114results about How to "Reduce refactoring time" patented technology

When a receive signal strength received from a target network that will perform the handoff is larger than a reference strength, software related to the target network is previously installed in the corresponding portable terminal, a wireless connection environment with the target network is configured by driving the software related to the target network at the time of determining that the handoff is performed, and performs the handoff to the target network in the portable terminal.

The invention discloses a multi-task super-resolution image reconstruction method based on KSVD dictionary learning, which mainly solves the problem of relatively serious quality reduction of the reconstructed image under high amplification factors in the existing method. The method mainly comprises the following steps: firstly, inputting a training image, and filtering the training image to extract features; extracting image blocks to construct a matrix M, and dividing the matrix M into K classes to acquire K pairs of initial dictionaries H1, H2...Hk and L1, L2...Lk; then, training the K pairs of initial dictionaries H1, H2...Hk and L1, L2...Lk into K pairs of new dictionaries Dh1, Dh2...Dhk and Dl1, Dl2...Dlk by utilizing a KSVD method; and finally, carrying out super-resolution reconstruction on the input low-resolution image by utilizing a multi-task algorithm and the dictionaries Dh1, Dh2...Dhk and Dl1, Dl2...Dlk to acquire a final reconstructed image. The invention can reconstruct various natural images containing non-texture images such as animals, plants, people and the like and images with stronger texture features such as buildings and the like, and can effectively improve the quality of the reconstructed image under high amplification factors.

The invention provides a method for accurately reconstructing a microcosmic finite element grid model of a dissimilar material on the basis of CT (computed tomography) images. According to the method, sequence CT images are acquired through industrial CT, and micro-structural information in the CT images is mapped onto the reconstructed finite element grid model on basis of digitization and threshold segmentation, so that any detailed structural information in the dissimilar material can be represented in the reconstructed model. The method improves the reconstruction accuracy by means of contrast-limited adaptive histogram equalization, median filtering and pixel interpolation, and improves the reconstruction efficiency through image cut and pixel combination. With the method, rectangular (two-dimensional) and cuboid (three-dimensional) unit grid models with higher finite element analysis accuracy are directly reconstructed, error accumulation during reconstruction, grid partition and other links of the existing geometric reconstruction method is avoided, and reconstruction accuracy and efficiency are improved. The method can be widely applied to fields such as performance prediction and optimization design of dissimilar materials.

The invention discloses a multiple observed value vector sparsity self-adaptive compressed sampling matching pursuit method, which relates to the technical field of information and communication. The multiple observed value vector sparsity self-adaptive compressed sampling matching pursuit method is provided for solving the problem of recovering an original multiband signal from multiple observed value vectors with unknown sparsity after continuous-limited module conversion through sampling by a modulated broadband converter under an Xampling framework. The multiple observed value vector sparsity self-adaptive compressed sampling matching pursuit method comprises the steps of: conducting self-adaptive estimation on sparsity of a signal; updating the sparsity with a given step length factor through repeated iteration so that the sparsity gradually approaches the actual sparsity of the signal; correcting a support set through a backtracking thought and a minimum mean square criterion; stopping iteration until an residual error is less than a set threshold value; and finally reconstructing an original multiband signal through pseudo inverse operation by utilizing the obtained complete support set. The multiple observed value vector sparsity self-adaptive compressed sampling matching pursuit method can achieve the analog reconstruction of the multiband signal based on compressed sensing.

The invention is directed to a method for producing a polypeptide composition comprising: combining a polypeptide with a volatile additive to form a liquid mixture and lyophilizing the liquid mixture to obtain a lyophilized polypeptide composition.

The invention claims an image compression sensing method based on a sparse denoising self-coding network, and belongs to the technical field of deep learning and image processing. The method comprisesthe following steps: 1, obtaining an original image signal x as training data, preprocessing the data and completing signal corrosion to obtain the formula as shown in the specification; 2, buildinga coding sub-network of a sparse denoising self-coding network, and obtaining a measurement value y by the image signal x through the coding sub-network; 3, setting up a decoding sub-network of the sparse denoising self-coding network, obtaining a reconstructed picture as shown in the specification by the measurement value y through the decoding sub-network, 4, introducing sparsity limitation, andgenerating a loss function JSDAE (W, b); and 5, carrying out joint training on the coding and decoding sub-networks through a back propagation algorithm, updating parameters and obtaining an optimalsparse denoising self-coding network. Sparsity limitation is added on the basis of the denoising self-coding network, image compression and reconstruction are integrated into a unified self-coding network framework, the quality of reconstructed images is effectively improved, and the reconstruction time is greatly shortened.

The invention provides a disk array multi-level fault tolerance method, which adopts a three-level fault tolerance mode to solve common array errors at present effectively. The first-level fault tolerance is sector-level fault tolerance for effectively preventing the vector incapable of tolerating fault of a disk from failing; the second-level tolerance is data migration-level fault tolerance for preventing fault caused by the reduction in the reliability of the disk; and the third-level fault tolerance is to apply a parallel reconstruction mode to repair the disk fault in an array quickly. In the method, the reliability of an array-based storage system is improved by a three-level fault tolerance policy, and the performance of the system is guaranteed.

The invention provides a test system used for a satellite power supply and distribution system. The system comprises a control module, a PXI module, a stabilized power supply, and a sun square matrix simulator. A man-machine interaction unit is used for receiving instructions input by external users and sending instructions for a control unit. The control unit controls the PXI module, the stabilized power supply, and the sun square matrix simulator to complete data acquisition according to the received instructions. The PXI module, the stabilized power supply, and the sun square matrix simulator realize data acquisition according to the instructions, and feed back acquired data to the man-machine interaction unit. The system solves problems that the number of moonlet ground test devices is large, volume of the devices is large, versatility is bad, and design and development period are long.

The invention discloses an image structure model-based compressed sensing image reconstruction method, which mainly solves the problems that image structure information is not considered and blind iteration is carried out in the conventional method. The method comprises the following steps of: inputting an image A, and performing Fourier transform on the image A to obtain a Fourier coefficient matrix X1 of the input image A; sampling the Fourier coefficient matrix X1 according to a density variable sampling model for fully sampling Fourier coefficients at low frequency to obtain an observation vector f; performing inverse Fourier transform on the observation vector f to obtain a transformed image X2; performing edge detection on the transformed image X2 to obtain an edge detection image X3; performing Wavelet transform and Curvelet transform on the edge detection image X3, finding an edge position and positions of large coefficients, and finding corresponding coefficients in the transformed image X2 according to the obtained positions; and performing Wavelet-curvelet frame-based Split Bregman reconstruction algorithm to iterate for 20 times and finally obtaining the required reconstructed image. The method has the advantages of higher accuracy, better effect and shorter time for image reconstruction.

The invention discloses a video sequence reconstruction method based on compressed sensing. An encoding end separates an original video sequence into two types of frames, i.e., key frames and non-key frames, and measurement is performed respectively by use of different sampling rates. At a decoding end, different video sequences are subjected to performance judgement of two different algorithms, i.e., motion estimation / compensation prediction and optical flow method prediction, and then through combination with a comparison result, all the non-key frames are subjected to good-performance algorithm reconstruction by use of inter-frame correlation . When a video is processed, the amount of data needing to be sampled is small and the quality of the recovered video is good. Compared with a traditional algorithm of video independent reconstruction, the peak signal-to-noise ratio at a low sampling rate is improved and the reconstruction time is shortened.

The invention provides an adaptive threshold value iterative reconstruction method for distributed compressed sensing, and mainly solves the problems that signal reconstruction time is long, reconstruction errors are large and the like in the prior art. The method includes the steps: (1) calculating an adaptive step and an adaptive threshold value h; (2) calculating an iterative value according to an iterative formula; (3) comparing the iterative value with the calculated adaptive threshold value h to obtain an iterative result; (4) updating a support set and modifying the iterative result; (5) stopping iteration and acquiring estimation signals when meeting an iteration stopping condition, otherwise, continuing iteration. The adaptive threshold value iterative reconstruction method has the advantages of step and threshold value adaptivity, shorter reconstruction time, small reconstruction error and the like.

The invention discloses a compressed sensing based color imaging device and a compressed sensing based color imaging method. The compressed sensing based color imaging device comprises a PC (personal computer), a DLP (digital light projector), a target image, a single-pixel photon detector and a data collection and control module. The PC, the DLP and the single-pixel photon detector are connected with the data collection and control module. The PC generates a two-dimensional random binary projected intensity image. The data collection and control module controls the DLP to perform binary intensity image projection on the target image under red, green, blue and white structured light sequentially to acquire digital signals of the red, green, blue and white structured light respectively and send the digital signals to the PC, reconstructs the signals of the red, green, blue and white structured light through compressed sensing to acquire four monochrome gray level images, and performing color fusion on the four monochrome gray level images to acquire a final color image. The compressed sensing based color imaging device and the compressed sensing based color imaging method have the advantages that light filters are not needed, and simple structure and low cost are achieved; sampling frequency can be reduced, and color fidelity can be guaranteed without reduction of image resolution.

The invention discloses a method for reconstructing a super-resolution image. The method comprises the following steps of: (1) generating a training set and characteristically representing the training set; (2) classifying a module through a training set; (3) classifying the module through a low resolution image block; (4) reconstructing the module through a high resolution image block; and (5) synthetizing high resolution images. According to the method, the training set is classified, types of input low resolution image blocks are identified, domain nesting is carryed out according to the types of the image blocks, and finally, the high resolution images are reconstructed. With the adoption of the method, time for reconstructing the images is shortened; and quality of reconstructed images can be maintained better.

The present invention discloses an image structure-based particle swarm optimization non-convex compressed sensing reconstruction method. The method comprises: 1. according to an observation vector, distinguishing an image block structure, and marking an image block as smooth, unidirectional and multi-directional; 3. clustering observation vectors corresponding to different types of image blocks, and constructing a corresponding over-complete redundant dictionary for each type of the image blocks; 4. constructing an initial population for each type of the image blocks; 5. for each type of the smooth image blocks, using a particle swarm algorithm based on a grouping initialization policy to search an atomic combination with an optimal scale; 6. for each type of the unidirectional and multi-directional image blocks, using a particle swarm algorithm based on a cross and an atomic direction constraint to search an atomic combination with an optimal direction and scale; and 7. calculating an estimated value of all image blocks, and sequentially splicing into an entire image to output. According to the method of the present invention, reconstruction time is short, and the reconstructed image has good visual effects, a high peak signal to noise ratio, and high structural similarity. The method can be used for non-convex compressed sensing reconstruction of an image signal.

The invention discloses a power distribution network reconstruction method and system. The method comprises the steps that an incidence matrix model is established according to the connection relation of father nodes and son nodes in a power distribution network and branch switches, and the on-off states of the branch switches are assigned to form an incidence matrix set; all incidence matrixes are used for simulating a topological structure of the power distribution network, whether the topological structure has a looped network is judged, if the topological structure has a looped network, the incidence matrixes corresponding to the topological structures are eliminated, if the topological structure has no a looped network, the topological structure is subjected to load flow calculation, and if the topological structure does not meet load flow constraints, the incidence matrixes corresponding to the topological structure are eliminated; a target function and constraint conditions are established, the target function is solved through adoption of an improved particle swarm optimization according to the restraint conditions so as to obtain the best topological structure; the power distribution network is reconstructed according to the best topological structure. The power distribution network reconstruction method and system can reduce needed time of power distribution network reconstruction by improving the optimizing speed.

The invention discloses an aircraft DC power supply system and a power supply method. The system comprises: at least two generators and correspondingly connected motor controllers for generating and outputting DC power to corresponding primary power bus bars; at least two primary power bus bars respectively connected to the at least two generators through controllable switches, wherein the two adjacent primary power bus bars are connected to each other; an external DC power source connected to the primary power bus bars through the controllable switches for supplying power to the primary powerbus bars in the engine starting state; DC power conversion devices, wherein the input ends are connected with the primary power bus bars, and the output ends are connected with key load bus bars forconverting the DC power on the primary power bus bars and outputting to the key load bus bars; and the key load bus bars for supplying power to corresponding key loads. The power density of the systemis improved and the continuous power supply of the power supply system when single or multiple generators are faulty is achieved.

The invention discloses a large-scale MIMO channel feedback reconstruction algorithm based on compressed sensing, including such steps as setting up system model, installing multiple antennas at basestation, serving multiple users at the same time, receiving each user with single antenna, uniformly linearly arranging antennas at base station and obtaining channel matrix at receiving end by channel estimation; 2, a channel state information compression step, vectorizing the channel matrix, a vector is obtained, the vector is compressed by the observation matrix to obtain the observation vector, and the observation vector (img file = 'DEST_PATH_IMAGE001. TIF' wi= '10' he= '14' / ) is sent to the base station through the feedback link. S3, the channel state information reconstruction step: after receiving the observed value vector, the base station performs numerical initialization and cyclic iteration, and finally obtains the reconstructed signal. The invention adopts the generalized orthogonal matching pursuit algorithm as the channel feedback reconstruction algorithm, which reduces the iterative times, not only effectively improves the reconstruction accuracy of the channel state information, but also shortens the reconstruction time.

The invention relates to the field of video compressed sensing and image sparse representation, and discloses a video coding and decoding system based on compressed sensing. The video coding and decoding system based on compressed sensing is designed to make a wireless video sensing network have the advantages that the complexity and calculated amount of a coding terminal are small, the volume of data transmitted through a channel is small and a decoding terminal can carry out high-quality real-time video reconstruction. According to the technical scheme, the video coding and decoding system based on dictionary learning and compressed sensing mainly comprises the video coding terminal and the video decoding terminal, wherein the coding terminal is used for temporarily storing image pixel data of K frames, reducing the dimensionality of the image pixel data of the K frames and transmitting data after dimensionality reduction to the decoding terminal through a wireless transmitting module according to the compressed sensing theory, and the decoding terminal is used for decoding the K frames according to the compressed sensing reconstruction algorithm (namely, the improved NSL0 method), storing the K frames and finally forming a video through integration according to frame sequences and outputting the video. The video coding and decoding system based on compressed sensing is mainly applied to video compressed sensing and transmission.

In a device including a programmable circuit, the programmable circuit is connected to a non-volatile memory in which configuration information is stored, and another memory having a faster reading speed than the non-volatile memory, and the programmable circuit includes a configuration memory control circuit, and a signal line group for performing reading with respect to the other memory such as a volatile memory and an embedded memory from the non-volatile memory by the configuration memory control circuit, and copies a part of circuit configuration information which is required to be subjected to fast restoration from failure into the other memory.

The invention discloses an asymmetrical disk array caching dispatching method, belonging to the technical field of computer storage. According to the method, a disk not involved in reconstitution is selected as a sacrificed disk, cache size of the sacrificed disk is reduced, and the cache size of a disk involved in reconstitution is correspondingly increased, so that number of times of input / output (I / O) requests to invalid disks and disks involved in reconstitution are reduced, the reconstitution speed of the invalid disk is improved, I / O response time of users is shortened, the availability and reliability of a storage system are improved, and the performance of the system is improved.

A logic integrated circuit reconfigures a reconfigurable circuit to a circuit having the function of a fixed circuit at the time of a fault in the fixed circuit. The fixed circuits are divided into a plurality of functional circuit blocks, which are connected to programmable buses. Reconfigurable circuits corresponding to each functional circuit block are provided. In this configuration, the range of reconfiguration is limited to the block including the defective portion, so substitution processing is completed within a short time. Further, in the range which is not affected by the substitution processing, the operation can be continued even during the substitution processing.

The invention discloses a distributed video compressive sensing sampling method based on time correlation. According to the method, on the basis of establishing a non-feedback distributed video compressive sensing model, the time correlation among video frames is utilized fully; a sampling rate of each block is preliminarily allocated according to a size of the information of a video group of pictures occupied by the information of each picture block; mode judgment is carried out according inter-frame residuals; and a practical sampling rate of each small block is calculated, so self-adaptive sampling allocation is realized. According to the method, the reconstruction quality of a video is improved under the same total sampling rate, the energy saving amount resulting from reducing the sampling times far exceeds the extra energy consumption amount resulting from employing a dynamic sampling rate algorithm, no feedback channel is employed, and the time delay is relatively low. According to the method, the problem that the time correlation is not taken into full consideration in an existing distributed video compressive sensing sampling process is solved, and the method has good practical value.

The invention discloses an independent redundant disk array data reconstruction method, device and equipment. The method comprises the following steps of: after the RAID independent redundant disk array is added to the storage pool, after the RAID formatted storage unit is added to the logical volume, setting the used flag on the storage unit in the logical volume; when a disk fault exists in theRAID memory is detected, setting a fault flag on all storage units corresponding to the fault disk; traversing all the storage units corresponding to the fault disk; if the currently traversed storageunit is simultaneously provided with the used flag and the fault flag, reconstructing the current traversed storage unit, and after the reconstruction is completed, cancelling the fault flag of the reconstructed storage unit, and continue to traverse the next storage unit; otherwise, directly traversing the next storage unit until the fault disk traversal is completed. According to the independent redundant disk array data reconstruction method, only the used parts of the fault disk are reconstructed, the unused parts are not reconstructed, so that the reconstruction time is shortened, and the reconstruction efficiency is improved.

The present invention provides a method for data reconstruction of a disk array, and a disk array system. The method comprises: S1. determining original data of a current strip fragment in a source faulty disk is unreadable, and if yes, performing step S2, and if no, performing step S3; S2. determining a relevant strip fragment that belongs to the same strip as the current strip fragment, obtaining data of the relevant strip fragment, and reconstructing the original data of the current strip fragment according to the data of the relevant strip fragment, to obtain reconstructed data corresponding to the current strip fragment; and S3. reading the original data of the current strip fragment, and using the original data as reconstructed data corresponding to the current strip fragment. According to the method for the data reconstruction of the disk array and the disk array system provided by the present invention, the efficiency of the data reconstruction can be improved.

The invention discloses a motion-compensation-and-block-based video compressed sensing (CS) processing method, and relates to the technical field of a video compressed sensing technology. The processing method comprises the steps: 1) a block image residual error frame reconstruction method; 2) a block CS image residual error frame reconstruction algorithm; and 3) a reference frame method based on bidirectional reconstruction. The motion-compensation-and-block-based video compressed sensing processing method uses a motion-estimation algorithm to analyze the motion vector and the residual error data between video frames, and takes the residual error data between video frames to replace the video frames as the compression reconstruction object, so that the video compression ratio is greatly improved. At the same time, the motion-compensation-and-block-based video compressed sensing processing method mainly utilizes a forward / backward bidirectional reconstruction idea and is supplemented by a dynamic adaptive selection reconstruction algorithm, and automatically operates different video reconstruction algorithms according to the exchanging speed of the video content, so that the calculation complexity and the reconstruction time during the video reconstruction process can be effectively reduced.

A logic integrated circuit reconfigures a reconfigurable circuit to a circuit having the function of a fixed circuit at the time of a fault in the fixed circuit. The fixed circuits are divided into a plurality of functional circuit blocks, which are connected to programmable buses. Reconfigurable circuits corresponding to each functional circuit block are provided. In this configuration, the range of reconfiguration is limited to the block including the defective portion, so substitution processing is completed within a short time. Further, in the range which is not affected by the substitution processing, the operation can be continued even during the substitution processing.

The invention provides a dual-redundancy FC-AE-1553 network reconstruction method based on switching topology, which comprises the following steps: in a network in which a network communication node adopts a redundant backup design and a node transmission channel is a dual-redundancy channel, adding a network fault detection mechanism and a main / standby node communication function switching mechanism; after the network controller or the network end node breaks down, switching the backup network end node to the network controller, uploading a network message scheduling table, completing networkcommand frame organization scheduling and network management control, and taking over the communication function of the broken-down network controller; or switching to the network end node, and switching the physical mapping relationship between the address of the network end node and the switching port by the network switch, so as to take over the function of the fault end node and complete thenetwork message communication function. According to the method, the reconstruction problem of the switched FC-AE-1553 network is solved, the reconstruction time is shortened, and the network reliability is improved.

The present invention relates to improved pharmaceutical compositions that contain high concentrations of one or more protein biomolecule(s). In particular, the invention relates to such pharmaceutical compositions that include one or more amino acid molecules, particularly arginine, alanine, glycine, lysine or proline, or derivatives and salts thereof, or mixtures thereof, as stabilizing compounds. The inclusion of such stabilizing compounds decreases reconstitution time whilst improving and / or maintaining the long-term stability of the protein biomolecule, so as to facilitate the treatment, management, amelioration and / or prevention of a disease or condition by the pharmaceutical composition. The invention particularly pertains to such pharmaceutical compositions that lack, or substantially lack, a sugar stabilizing agent.