccurate recognition of complicated road section of the vehicle navigation system. Decision-making circles are arranged in the road section areas difficult to be matched with the general map matching method, accurate points of all road sections in the decision-making circles are collected, the GPS position points of vehicles in the decision-making circles are matched with the accurate points through point-to-point mode, and the number of successful matches of the accurate points in each road section is under statistical comparison to determine the road section wherein the vehicle is located. The method overcomes the inaccurate matching problem of the general algorithm, also avoids erecting the site beacon station equipment and accordingly saves large quantity of human and material resources.

The invention discloses a multi-service processing model and a multi-service processing method in a communication test system. The processing model comprises a state processing end and a controlling and scheduling end which are in signal connection, the state processing end is used for concurrently processing each circulating state of test task services, and the controlling and scheduling end is used for managing and controlling the test task services. By the aid of a matrix state machine and a general algorithm model, a thread can use fragmentary time slots for processing tasks in multiple seats; and multiple threads can process multiple high-capacity services, CPU (central processing unit) time fragments are used fully, and high-capacity multi-service processing difficultly achieved by a serial control mechanism is achieved. By the multi-service processing model and the multi-service processing method, dependency on hardware is weakened effectively, so that the services are maintained and expanded more easily.

A generalized hardware architecture that supports built-in self testing (BIST) for a range of different computer memory configurations and a generalized BIST algorithm can be compiled, based on specified configuration characteristics (e.g., the number of write ports, the number of read ports, the number of entries, and the number of bits per entry in the computer memory), to generate the hardware design for a particular computer memory system. In one embodiment, the generalized hardware architecture includes a multiplexer block that enables a single BIST comparator to be multiplexed for use in performing BIST testing via different read ports of the computer memory.

The invention relates to a simulation system and method for multi-agent group behaviors. The system comprises a simulation engine layer, a simulation component layer, a system application layer, a module model library and a behavior node library, the simulation engine layer comprises a simulation world class, a simulation scene class, a simulation scheduler, a time controller, an entity element class, a simulation event, a behavior node class and a knowledge sharing blackboard class, and the simulation component layer comprises an agent entity model, an agent module model, an entity management model, a component management model, an event management model and a behavior management model. The system application layer comprises a plurality of agent model components, and the module model library comprises a motion class module, a perception class module, a communication class module and a decision class module; the behavior node library comprises a general algorithm node, a group behavior node and a service interface node. By adopting the system, multi-agent behavior simulation can be realized.

The invention provides an algorithm for generating a unique packet ID of a financial data exchange message. The algorithm for generating a unique packet ID of a financial data exchange message comprises the following steps: generating the network adapter MAC address of the packet ID computer; generating the local time of the the packet ID computer; obtaining the PID of the process; accumulating numbers; and adding the field of the local pointer. The beneficial effect of the invention is that the algorithm for generating a unique packet ID of a financial data exchange message is a general algorithm in a variety of commonly used operating system (Windows, Linux, AIX, HP-UX), and can guarantee the uniqueness of less than a million message packet ID within a second in the whole system at the same time.