36results about How to "Reduce detection delay" patented technology

The invention discloses a coordinated detection method of an NDN low-speed cache pollution attack, which can be used for detecting attack behaviour through calculating multilayer node request change rates on a transmission path, thereby fusing nodes in each layer and correlation of request change rates of nodes in a first layer. The method of the invention can ensure high correct detection rate under occasion of the low-speed cache pollution attack, and simultaneously reduce detection delay of a dispersed attack by cooperating with more than three layers of routes. The method of the invention can be used for effectively detecting a low-speed concentrated attack and the dispersed attack simultaneously and improving detection performance by sacrificing space complexity. The method of the invention can be applied to detect a cache pollution attack of named data networking.

The application relates to the field of wireless communication, and provides a method for acquiring control resource sets. The method comprises the following steps that: a terminal device receives atleast one piece of indication information from a network device, wherein at least one piece of indication information is used to indicate a first time domain resource location, and the first time domain resource location is unavailable for control information transmission; the terminal device acquires a second control resource set according to at least one piece of indication information; and theterminal device detects the control information on the second control resource set. The method reduces the signaling overhead caused by the reconfiguration for the control resource sets by the high layer signaling, and reduces the control information detection delay.

There is provided a signal detecting method using constellation set grouping in a spatial multiplexing multiple input multiple output system. The signal detecting method includes dividing a set of candidate symbols, a constellation set into a plurality of subsets by grouping the constellation set; dividing a tree search process of a QR-decomposition with M-algorithm (QRDM) algorithm into a plurality of partial detection phases; and performing the plurality of divided partial detection phases in parallel or iteratively.

The embodiment of the invention provides a method and a device for detecting a physical broadcast channel. The method comprises the following steps of: collecting first wireless frame data; performing physical broadcast channel detection on the first wireless frame data; and finishing the current detection if the physical broadcast channel information is detected. By applying the embodiment of the invention, when the data is less than 40ms, the required physical broadcast channel (PBCH) information can be acquired by traversing and analyzing data at different positions in a PBCH Buffer. Undernormal condition, the PBCH information can be detected in 10ms, so the detection delay is greatly shortened, and guarantee is provided for other service operation, such as user equipment (UE) accessing, switching and the like.

The invention provides an industrial product quality real-time monitoring method, equipment and system, relates to the technical field of networks, and aims to reduce the detection delay, facilitate industrial control equipment to quickly screen industrial products according to an analysis result of an edge cloud platform, improve the detection precision and the working efficiency and reduce the production cost of enterprises. The method is applied to an edge cloud platform, the edge cloud platform is in communication connection with industrial control equipment and a central cloud platform, and the method comprises the following steps: receiving image data of an industrial product sent by the industrial control equipment; receiving a detection model sent by the central cloud platform; utilizing the detection model to analyze and process the image data to obtain an analysis result; and feeding back the analysis result to the industrial control equipment to enable the industrial controlequipment to screen the industrial products according to the analysis result. The method is mainly used for monitoring the quality of industrial products in real time.

The invention provides sending and receiving methods, sending and receiving devices and a transmission system for a synchronizing signal. The sending method comprises the following steps that a base station determines one or more sets of system parameters, wherein each set of system parameters include frequency information of a carrier frequency and/or frame structure parameters of the carrier frequency; the base station constructs the synchronizing signal of a predetermined structure according to the system parameters; and the base station sends the synchronizing signal to a terminal, whereinone or more sets of system parameters are corresponding to the same predetermined structure. Through the sending and receiving methods, the sending and receiving devices and the transmission system for the synchronizing signal, a problem of high complexity during detection of the synchronizing signal in the prior art is solved.

The invention provides a cognitive radio spectrum sensing method, belongs to the technical field of cognitive radio and relates to a rapid CUSUM detection technology. According to the cognitive radio spectrum sensing method, by further improving and applying a non-parameter CUSUM detection algorithm to spectrum detection, the shortcomings of an existing rapid detection method can be overcome under the conditions that no signal priori knowledge exists and signal appearing moment is random, and signals can be rapidly detected. The cognitive radio spectrum sensing method can dynamically adjust offset according to the detection situations and further shorten detection delay.

The invention relates to the technical field of radar target detection, and in particular, relates to an FPGA-based two-dimensional ordered statistical constant false alarm detector implementation method. According to the method disclosed by the invention, detection is carried out in each clock period from two-dimensional power matrix input, so that the repeated reading time delay of the data cache is reduced, and the detection speed can be effectively improved. Aiming at the condition of large calculated amount in a traditional OS-CFAR (Ordered Statistical Constant False Alarm Rate) sorting process, the FPGA implementation method is completed by adopting parallel comparison, so that the sorting complexity is reduced. The reusability of a module is fully considered, two-dimensional slidingwindow structure setting is completed through a shifting register set, two-dimensional OS-CFAR detection is achieved, and BRAM memory resources and DSP resources of the FPGA can be saved.

The invention discloses a single-phase voltage sag quick detection method based on a morphological filter and derivation method [Alpha][Beta]-dq transformation. The method comprises the following steps that: S1: adopting a structural element of which the cosine shape and the triangle are combined according to a certain ratio to carry out primary filtering on a detected single-phase voltage signal;S2: using a signal subjected to primary filtering through a combined-form filter for derivation, and constructing [Alpha][Beta] phase voltage; S3: using a cosine-form filter to filter noise signal interference amplified by differentiate operation; S4: on the basis, through dq transformation, using a linear type filter to filter a non-direct-current amount from a dq transformation result; and S5:calculating the amplitude and the phase angle of voltage sag. By use of the method, the amplitude, the time of duration and the phase change of the voltage sag can be quickly and accurately detected.

The invention discloses a method and device for switching an overtime period, and communication equipment. When a transmission link between first communication equipment and second communication equipment has other communication equipment, the first communication equipment can switch a long overtime period into a short overtime period, thereby improving the link detection efficiency, and timely carrying out the corresponding processing to reduce the cutoff time of the communication equipment when the transmission link has an accident. The method comprises the steps that the first communication equipment determines whether the transmission link between the first communication equipment and the second communication equipment has third communication equipment or not; the first communication equipment enables the overtime period for detecting the transmission link to be switched to a second overtime period from a first overtime period when the transmission link has third communication equipment, wherein the first overtime period is greater than the second overtime period.

The invention discloses a MIMO-based signal detection method. The method comprises: a detection platform receiving a signal r and a channel estimation matrix H through multiple antennas; and the detection platform, according to the received signal r and the channel estimation matrix H, performing parallel processing by use of a single instruction multiple data (SIMD) instruction set, and obtaining a UE sending sequence. According to the invention, the parallel processing of MIMO detection is realized by use of a SIMD instruction, therefore, high-complexity operation including matrix inversion, vector multiplying and the like can be avoided, and detection time delay is reduced. Besides, since the method and platform are realized based on a general-purpose processor (GPP), the versatility is quite good, and manpower resources can be saved.

The invention discloses an active power filter direct current control method suitable for the condition of a weak power grid. The method is implemented according to the following steps: Step 1. voltage of a PCC point of a weak power grid system, inverter direct current side voltage, an instantaneous value of load current and an instantaneous value of current emitted by the inverter are collected; Step 2.the collected instantaneous values and the instantaneous value of current emitted by the inverter are processed through a conditioning circuit and is input to a DSP to be converted to digital signals; Step 3. the DSP processes the digital signals to obtain instruction current signals of the active power filter; Step 4. the DSP performs hysteresis comparison on the instruction current signals and the digital signals, and is controlled to emit PWM waves; and Step 5. the emitted PWM waves are sent to a drive circuit of an IGBT module of the inverter, the inverter is controlled to emit current according to the instruction current signals, and harmonic waves and reactive power in a power grid system are compensated according to the emitted current. The active power filter direct current control method suitable for the condition of the weak power grid effectively and accurately compensates reactive current and harmonic current of a load.

The invention discloses an integrated detection method of an edge side cloned node based on a counterpropagation neural network. The method comprises the following steps: S1. collecting, by an edge side computing node, a data set; S2. training and testing a BPNN by using the data set; S3. waiting for a new information packet; S4. extracting channel information from the information packet, storingreference channel information, and calculating a channel difference value; S5. accumulating the credibility of each node; S6. inputting the credibility of each node into the BPNN to judge whether a clone attack exists; and S7. if no clone attack exists, updating the reference channel information, and if the clone attack exists, sending a clone attack alarm. According to the integrated detection method disclosed by the invention, integrated detection is performed on a data source node on the edge side node by using the BPNN, meanwhile whether the clone attack exists in multiple nodes, thus improving the detection efficiency of the cloned node and reducing the network transmission load and the load of a central network. According to the integrated detection method disclosed by the invention,the influence of random noise of a channel is also reduced by accumulating the credibility and classifying the BPNN, and the accuracy of the detection of the cloned node is improved.

The invention discloses a robot collision detection method based on a second-order generalized momentum observer. The method comprises the following steps: firstly, constructing a robot kinetic model, and recognizing kinetic parameters; secondly, establishing a generalized momentum observer, determining a gain coefficient, establishing a friction model in a targeted manner, and identifying model parameters; and thirdly, a second-order generalized momentum observer is established through a second-order damping model, a PD regulator is connected in series on the basis of the second-order damping model, and a threshold value is set. According to the robot collision detection method based on the second-order generalized momentum observer, adjustable parameters are increased, system controllability is improved, short transition time is easier to obtain, system collision detection delay is reduced, and the application value is high. The method can be applied to the collision detection technology.

The embodiment of the invention provides a face feature detection method and device, a medium and electronic equipment, and relates to the technical field of artificial intelligence. The method comprises the following steps: acquiring a to-be-detected image; inputting the to-be-detected image into a human face feature detection model, and outputting human face region coordinates and human face key point coordinates corresponding to the to-be-detected image, wherein the human face feature detection model comprises a target human face region detection network and a human face key point detection network; and marking the to-be-detected image through the human face region coordinates and the human face key point coordinates, and generating the to-be-detected image marked with the human face region and the human face key points. According to the technical scheme of the embodiment of the invention, the face region coordinates and the face key point coordinates can be output at the same time, the image containing the face region labels and the face key point labels can be quickly obtained, and the face feature extraction efficiency is effectively improved.

The invention discloses a deep learning-based point-by-point classification fault detection method (DPCFD), and the method specifically comprises the steps: collecting the data of each channel of an industrial system, and obtaining an original data sequence; inputting the original data sequence into a pre-trained sequence state generator model to generate a real-time state sequence of each channel; splicing the real-time state sequence of each channel and the original data sequence according to the time dimension to obtain a fused data sequence, grouping the channels according to the incidence relation between the channels, and inputting the fused data sequence into a pre-trained fault detection model based on deep learning point-by-point classification according to the channel grouping to obtain a sequence of the fault detection results. According to the method, the DPCFD method is evaluated by using a standard data set Tennessee Eschermann, and experimental results show that the method has the advantages of high detection performance and low detection time delay.

Embodiments of the present invention provide an information detection method and user equipment, which relate to the communication field and enable the user equipment to reduce detection delay, power consumption and detection complexity without knowing the channel environment where it is located. The method is as follows: first determine the reference information, then determine the detection level of at least one target information in the main information block, downlink control information, and system information block according to the reference information, and then perform the detection level of the target information according to the detection level of the target information. detection to obtain the target information. Embodiments of the present invention are used for detection of information.

The invention provides an in-bed and off-bed detection method. The method comprises the following steps: providing a neural network and a training signal, and dividing the training signal into a static signal, a body movement signal, a discharge signal and a stable signal as a template signal group; training the neural network to obtain a trained neural network; inputting continuous online signals collected within a predetermined time period as unit input signals into the trained neural network, and outputting state information corresponding to the unit input signals by the trained neural network; comparing the state information of two unit input signals adjacent in time sequence according to a preset rule, and outputting an in-bed result or an off-bed result; and judging the in-bed state and the off-bed state according to the in-bed result or the off-bed result, so that the in-bed and off-bed judgment accuracy is improved, and the detection time delay is reduced. The invention further provides a detection system which comprises a signal processing module, a training module and a judgment module. The invention further provides equipment and a storage medium.