565results about How to "Strong anti-noise ability" patented technology

A digital television (DTV) transmitter and a method of processing data in the DTV transmitter/receiver are disclosed. In the DTV transmitter, a pre-processor pre-processes the enhanced data by coding the enhanced data for forward error correction (FEC) and expanding the FEC-coded data. A packet formatter generates one or more groups of enhanced data packets, each enhanced data packet including the pre-processed enhanced data and known data, wherein the data formatter adds burst time information into each group of enhanced data packets. And, a packet multiplexer generates at least one burst of enhanced data by multiplexing the one or more groups of enhanced data packets with at least one main data packet including the main data, each burst of enhanced data including at least one group of enhanced data packets.

The invention relates to a point cloud automatic registration method based on normal vector. According to the method, processing objects are two or more than two pieces of three-dimensional point cloud data, wherein overlapped part exists every two pieces of adjacent three-dimensional point cloud data. The method comprises the following processing steps that (1) feature points are selected according to the point cloud local normal vector changes; (2) the histogram feature quantity is designed for carrying out feature description on each obtained feature point; (3) the initial matching dot pair is obtained through comparing the histogram feature vector of the feature points; (4) the precise matching dot pair is obtained through applying the rigid distance constraint condition and combining a RANSAC (random sample consensus) algorithm, and in addition, the initial registration parameters are obtained through calculation by using a four-element method; and (5) an improved ICP (iterative closest point)) algorithm is adopted for carrying out point cloud precise registration. The point cloud can be automatically registered according to the steps. The method has the advantages that feature description is simple, identification degree is high, higher robustness is realized, and registration precision and speed are improved to a certain degree.

A digital television (DTV) transmitter/receiver and a method of processing data in the DTV transmitter/receiver are disclosed. In the DTV transmitter, a pre-processor pre-processes the enhanced data by coding the enhanced data for forward error correction (FEC) and expanding the FEC-coded enhanced data. A data formatter generates enhanced data packets including the pre-processed enhanced data and inserts known data to at least one of the enhanced data packets. A first multiplexer multiplexes the enhanced data packets with main data packets including the main data. And, an RS encoder RS-codes the multiplexed main and enhanced data packets, the RS encoder adding systematic parity data to each main data packet and adding RS parity place holders to each enhanced data packet. Herein, the RS encoder may insert non-systematic RS parity data or null data into the RS parity place holders included in each enhanced data packet.

The invention discloses a 3D terrain imaging system of the interferometric synthetic aperture radar (InSAR) and an elevation mapping method thereof, which mainly solve the problems that the existing InSAR has bad imaging pragmaticality and can not implement 3D elevation mapping on the fast-changing terrain and the transilient terrain. The system comprises three sub-aperture antennas, a radar transmitter, a radar receiver and an imaging data processor; the imaging signal processor comprises a SAR image processing unit and an InSAR image processing unit. The invention receives radar echo through the three sub-apertures, then conducts SAR imaging process on the radar echo respectively received by the three sub-apertures, and then conducts InSAR imaging process on the obtained SAR complex pattern, wherein the InSAR imaging process comprises image registration, phase filtering and phase unfolding based on cluster analysis. The processed InSAR phase unfolded image is processed with an elevation inversion to recover a three dimensional digital elevation map. The invention has the advantages of wide adaptability to mapped terrains, and high imaging effectiveness, therefore, the invention can be used in the mapping of the 3D terrain.

The invention relates to a multi-scale normal feature point cloud registering method. The multi-scale normal feature point cloud registering method is characterized by including the steps that two-visual-angle point clouds, including the target point clouds and the source point clouds, collected by a point cloud obtaining device are read in; the curvature of radius neighborhoods of three scales of points is calculated, and key points are extracted from the target point clouds and the source point clouds according to a target function; the normal vector angular deviation and the curvature of the key points in the radius neighborhoods of the different scales are calculated and serve as feature components, feature descriptors of the key points are formed, and a target point cloud key point feature vector set and a source point cloud key point feature vector set are accordingly obtained; according to the similarity level of the feature descriptors of the key points, the corresponding relations between the target point cloud key points and the source point cloud key points are preliminarily determined; the wrong corresponding relations are eliminated, and the accurate corresponding relations are obtained; the obtained accurate corresponding relations are simplified with the clustering method, and the evenly-distributed corresponding relations are obtained; singular value decomposition is carried out on the final corresponding relations to obtain a rigid body transformation matrix.

The invention discloses a non-rigid heart image grading and registering method based on an optical flow field model, which belongs to the technical field of image processing. The method comprises the following steps of: obtaining an affine transformation coefficient through the scale invariant characteristic vectors of two images, and obtained a rough registration image through affine transformation; and obtaining bias transformation of the rough registration image by using an optical flow field method, and interpolating to obtain a fine registration image. In the non-rigid heart image grading and registering method, an SIFT (Scale Invariant Feature Transform) characteristic method and an optical flow field method are complementary to each other, the SIFT characteristic is used for making preparations for increasing the converging speed of the optical flow field method, and the registration result is more accurate through the optical flow field method; and the characteristic details of a heart image are better kept, higher anti-noising capability and robustness are achieved, and an accurate registration result is obtained. Due to the adopted difference value method, a linear difference value and a central difference are combined, and final registration is realized by adopting a multi-resolution strategy in the method simultaneously.

The invention relates to a measuring post simulation method of the fault wire selection for a low current grounding system. The invention belongs to the technical field of the power system relay protection. The method is realized by that when the instantaneous value of the voltage of a bus zero exceeds the limit, a fault wire selection device is started immediately and used for recording the wave. The invention adopts a digital filter algorithm to obtain the bus zero voltage and the transient pure fault components of zero current on each feedback line. When a low current grounding system takes place a single-phase earth fault, the waveform of the zero current is quantitatively solved by using measuring post simulation according to the transient pure fault component of the measured value of the bus zero voltage and the feeder zero distribution capacitor parameter under the assumption premise of the perfect feeder of every feeder. The invention carries out correlativity analysis to compare the measured waveform of the current of every zero current with the transient pure fault component solved by the measuring simulation method under a definite data window and calculate both correlative coefficients, thereby the invention forms a line selecting criterion 1 and 2 and can carry out line selection to the system according to the line selecting criterion. The principle analysis and the simulation show that the line selection method has the advantages of accuracy and reliability.

The invention discloses a gesture recognition method based on depth images. The method comprises the following steps: acquiring depth images in a training data set and a test date set by virtue of a depth sensor; calculating the minimal depth values of human body regions in the images, and partitioning gestures in the depth images by use of a depth threshold in combination with a preset condition that a human hand is an object nearest to the sensor; then acquiring projection drawings of the gesture on three orthogonal planes, namely a front-view projection drawing, a side-view projection drawing and a top-view projection drawing; further extracting the outline fragment packet characteristics of the three projection drawings and cascading to form a characteristic vector of the original depth gesture; and finally classifying the gesture characteristic vectors acquired from the depth images to be recognized by virtue of a training classifier, thereby obtaining recognition results of the to-be-recognized gestures. The invention further provides a corresponding gesture recognition system. The method is simple and practical in gesture recognition, high in popularization capability and high in recognition accuracy and can be used for effectively overcoming the influence of adverse factors such as busy background, illumination, noises and self occlusion.

The invention relates to a self-adaptive method for single-phase grounding fault line selection of an electric distribution network by using S transformation energy relative entropy. The method comprises the following steps: when the zero-sequence voltage instantaneous value of a bus is out of limit, starting a fault line selection device immediately; performing S transformation on zero-sequence current in 1/4 cycle after the fault of each line, and calculating transient energy under each frequency of the zero-sequence current of each line by using a complex matrix obtained by the S transformation; and calculating the S transformation energy relative entropy under each frequency of each line and solving the comprehensive S transformation energy relative entropy of each line by using the super-strong recognition capability of the relative entropy to slight differences between signals, and self-adaptively selecting out the fault line by comparing the size of the comprehensive S transformation energy relative entropy of each line under all frequencies. Theoretical analyses and a large number of emulations show that the method effectively avoids the influence caused by a CT saturation discontinuous angle on the line selection, and is applicable to the cable-wire mixed line, pure cable lines and pure aerial lines.

A precise measuring method for the static image of cutting tool includes such steps as locating the precise coordinate position of the margin of said static image by digital image processing method, calculating the precise geometric parameters of cutting tool, and obtaining the envelope of said cutting tool. Its advantages are high percision and anti-interference power, and high locating correctness.

The invention discloses a bridge detection method and detection system based on vehicle-bridge coupling vibration analysis. The bridge detection method comprises the following steps: obtaining time-variant model parameters and time-invariant model parameters of having or not having vehicle passing through a group of sensors which are arranged on a bridge in the length direction; computing mass-normalized mode coefficients at moments of a bridge structure; resolving an average value of zoom coefficients at all moments; obtaining a mass-normalized mode of the structure; reconstructing a frequency-function matrix of the structure; conducting displacement flexibility identification. According to the invention, the bridge detection method addresses the inconvenience of on-site detection and poor precision of current flexibility detection devices, overcomes the inability of environment vibration to identify deep parameters of the structure and the high difficulty of impact vibration on-site detection. The detection method not only can obtain static deformation of the structure, and can obtain rigidity information of the structure, thus providing effective evaluation of the safety of the bridge structure.

A power source apparatus with a saving in wiring, large noise immunity and an additional function is achieved by connecting AC input bus lines (Vin+), (Vin−), DC output bus lines (Vo+), (Vo−) and a current balance signal bus line (CB) for connecting first, second, third power source units 1, 2, 3 through connectors to form a module power source and connecting an additional function unit 4 for adding a predetermined additional function to the module power source using the bus lines to this module power source through a connector.

A vector geographic space data watermarking-method based on integer wavelet transform includes fetching original vector geographic space data from mapping databank, enciphering watermark information with chaos sequence, carrying out integer wavelet transform on coordinate string of said geographic space data and embedding watermark information into low frequency coefficient of wavelet transform; picking up watermark information by comparing wavelet coefficient mutual relation of data string to be tested to original reference data string when watermark is required to be picked up.

The invention discloses a training method for a short-speech speaker recognition model. The method comprises steps of extracting acoustic features from speech data of a training corpus; performing phoneme labeling on the speech data of the training corpus to obtain phoneme labeling results; performing phoneme-related GMM-UBM model training to obtain a phoneme-related GMM model and a UBM-model of a speaker according to the acoustic features and the phoneme labeling results; and based on the phoneme-related GMM model and the UBM model, generating a phoneme-related i-vector total variation matrix for extracting i-vector features for each phoneme; and extracting the phoneme-related i-vector parameters from data of each speaker using the phoneme-related i-vector total variation matrix, and performing dimension reduction to obtain the phoneme-related i-vector features of the speaker. As a speaker model, the present invention creates a phoneme-related i-vector model for the speaker to make the model more accurate and improves the recognition accuracy.

The invention provides a motion blurring and defocusing composite blurring image restoration method. By the method, parameter estimation and image restoration can be performed on a motion blurring and defocusing image, and the method comprises the following steps of: (1) establishing a gauss white noise template, and convoluting a degraded image and the white noise template to fulfill the aim of removing noise; (2) estimating a main blurring direction and a secondary blurring direction of the image through an image energy spectrum; (3) calculating a main directional derivative matrix and a secondary directional derivative matrix of the image; (4) performing self-correlation operation and directional accumulation operation on the main directional derivative matrix and the secondary directional derivative matrix respectively; (5) estimating a main direction blurring length and a secondary direction blurring length according to the self-correlated accumulation curve of a main directional derivative and the self-correlated accumulation curve of a secondary directional derivative; (6) establishing a composite blurring model according to the obtained main direction blurring length and secondary direction blurring length; and (7) restoring the degraded image by using wiener filtering.

The invention provides a nonlinear active-disturbance-rejection control method for a vertically rising and falling repeatedly-used carrier. The method comprises the following steps of step 1,attitudecontrol model establishment; step 2,TD tracking differentiator design; step 3,nonlinear expansion state observer design; step 4,nonlinear active-disturbance-rejection controller design; and step 5,nonlinear feedback control law design. The nonlinear active-disturbance-rejection control method for the vertically rising and falling repeatedly-used carrier is provided for the defects of longer attitude response time,weak anti-noise ability,lower attitude control precision and the like of an existing active-disturbance-rejection controller,combines a nonlinear TD tracking differentiator with a finite time convergence characteristic,an expansion state observer with fixed time convergence and a nonlinear feedback control law to form a novel nonlinear active-disturbance-rejection controller,thereby improving the complex external interference rejection ability of a system,and also improving the attitude control precision and response speed.

A landmark detection apparatus and method, the apparatus including a first detection unit that generates N first sample blocks in a first sampling region using a first weighted sampling method according to a first degree of dispersion, and that performs a first landmark detection by comparing a feature of each first sample block a feature of a landmark model, where the first sample region is set to the entirety of a current frame image; and a second detection unit that generates N second sample blocks in a second sampling region using a second weighted sampling method according to a second degree of dispersion, and that performs a second landmark detection by comparing a feature of each second sample block the feature of the landmark model, where the second sampling region is set to an area less than the entirety of the current frame image.