135results about How to "Avoid estimation" patented technology

Methods and apparatus for super-resolution in focused plenoptic cameras. By examining the geometry of data capture for super-resolution with the focused plenoptic camera, configurations for which super-resolution is realizable at different modes in the focused plenoptic camera are generated. A focused plenoptic camera is described in which infinity is super resolved directly, with registration provided by the camera geometry and the microlens pitch. In an algorithm that may be used to render super-resolved images from flats captured with a focused plenoptic camera, a high-resolution observed image is generated from a flat by interleaving pixels from adjacent microlens images. A deconvolution method may then be applied to the high-resolution observed image to deblur the image.

For the notification of a receiving device about a forthcoming transmission session, an identifier of one of various possible types of identifiers in a transmission session is mapped to a transmission session identifier field. This field is used for notifying the receiving device. Further, a repetition value is added to the transmission session identifier field, which indicates whether the forthcoming transmission session is new or not. Further, the receiving device may release context data stored for a particular transmission session identifier, if an acquisition of data in transmission sessions identified by the transmission session identifier can be terminated.

The invention discloses a text feature quantification method based on comentropy, a text feature quantification device based on comentropy, a text classification method and a text classification device. The text feature quantification method comprises the following steps that: the weight of each feature word in a document is calculated according to the word frequency of feature words in a text document and the comentropy distributed on different text classes; meanwhile, the inter-class distribution entropy of the feature words is calculated in different modes according to the unbalance performance of the scale of each class of a text set; in addition, the inverse document frequency is introduced as required according to the distribution features of each feature word in the text set; local word frequency factors are properly reduced, so that the weight distribution of each feature word in the document is reasonable; and the feature differences of different classes of texts are sufficiently reflected by generated document feature vectors. The text feature quantification device and the text classification device disclosed by the invention have a plurality of options or parameters; and the optimum text classification effect can be achieved through regulation. The text feature quantification method has the advantages that the text classification accuracy is improved, and the performance on different text sets is stable.

The invention discloses an iterative least square method-based MIMO (multiple input multiple output) radar DOA (direction-of-arrival) estimation method, which is characterized in that receiving and transmitting array response matrixes on which dimension-reduced processing is performed are solved by using an iterative least square method. The iterative least square method-based MIMO radar DOA estimation method comprises the following steps: firstly, performing the dimension-reduced processing on echo data matrixes of multiple radar transmitted pulses and the receiving and transmitting array response matrixes; then, establishing cost functions under the least square condition, and solving the cost functions by utilizing a gradient descent-based iterative method; finally, estimating the direction of a target by utilizing known receiving and transmitting array manifolds. Compared with a traditional monostatic MIMO radar array DOA estimation method, the iterative least square method-based MIMO radar DOA estimation method disclosed by the invention directly obtains the DOA estimation of the target, and does not need to perform spectrum peak search. Noise is effectively suppressed by adopting the dimension-reduced processing, and the estimation accuracy under low signal to noise ratio is improved; the estimation, the inversion and the eigenvalue decomposition operation of high-dimensional data covariance matrixes are avoided; the defects that the calculated amount is high and the needed sample number is large when the traditional array DOA estimation method is applied to a monostatic MIMO radar are overcome.

The invention discloses an optical flow estimation method based on multiple dimensioned corresponding structuring learning; under given successive video frames, the method can parse the motion conditions of the first frame relative to the second frame; the method specifically comprises the following steps: obtaining a successive frame image data set used for training optical flow estimation, and defining an algorithm object; carrying out structuring modeling for correspondences between two successive frame images in different dimensions; joint encoding the corresponding relations in different dimensions; building an optical flow estimation prediction model; using the prediction model to estimate the successive video frame optical flow values. The optical flow estimation method is applied to the optical flow motion analysis in true videos, and can provide better effect and robustness under various complex conditions.

The embodiment of the invention provides a compensation method and device for holder drift, a holder and an unmanned aerial vehicle, and is applied to the technical field of the unmanned aerial vehicle. The compensation method comprises the following steps: through a first image and a second image collected by an image acquisition device on the holder, obtaining a holder drift angle, and controlling the holder to move to compensate the drift angle. According to the compensation method, the technical problem that the estimation and the compensation of the holder drift cannot be accurately carried out when the zero drift of a gyroscope is compensated is solved.

The invention relates to a method for selecting codebooks based on deep learning under large scale MIMO(Multiple-Input Multiple-Output) and belongs to the technical field of wireless communication. The method comprises following steps: acquiring pilot frequency information of a test zone to establish a pilot frequency training sequence and further obtaining a pilot frequency training sample; performing neural network iteration learning to the pilot frequency sample to obtain a final network weight value; selecting optical code words from a complete codebook according to the signal channel output by the neural network after learning. performing signal channel information matching to an unknown zone and the test zone to obtain a wireless signal channel thereof, and further obtaining code words corresponding to the wireless signal channel. By means of the method, wireless signal model and codebook query can be effectively, accurately and quickly established to avoid signal channel estimation of unknown zones and greatly reduce the complexity of unknown zone signal channel codebook selection.

The invention discloses a video object division method based on change detection and frame difference accumulation. The video object division method includes: interframe changes of symmetrical frames with the interval to be k frames are tested through t significance testing, a detected initial motion and variation area is subjected to time domain fixed interval time domain calculating, and a memory mask is formed through further integrating; a threshold value is adjusted through image edge continuous testing by aid of a Kirsch edge testing operator based on discontinuous testing to obtain all connected edge information in the current frame; a semantics video object plane is obtained through a space-time filter; and video object division is achieved through selective application filling and morphological processing operations. The video object division method based on change detection and frame difference accumulation is novel, effectively solves the problems of video object internal lack and background exposing which are caused by irregular object movements frequently happening in the video object division method, and is greatly improved in division speed, division effect, application range and portability.

The invention discloses a multi-missile cooperative guidance method based on output consistency. The method comprises the steps that constraint conditions of normal acceleration and field angles of all missiles are given; a linear model on which the missile status depends is built on the basis of a relative motion relationship of missiles and a target, convergence variables, line-of-sight angle rates and field angles of the linear model on which the missile status depends are selected as output variables, and a predictive control model is built according to a set prediction time domain; a performance index function is obtained on the basis of requirements of predictive control model and missile striking time cooperation; the performance index function and the constraint conditions are converted into a quadratic programming standard form; an optimal model achieving multi-missile cooperative guidance is obtained, normal acceleration of all the missiles on the present moment is obtained by means of a convex optimization method, and updated statuses of all the missiles are adopted on the next moment till all the missiles hit the target. According to the multi-missile cooperative guidance method based on the output consistency, optimal cooperative guidance on the condition that normal acceleration overload and field angles are limited can be achieved.

The invention provides a channel rank estimation method during multi-stream beamforming transmission, which comprises the following steps: a base station receives a CQI which is fed back by a user equipment UE and detected by the UE according to a common pilot; the base station estimates uplink channel information according to an uplink detection pilot signal sent by the UE; and the base station obtains the rank of a channel according to the CQI fed back by the UE and the estimated uplink channel information. The estimation method can effectively solve the estimation of the rank value during the multi-stream beamforming transmission, further support the rank self-adaptive transmission during the multi-stream beamforming transmission and improve the flexibility of a system.

An improved per-tone FEQ method with a noise reduction technique using periodic training pilot tones increases the throughput for long-reached modems. This method can reduce the noise effects in estimating FEQ equalizer coefficients. Each per-tone FEQ can be estimated by using the periodic training signals and an averaging technique to remove noise from each sub-channel (EQN. VI). After solving the system equations (EQN. IV), per-tone equalization coefficients of the FEQ equalizer for each group can be combined to obtain the optimized results in the form of the Toeplitz matrix (EQN. V). Each element within the Toeplitz matrix can be derived from the averaging technique used to remove noise from each sub-channel (EQN. VI). To demodulate a signal with the Toeplitz matrix, an inverse of every element in a row of the Toeplitz matrix is taken and multiplied by the sending signal which creates an N Log N matrix.

A method that includes interference control at transmitters and interference mitigation at receivers in a wireless communication system is disclosed. Embodiments of the present invention exploit the interference sensitivity at neighboring terminals by taking into account the reciprocity of propagation radio channels in Time Division Duplexing systems (TDD). It can be applied to design the resource allocation for downlink (DL) and uplink (UL) transmissions in a wireless communication system. The methods include the self-configuration of the transmit power, the transmit precoder and the receive filter, at each transmitter and receiver in a multi-cell network. Systems are also provided and configured for implementing the methods of the invention.

The invention relates to a method for correcting direct positioning deviation based on a neural network under an array amplitude phase error condition. The method comprises the following steps: distributing a plurality of correction sources in a preset region, and acquiring a group of correction source estimated position and real position information aiming at each correction source; inputting theestimated position and real position information of all correction sources as a training set into a preset multi-layer perceptron neural network for training; acquiring the trained multi-layer perceptron neural network; and estimating a position with deviation caused by an array amplitude phase error according to a collected array signal including target position information, and inputting the position into the trained multi-layer perceptron neural network, so as to obtain the corrected target position. According to the method, the estimation of an array error matrix is omitted, and the correction of the target position is directly finished, so that the influence caused by the array amplitude phase error to the positioning precision can be inhibited to a certain extent, the positioning precision of a target under the amplitude phase error condition is improved, and the performance is stable, reliable and efficient.

The invention discloses a method for MIMO radar system angle estimation based on fast Fourier transformation. The method for MIMO radar system angle estimation based on fast Fourier transformation comprises the steps that a data matrix received by a first pulse of the radar system is evenly divided and divided signals are expressed in the description, new signals are divided by the four matrix blocks defining; bi-dimensional fast Fourier transformation is respectively conducted to the signals shown in the description; coherent integration is conducted on F11(l), F12(l), F21(l) and F22(l), a peak point shown in the description and the corresponding subscript ix and the corresponding subscript iy are recorded, points corresponding to the subscript ix and the subscript iy are respectively obtained from the F11(l), the F12(l), the F21(l) and the F22(l), so that the vector of f(1) belonging to C4*1 is established; the covariance matrix of the f(1) is calculated according to the sampling covariance matrix inversion principle, characteristic decomposition is conducted on the covariance matrix, and a noise projection matrix pn can be obtained through a noise sub space un; a transmitting oriented vector and a receiving oriented vector br(theta) are obtained according to a receiving data matrix Y(1) and the leaving angle and the reaching angle are estimated through the MUSIC arithmetic.

When encryption information including an encryption rule, an encryption range, and an encryption key is input to a server apparatus from a local maintenance console in advance, the server apparatus stores the encryption information in an encryption information setting unit, creates an SIP request message including the encryption information, and transmits the SIP request message to a client apparatus. The client apparatus receives the SIP request message including the encryption information. If confirming normality of the encryption information, the client apparatus sets the encryption information therein. After completion of a setting of the encryption information, the client apparatus transmits a notification of the completion of the setting of the encryption information to the server apparatus. Upon receiving the notification of the completion of the setting of the encryption information, the server apparatus acknowledges the completion of the setting of the encryption information, sets the encryption information therein, transmits the notification of the completion of the setting of the encryption information to the local maintenance console, and causes the local maintenance console to display the completion of the setting of the encryption information.

The invention relates to a transaction priority determination method in the field of heterogeneous distributed parallel processing. The method comprises the following steps of: determining the priority of a global transaction; distributing sub-transactions which are obtained by dividing the global transaction according to physical positions of data relevant to the sub-transactions; dynamically determining the priority of respective parts of local transactions; performing parallel processing on the local transactions; and returning an execution result. The invention provides a flow for dynamically determining the priority of the transaction based on a heterogeneous distributed system, so the real-time property and reliability of the system on processing of the global transaction are guaranteed.

The present invention discloses a non-fragile dissipative filtering method of a nonlinear networked control system. The method comprises the steps of firstly establishing a nonlinear networked filtering error system model on the conditions of considering the time delay and the packet loss of the nonlinear networked control system and the perturbation of the filter parameters, then constructing a Lyapunov function, and then utilizing a Lyapunov stability theory and a linear matrix inequality analysis method to obtain the sufficient conditions of the mean square exponential stability of a nonlinear networked filtering error system and the existence of a non-fragile dissipative filter, utilizing a Matlab LMI tool kit to solve, and definding a non-fragile dissipative filter parameter matrix. The method of the present invention considers the random time delay and the pocket loss situations between the sensors and the filters, is suitable for the general dissipative filtering including the H-infinite filtering, and enables the conservatism of the non-fragile dissipative filter design to be reduced. Moreover, a non-modeling state of the system is considered when a full-order filter is designed, thereby being able to reduce the calculation burdens and the design cost.

The invention discloses a method for extracting video object contour based on centroid tracking and improved GVF Snake. The method is characterized by comprising the following steps of according to the condition that the movement trend of adjacent frames is similar in short time, dividing a video sequence into a plurality of sections, wherein each section has k frames of video, taking the first two frames in the section as key frames, detecting the effect of eliminating the background border based on the change of t obvious test, and acquiring an initial movement area; extracting a critical quadrangle as an initial contour of the key frames, performing intra-frame GVF Snake evolution, searching the exact contour, then forecasting initial contours of the subsequent frames through the movement vector between centroids of the intra-frame movement object contours of the key frames, and then performing the exact intra-frame GVF Snake contour positioning of the subsequent frames; and by the analogy, extracting the object contour of all frames. The improved model adopts four-direction anisotropic diffusion, and adopts fidelity term coefficients with fast descending speed to enhance the performance to enter into concave; and the convergence to a weak edge is kept. By the method, the shortcoming of manually acquiring the initial contours is conquered.

The invention provides a compressed sensing spectrum detecting method under the blind sparse condition. The aim of spectrum detecting under the condition that the sparseness is unknown is achieved. The compressed sensing spectrum detecting method under the blind sparse condition includes the steps of (1) conducting optimization iteration solving on a built mathematic model (please see the specifications for the formula), (2) conducting simplification to obtain convex optimization problem of reconstitution signals, (3) obtaining an element with the maximum correlation, merging the element with a support set of last-time iteration, and obtaining a new support set, (4) obtaining a residual error, (5) obtaining a contribution value and outputting spectrum detecting results (please see the specifications for the formula) and the like. The mode is applied to the compressed sensing spectrum detecting method.

A method and device for notifying and determining DMRS ports or a mapping relationship is provided. The method includes a sending end sending indication information to a receiving end in a TM, and the sending end indicates allocation information about DMRS ports or a mapping relationship according to the indication information, and the indication information includes at least one of the following: RRC signaling, physical layer NDI bit, and DMRS pilot scrambler configuration information nscid. A problem of influence on a performance of a MU-MIMO system caused by lower channel estimation performance due to limited orthogonal DMRS ports for MU-MIMO transmission and high MUI after increment of a total number of MU-MIMO transmission layers is solved.

The invention discloses an image haze removal method and system based on image layer enhancement. The image haze removal method based on image layer enhancement comprises the steps that S1, the atmosphere optical value A of an original image is estimated; S2, two layers of half-inversion images are constructed according to the atmosphere optical value, and linear contrast enhancement is conducted on the two layers of half-inversion images; S3, the absolute difference values between the original image and the enhanced half-inversion images in an H channel of a CIE LCH space are calculated, the weight distribution of the enhanced half-inversion images are determined according to the absolute difference values, and the two layers of enhanced half-inversion images are fused according to the weight distribution; S4, linear enhancement is further conducted on an image obtained after image infusion, and the image with the haze removed and the increased contrast ratio is obtained finally. By the adoption of the image haze removal method based on image layer enhancement, the situations such as insufficient enhancement or color distortion appearing when a traditional image enhancement algorithm is adopted in the prior art can be effectively avoided, the clear image with the haze removed is obtained, calculation is easy, the applicability is high, and the requirements for real-time processing and application can be met.

The invention discloses a self-adaption anti-coherent interference technology based on characteristic component rejection. Firstly, characteristic decomposition is carried out on an antenna multichannel receiving data covariance matrix to judge the number of a big characteristic value; then, the characteristic vector corresponding to signals and coherent interference is searched in a characteristic vector group corresponding to the big characteristic value so as to subtract the characteristic vector from the covariance matrix; finally, diagonal loading is carried out on the covariance matrix removing signals and coherent interference components, and the loaded matrix is used for calculating a self-adaption weight, data is weighed, and specific steps are disclosed in the drawing. The method of the invention avoids cancellation of desired signals while inhibiting incoherent interference, does not have array aperture loss and does not need to master the direction priori information of coherent interference. The method only relates to characteristic decomposition and inversion operation but does not relate to high-order cumulant operation, so that the method has simple steps and small calculation amount; the device is simple and has low cost. In addition, the method of the invention receives and utilizes the coherent interference as a wanted signal so as to improve the receiving gain of a target signal, thus owning better receiving performance. The method of the invention can be realized only by downloading a program to a general signal processing board, is easy to popularize and only needs to programme on a programmable signal processing board; thus, the system is convenient to upgrade while the system structure is not changed. The method of the invention can be widely applied to a system with various kinds of receiving channel structures and has popularization and application value.

The invention relates to a lens clustering method based on an information bottleneck theory. The information bottleneck theory is used for the lens clustering. Every lens to be classified is initialized into one sort. Common information loss in a merging process is used as a measure for a category distance to implement the sort combination until all lenses are merged into one sort. The sort number corresponding to common information loss inflection points is used as the final sort number of the lens clustering. At the same time, in order to solve the problem of local optimal solution appearing in a hierarchical clustering, the classification result is regulated when combined with a sequence clustering method. The lens clustering method can apply the information bottleneck theory to the clustering method without estimating the number of the sort beforehand, thereby improving the precision and the recall ratio of the clustering results and avoiding the problem of local optical solution.

The invention belongs to technical field of target characteristic and target identification and specifically relates to a broadband multiband imaging coherent processing method. The method comprises following steps of: performing modeling extrapolation processing on data in two different frequency bands of a same target measured respectively by two radars in order to obtain frequency response data with consistent frequency ranges; performing imaging processing on extrapolated broadband data in order to extract positional information of two groups of scattering centers of range profiles; respectively calculating positional difference of corresponding scattering centers and finally obtaining an average positional difference in order to further obtain linear phase error estimation; calculating the amplitude errors of the two groups of scattering centers in sequence in order to obtain amplitude error estimation; performing linear phase error compensation and amplitude error compensation on extrapolated data out of a certain frequency band and extracting the positional information, the amplitude information, and the phase information of compensated scattering centers; and calculating the phase difference of the two groups of scattering center in sequence in order to obtain a fixed phase error. The method is little in computational complexity and high in estimative accuracy.

The invention discloses a millimeter wave communication multipath channel dynamic beam training method. According to the millimeter wave communication multipath channel dynamic beam training method provided by the invention, a beam training method of a millimeter wave communication multipath channel is fully studied, a layered codebook of a sending end and a receiving end which can be adjusted dynamically and have a closed expression is designed, and through a method for removing path interferences estimated previously, the problem of multipath channel estimation is converted into sequential multiple single-path channel estimation problems. The influence of estimated paths is removed through the design of a codeword, so that the beam training complexity of the multipath channel is greatlyreduced, and the accuracy is greatly improved.

A method for suppressing a non-stationary blanket interference signal in a satellite navigation system comprises the steps that when a blanket interference signal, a satellite signal and a noise signal coexist, an array signal to be processed is formed through an M-element even linear array; discrete sampling is conducted on a whole interference signal originating space and an array signal sparse representation model is obtained; coherent processing is conducted on sparse representation model data and guide vectors at all possible angles and the position of the maximum value of the coherent quantity in the guide vector matrix is found; a sparse vector corresponding to the maximum value of the coherent quantity is estimated through the least square method; the sparse vector is subtracted from the sparse representation model data and a surplus is obtained; whether interference components are completely suppressed or not is judged, if the conduction that the interference components are completely suppressed is not satisfied, repeated iteration is conducted, a first element of a surplus vector serves as data after current snapshot interference suppression, and satellite tracking and locating are conducted. According to the method, the number of interference signals does not need to be known in advance, mismatch of a DOA sampling interval is insensitive, and interference with the DOA interval smaller than a resolution ratio can be processed.

The invention discloses a wifi and geomagnetism fused indoor positioning system and method based on an HMM (Hidden Markov Model). The method comprises the following steps: matching a wifi signal acquired by a mobile terminal in real time with a pre-established wifi fingerprint library to obtain a local position area; initializing the position in the area to obtain an initial probability distribution matrix; obtaining a state transition probability matrix by using a position relationship of label points in the local position area; and fusing a geomagnetic signal with a pre-established geomagnetic fingerprint library to obtain an observation probability matrix, and estimating the position of a user according to a forward algorithm. When the user is positioned in the local position area determined by the wifi signal, the current real-time geomagnetic signal is used to update the observation probability matrix, and the position of the user is estimated by the observation probability matrixand the state transition matrix; otherwise, the wifi signal is introduced to re-establish the local position area, and the initial probability distribution matrix, the state transition probability matrix and the observation probability matrix are updated according to the preceding method. According to the wifi and geomagnetism fused indoor positioning method based on the provided by the invention, various information is effectively fused, and the positioning accuracy of the system is improved.

The invention discloses a speech noise reduction method applied to a dual-microphone small handheld device. A corresponding noise reduction method can be selected according to a different mode used by a user. In a normal handheld conversation mode, a method based on power level differences is applied to a near field signal model in the mode, and large difference information in the energy of speech signal receiving by primary and secondary microphones can be effectively used; in a loudspeaker using mode, when a method based on relevance between the two microphones is used, estimation of a noise power spectrum is not needed, and influences of inconsistency noise receiving by the two microphones on the method based on power level differences can be avoided; and in addition, compared with the traditional method based on the power level differences, the method of the invention can effectively avoid music noise caused by error power spectrum estimation through built Wiener filtering.

The invention discloses a playing method of IP real time stream media, which is suitable for the playing of single media stream and the synchronous playing of a plurality (can be more than two) of media streams. In the realization process, one media stream is assigned as the reference media stream to calculate the playing displacement and determine the playing time of each frame so as to realize the synchronous playing of all the media streams. The playing method is simple and reliable, and the playing process of the stream media is more fluent.

The invention belongs to the technical field of coastal zone dam monitoring, and discloses a coastal zone dam stability monitoring and flooding vulnerability evaluation method and system. The method comprises the steps of preparing a satellite-borne SAR single look complex image and global DEM data for assisting the InSAR time sequence analysis, and obtaining dam point cloud data, sea level risingdata and tide inspection data through employing an unmanned plane laser radar; carrying out data preprocessing to realize dam DEM generation, dam deformation rate acquisition, dam future DEM simulation and dam water level simulation; and performing flooding analysis to realize dam flooding analysis and dam flooding scene display. According to the invention, the combination of the satellite-borneInSAR time sequence analysis deformation rate and the unmanned aerial vehicle-mounted laser radar DEM is realized, and high observation precision and space-time resolution are ensured. According to the invention, three components (tidal component, storm water increase and sea level rise) are synthesized for flooding water level simulation, daily conditions and extreme conditions are simulated at the same time, and over-high water level estimation is avoided.