295results about How to "Simplified Computational Complexity" patented technology

The invention discloses a navigation method based on iterative extended Kalman filter fusing inertia and monocular vision. The method is as follows: A monocular camera and an inertial measurement unitare mounted on the carrier. A message filter in ROS is used to realize that time stamp synchronization of the monocular camera and the inertial measurement unit. The position, velocity and rotation obtained by IMU are taken as the state variables of the system, and the position and attitude information obtained by vision sensor is used as the observation variables to establish the system equation. The position, velocity and rotation obtained by IMU are used as state variables of the system. The information obtained from the two sensors is fused by an iterative extended Kalman filter to realize the real-time state estimation and navigation of the carrier. The invention can maintain high precision in the long-time real-time positioning and navigation process, and has the advantages that thecomputational complexity between frames does not change.

The invention discloses a high-speed train tracking running curve optimization setting method. According to the characteristic of 'movable and dynamic length' of a tracking section of a high-speed train under movable blocking condition, the method establishes a high-speed train echo state network speed prediction model, a movable blocking based tracking running model, a line network and a tracking running curve multi-target setting model adopting innovative evaluation indexes based on line and high-speed train running data acquired in a site; an efficient multi-target particle swarm optimization is adopted to use an algorithm convergence condition as one of model setting constraints, and high-speed train tracking running curve optimization setting is performed based on the real-time data; finally, section operation efficiency and stability are used as the evaluation indexes of the setting method, and a group of optimal running curves are screened out, so that the high-speed train running process is safe and efficient, and meanwhile the high-speed train section operating efficiency and stability under the movable blocking condition are improved.

The invention discloses a rapid correction method for scanning a document image. A detection step is calculated according to the size of the image; four lines are fixedly detected, and the maximum number of points of each line is 100, so the maximum number of characteristic points of a straight line is no more than 400; therefore, the calculated amount of Hough transformation during straight line detection is reduced and the stability is improved; the Hough transformation with a limited included angle is adopted to further improve the efficiency of the straight line detection; an inclined angle is calculated according to parallel lines, so the algorithm can process a trapezoidal document image; the calculation of an intersection is determined according to a parametric equation of two straight lines; when the image rotates, an effective image region is only processed, the process of interpolation calculation of a black background is avoided, and the processing efficiency is improved; and the document image is partitioned for processing, and the interpolation calculation is determined according to a partitioning characteristic so as to improve the execution efficiency of a correction algorithm; and quality optimization adopts a grey scale compensation method so as to achieve better visual effect.

The invention discloses a method and a device for evaluating the voice quality of a voice over Internet protocol (VOIP). The method comprises the following steps of: monitoring and capturing a data packet in real time; judging whether the monitored and captured data packet is a preset data packet of a VOIP client or not, and arranging the monitored and captured data packet into a data packet queue if the monitored and captured data packet is the preset data packet of the VOIP client; performing voice stream processing on the data packet arranged into the data packet queue, and acquiring a voice data packet; and performing voice quality evaluation coefficient calculation according to the acquired voice data packet, and evaluating the voice quality. By the method and the device, voice quality evaluation reliability can be improved.

The invention discloses an automatic gain control method and an automatic gain control circuit which are suitable for an orthogonal frequency division multiplexing (OFM) system. The method comprises the following steps of: measuring a baseband signal; and adjusting gain. Slide window processing is performed during signal measuring so as to average signal energy in a window. A gain adjustment algorithm determines reasonable gain of the next adjustment period through conditions such as the gain of an upper frame, a measured value of the upper frame, the number of overflow sampling points, the receiving signal intensity indication on the current antenna and the like. Simultaneously, the gain of a radio frequency receiving chip is changed by circulating prefix time so as to track an OFDM symbol level.

This invention discloses a method for selecting interframe prediction mode in video image interframe prediction coding process, which contains dividing video image sequence into different area according to different attribute, limiting the selectable interframe prediction mode of each image according to the block scale distribution property of different image area, selecting corresponded interframe prediction mode and coding in limited interframe prediction mode for each macro block in each image area. Said invention simplifies the selection process and raises efficiency and communication effect.

The invention discloses a fire image recognition method based on a mixed feature and manifold learning. The method comprises steps of: firstly dividing an image into a plurality of nonoverlapping sub-blocks by using a block dividing strategy, and detecting whether the sub-blocks are candidate fire areas by establishing two color modules in the HSV color space and a similarity matching method basedon a color histogram; secondly, in view of the significant visual characteristics of a flame area and a smoke area, using a hybrid feature extraction method in combination with local characteristicsand texture features to capture more image details and improve the accuracy of subsequent classifications; and finally, using a manifold learning method to construct a flame manifold and a smoke manifold based on double manifold topology, and establishing a classifier for final determination of the fire image on the two types of image manifolds. The method not only reduces the burden to the classifier caused by high-dimension feature, but also obtains high fire image recognition accuracy.

The embodiment of the invention discloses fault-tolerant processing method and device of a disk array and a fault-tolerant system. The fault-tolerant processing method of the disk array comprises the steps of: reading p data blocks of a first horizontal checking group stored in the disk array, wherein the first horizontal checking group comprises a first horizontal checking block and the P data blocks, and P is a positive integer; obtaining the first horizontal checking block by carrying out xor operation on the read P data blocks of the first horizontal checking group; reading p data blocks of a first slant checking group stored in the disk array, wherein the first slant checking group comprises the first horizontal checking block, a first slant checking block and the P data blocks; obtaining the first slant checking block by carrying out the xor operation on the first horizontal checking block and the read P data blocks of the first slant checking group; and writing the obtained first horizontal checking block and the obtained first slant checking block into a corresponding storage unit. The embodiment of the invention can relatively reduce the complexity of the fault-tolerant computation of a disk and enhance the enablement.

The invention discloses a lithium-ion battery SoC (State-of-Charge) estimation method based on improved and self-adaptive dual unscented-Kalman-filters. The method mainly comprises the following steps: 1) establishing a state filter and a parameter filter of a lithium ion power battery based on an equivalent circuit model; 2) coupling the state filter and the parameter filter of the lithium ion power battery based on the equivalent circuit model, and building dual unscented-Kalman-filters; and 3) inputting operation parameters of a to-be-detected lithium ion power battery into the dual unscented-Kalman-filters, and carrying out parameter correction and stage-of-charge (SoC) estimation on a lithium ion power battery equivalent circuit model. According to the method in the invention, the effectiveness of cholesky decomposition is guaranteed, the problem that iteration is stopped due to the fact that a covariance matrix is indefinite caused by reasons such as an initial value error, noisedisturbance, calculation module floating point error and the like is overcome, and the numerical stability of the filtering process and the robustness of the algorithm are enhanced.

The invention discloses a velocity model constructing and calculating method for ground monitoring microseism location, wherein the model is constructed based on a geophysical microseism linearization location method and an anisotropic average velocity model, in order to achieve construction and optimization solution of the three-dimensional anisotropic average velocity model, in comparison with the traditional laminated velocity model, the velocity model is closer to the actual simulation formation velocity so as to achieve a simple and reasonable calculating process, at the same time, through the velocity model constructing and calculating method, the laminated velocity model error caused due to ray tracing differentiation is also prevented; through the method, a residual vector between observation time and calculated travel-time difference of an appointed detector within a work area range and the optimization solution model are constructed, the least square solution of the velocity model can be obtained by iterating the model and inverted into the optimal velocity model, and crack events can be precisely located through the velocity model.

The invention relates to a comprehensive optimization system for a scheme of access of distributed power supplies and a microgrid to a power distribution system. The comprehensive optimization system includes: a database module used for storing various index models, each index model including at least one index; an input module used for calculating index data in a certain access scheme according to the index models in the database module; an analysis module used for reducing indexes according to relations between the index data and calculating a fuzzy membership degree value of each index after reduction; a comprehensive assessment module used for utilizing a combination weighting method to obtain a weighted value of each index, and calculating a comprehensive assessment score of the certain access scheme according to the fuzzy membership degree value and weighted value of each index; and an optimized output module used for obtaining an optimal access scheme according to the comprehensive assessment scores of a plurality of access schemes. Compared with the prior art, the comprehensive optimization system provided by the invention has the advantages of being high in efficiency and integration, being tightly combined with engineering practice, etc.

The invention provides a color image digital watermarking method based on a multi-transform domain. The method comprises the steps of, firstly, performing sub-channel DWT processing on a color image in combination with discrete wavelet transform (DWT), quaternion discrete cosine transform (QDCT) and singular value decomposition (SVD); then describing homogeneous frequency sub-bands of the three channels with a quaternion; then performing blocking according to a watermark size, performing DQCT on each sub-block to form a coefficient matrix; and finally, embedding a watermark into the coefficient matrix on the premise of guaranteeing visual perception quality. The invention provides a new color image watermarking method. For the fact that an existing color image digital watermarking algorithm has room for improvement in the relation of balancing robustness and transparency, the advantages of each transform method are fully utilized, and the robustness and embedding capacity of the watermarking algorithm are improved on the premise of guaranteeing the transparency.

The invention provides an automatic shockable rhythm identification and classification method combined with electrocardio time-frequency domain feature analysis. The method comprises specific steps as follows: S1, pretreating electrocardio signals; S2, automatically identifying cardiac arrest rhythms, and if discrimination conditions are not met, implementing S3; S3, on the basis of an integral coefficient band-pass filter, calculating the maximum amplitude proportion value (Pa), the average amplitude proportion value (Pb) and the average deviation proportion value (Pc) of output signals; S4, S5, S6 and S7, discriminating shockable rhythms and non-shockable rhythms according to frequency domain feature values such as the Pa, the Pb, the Pc and the like, and implementing S8 in case of failure; S8, calculating an electrocardio standard grid bar projection standard deviation; S9, discriminating the shockable rhythms and the non-shockable rhythms according to the standard deviation. The method can be applied to instruments and equipment which automatically identify and classify the shockable rhythms according to body surface electrocardiograms, the shockable rhythm identification sensitivity and the non-shockable rhythm specificity are improved, and the algorithm operating efficiency is improved.

The embodiment of the invention provides an information recommendation method, a device, a system and a storage medium. The method comprises the steps of receiving a recommendation request initiated by a client for a target user; querying a preference object set of the target user and a similar object set corresponding to each preference object in the preference object set; determining a similarity score of the target user and each similar object in the similar object set based on the loaded preference object set and the similar object set; and sending recommendation information correspondingto the similar objects of which the similarity scores meet the recommendation conditions to the client.

A minimum sum decoding method for quantization of low density odd-even check codes is a circulation method including the following steps: 1, using information received by a channel to initialize a varible node decoder, 2, every variable node inputs the information to a check node connected with it by the edge, which computes related logarithm likelihood ratio information , 3, the check node carries out equal distance quantization then transmits it to an adjacent variable node decoder, 4, every check node inputs the information to a variable node connected with it by edge to compute related logrithm likelihood ratio information, 5, carrying out hard judgment to the logrithm likelihood ratio information output by step 4 and stopping the decoding if the code meets a check matrix and outputting successful information, if iteration time reaches to a preset maximum one, then the decode is stopped and fail information is output, otherwise it is switched to step 2.

The present invention discloses a method for detecting the signal in the multi-antenna digital radio communication system; after the emitting terminal in the MIMO system codes the emitted symbols, the symbols reach the receiving terminal through at least one emitting antenna and two different channels; the method for the receiving terminal to detect the symbols emitted by the emitting terminal comprises that the receiving terminal obtains at least two receiving signals and estimates the channel to obtain the channel matrix; and then with the channel matrix, the factorized matrix of the estimated error and covariance of the symbols emitted by the transmitting terminal in the pattern of recursion is calculated, and then based on the obtained factorized matrix, the symbols are detected. With the method disclosed by the present invention, the calculation complexity for detecting signal can be reduced.

The invention discloses a power distribution network toughness three-stage evaluation method in typhoon weather, a storage medium and equipment, and the method comprises: simulating and analyzing theimpact on a power distribution network from a typhoon disaster and the response process of the power distribution network to the typhoon disaster when the typhoon disaster does not happen, and carrying out the statistical calculation of a pre-disaster toughness index of the power distribution network; in the typhoon disaster occurrence process, according to the real-time data returned by the powerdistribution network data acquisition and monitoring control system, calculating the toughness index in the power distribution network disaster; after typhoon departure, acquiring actual data of emergency response and first-aid repair of the power distribution network, and calculating a post-disaster toughness index of the power distribution network; and quantifying the three-stage toughness level of the power distribution network, and quantifying the pre-disaster strength degree, the in-disaster resistance, the post-disaster recovery efficiency and the comprehensive toughness of the power distribution network for dealing with typhoon disasters. The method can be used for guiding power distribution network element reinforcement when typhoon does not occur, emergency control in the typhoondisaster process and power restoration after typhoon disasters, and provides a quantitative basis for system planning, operation scheduling and decision recovery.

The invention discloses a new method for objectively estimating image fusion quality without reference image, which can overcome the disadvantages of a conventional estimation method. The method is characterized in that the method for objectively estimating image fusion quality is a method for estimating the fusion effect by using similarity of gray scale, namely measuring the fusion effect based on a color likelihood function of a Minkovski distance and weighting the color likelihood function value with partial obvious degree of each source image by taking account of both calculation complexity and partial information content. Compared with the conventional estimation method, the method is much closer to a visual physical model of a person, and a result which meets the subjective estimation standard well is obtained, the number of the input images is not limited to two and the number can be expanded to be any positive integer.

The invention discloses a non-maximum suppression, dynamic threshold calculation and image edge detection method. The detection method comprises the following steps: eliminating Gaussian noise in an original image by Gaussian filtering; obtaining the gradient of each pixel point of the image obtained after Gaussian filtering; carrying out non-maximum suppression processing by utilizing the gradient amplitude and the gradient direction of each pixel point to obtain a candidate edge image, marking pixel points serving as candidate edge points in the candidate edge image, calculating a dynamic threshold value of a target body contour edge point in the image, and screening the candidate edge points by using the dynamic threshold value to obtain an edge image. According to the invention, the gradient direction is determined by comparing the gradient amplitudes in the horizontal direction and the vertical direction; Therefore, the calculation of the gradient direction angle is avoided, the calculation complexity of edge detection is simplified, the dynamic threshold calculation method can effectively distinguish the pseudo edge and the contour edge of the target body caused by the surface texture of the target body in the image, and more accurate edge information is provided for target body identification.

The invention provides a self-adaptive bitstream switching method and system based on cache underflow probability estimation. The method includes the steps of 101) estimating a mean valve of video segment downloading time of each bitstream and a variance of the video segment downloading time of each bitstream at the current network conditions, 102) modeling arrival and departure of video data in a client cache into an Ek/D/1/N queuing model, setting parameters of the queuing model according to the mean values and the variances, and for each bitstream, utilizing the queuing model with the determined parameters to calculate the probability that cache queues are empty so as to obtain the underflow probability of each bitstream, 103) setting the underflow risk gain or loss of the current bitstream and the quality gain of each bitstream, and calculating comprehensive profit values according to the underflow risk gain or loss of the current bitstream, the quality gain of each bitsteam and the underflow probability of each bitstream when switching is performed between the bitstreams, and 104) selecting the bitstream with the highest comprehensive profit value to be switched , wherein video segments are obtained through equal duration division of copies of the bitstreams.

The invention provides a hybrid satellite communication modulation identification method and system based on a constellation diagram and deep learning, and the method comprises the following steps: 1,a receiver obtaining a preset signal through spectral analysis, and carrying out the carrier frequency estimation, bandwidth estimation, band-pass filtering and down-conversion, thereby obtaining a baseband signal; 2, estimating a timing error, and carrying out interpolation filtering on a non-optimal sampling data point to approach an optimal sampling point; 3, performing phase difference on theoptimal sampling point to eliminate the influence of frequency offset, and recovering a constellation diagram after phase difference; and 4, clustering the constellation diagram through a machine learning method, and performing modulation mode classification through features of clustering points. On the basis of a traditional modulation recognition method, fine classification and recognition arecarried out through a mean shift clustering method, the recognition accuracy can be improved through combination of the two methods, meanwhile, the calculation complexity is simplified, and good balance is achieved between the accuracy and the complexity.

The present invention discloses an interaction platform based method for rapidly detecting a text in a complex background. The method comprises the following steps: S1: inputting an image for preprocessing; S2: rapidly positioning of a text candidate area: performing contour detection on the image processed in the step S1, and performing frame selection on each closed area by using a rectangular frame, then rapidly positioning all angle points in each rectangular frame by using an SIFT algorithm, and performing preliminary screening by using the number of the angle points as a preliminary screening condition; S3: firstly adjusting the image to a uniform size by using a normalization algorithm, then projecting contents in an original image to an exact center of the normalized image by a forward mapping method, and correcting an angle appropriately; and S4: text/background screening: extracting a feature firstly, and using a candidate area that is screened by a trained classifier as a detected text area. According to the method provided by the present invention, text detection in a complex background is realized, and a major problem that is solved is how to rapidly position a horizontal text and a text with a rotation angle in the image in the case of maintaining relatively high accuracy.

The embodiment of the invention provides a polar code encoding and rate matching method, which comprises the steps of determining one or more rows to be deleted of a generator matrix, wherein the generator matrix is determined by the preset code length of a mother code, and a column where '1' of the one or more rows to be deleted is located includes at least one column with a column weight being 1; deleting a row corresponding to a polar channel with the minimum degree of reliability in the one or more rows to be deleted, and deleting the column with a column weight being 1 in the columns where '1' of the row is located to obtain a deleted generator matrix; using the deleted generator matrix as a generator matrix again for repeating the steps until the order of a final generator matrix is equal to the target code length; and performing encoding and rate matching on a bit to be encoded according to the final generator matrix. Accordingly, the reliability degree sequence is not required to be repeatedly calculated, and thus the calculation complexity can also be greatly reduced.

The invention provides a signal-to-noise-ratio estimation method which is used for estimating the signal to noise ratio of a receiving signal according to pilot frequencies inserted into the receiving signal. The signal-to-noise-ratio estimation method includes the following steps: S1, a pilot frequency numerical value Xm, k, a channel estimation value Hm, k and Gaussian white noise Nm, k of the positions where the pilot frequencies are located are obtained from the receiving signal, wherein the m and the k show that the corresponding pilot frequencies are located at the mth data symbol and the kth subcarrier; S2, pilot frequency position information Ym, k of the positions where the corresponding pilot frequencies are located is obtained according to the pilot frequency numerical value Xm, k, the channel estimation value Hm, k and the Gaussian white noise Nm, k; S3, a signal-to-noise-ratio estimation value of the receiving signal is obtained according to the pilot frequency numerical value Xm, k, the channel estimation value Hm, k and the pilot frequency position information Ym, k. By means of the signal-to-noise-ratio estimation method, under the condition that the number of the pilot frequencies inserted into data symbols is limited and a large amount of statistics cannot be carried out, contiguous items between the noise and the signal can be eliminated, the accuracy and the stability of the algorithm estimation value can be optimized, and the computing complexity can be simplified.

The invention discloses a fast dynamic spectral data extraction method, belonging to the technical field of the spectral analysis. A photoelectric volume pulse wave is obtained in preset time, preferably in 1-6 seconds, a frequency f is calculated by a photoelectric volume pulse wave, and a sampling frequency fs is set as 4M times of the frequency f, wherein M is an integer larger than 1; the all-wave photoelectric volume pulse wave is continuously collected in the preset time, preferably in 1-6 seconds by using the sampling frequency fs, an equivalent absorbency A of the photoelectric volume pulse wave under each wavelength is calculated by a fast digital phase-locking method, and one real-time dynamic spectrum is formed; the above steps are repeatedly performed and after more than five real-time dynamic spectrums are extracted; and the real-time dynamic spectrum containing thick error is eliminated by counting the average effect, and the residual dynamic spectrums are superposed and averaged to obtain a final dynamic spectrum to output. The method reduces the calculation complexity and calculation amount, and increases the signal-to-noise ratio of the final dynamic spectrum.

The invention discloses a mixed Gaussian noise sparse Bayesian frequency spectrum sensing method which comprises the following steps: 1) constructing a compression frequency spectrum sensing system model affected by the mixed Gaussian noise; 2) exploring sparsity of a master use power spectrum signals according to the compression frequency spectrum sensing system model; 3) utilizing the sparsity of the master user power spectrum signals to reconstruct the master user power spectrum signals and further judging whether channels are occupied or not. The mixed Gaussian noise sparse Bayesian frequency spectrum sensing method disclosed by the invention is based on a virtual reference grid point scheme and utilizes a layered prior variational Bayesian algorithm to reconstruct power spectrum information of the master user power spectrum signals; thus, convenience is brought to secondary users to use limited frequency spectrum resources. According to the mixed Gaussian noise sparse Bayesian frequency spectrum sensing method disclosed by the invention, effects of the mixed Gaussian noise to recognizing a wireless system are taken into consideration; furthermore, the reconstructed master userpower spectrum signals are prevented from being judged again, and effective spectrum resource information can be obtained.