494 results about "Adaptive matching" patented technology

A bidirectional signal processing method uses parallel transmission of digital transmitted data streams in a multiple input-multiple output system. Related art methods generate high bit error rates mostly in singular transmission channels. For this reason, the rank-adaptive signal processing method provides that the number n_d of active subchannels are varied according to the actual channel behavior in order to effect a robust data transmission even in singular radio channels based on a transmit-side and receive-side channel knowledge and a modification of the data vector by a linear matrix vector multiplication while introducing a factor gamma for limiting the maximum transmit power. The maximum transmit power is then only distributed to the currently activated subchannels so that no transmit power remains unused. Another optimization of the number of subchannels n_d occurs when selecting the modulation and encoding methods. During the optimal rank-adaptation according to the water-filling principle, another power is allocated to each subchannel. Another modulation and encoding method is accordingly selected for each data stream. During the suboptimal rank-adaptation according to the channel inversion principle, all subchannels have the same power whereby enabling the data streams to be modulated and encoded in a common source

The invention discloses a gesture recognition method based on an acceleration sensor. The gesture recognition method based on an acceleration sensor comprises the following steps: automatically collecting gesture acceleration data, preprocessing, calculating the similarity of all gesture sample data so as to obtain a similarity matrix, extracting a gesture template, constructing a gesture dictionary by utilizing the gesture template, and carrying out sparse reconstruction and gesture classification on the gesture sample data to be recognized by adopting an MSAMP (modified sparsity algorithm adaptive matching pursuit) algorithm. According to the invention, the compressed sensing technique and a traditional DTW (dynamic time warping) algorithm are combined, and the adaptability of the gesture recognition to different gesture habits is improved, and by adopting multiple preprocessing methods, the practicability of the gesture recognition method is improved. Additionally, the invention also discloses an automatic collecting algorithm of the gesture acceleration data; the additional operation of traditional gesture collection is eliminated; the user experience is improved; according to the invention, a special sensor is not required, the gesture recognition method based on the acceleration sensor can be used for terminals carried with the acceleration sensor; the hardware adaptability is favorable, and the practicability of the recognition method is enhanced. The coordinate system is uniform, and can be adaptive to different multiple gesture habits.

The invention discloses a method and system for pasting an image to a human face based on affine transformation. Characteristic point locating and characteristic point extraction are carried out on a standard human face image, curve fitting is carried out on extracted characteristic points of the standard human face image through a Lagrange's interpolation method, standard grain coordinates are obtained, then characteristic point locating is carried out on the human face image to be processed, self-adaption matching is carried out on the standard grain coordinates and the corresponding characteristic points of the human face image to be processed through affine transformation according to the actual characteristic points of the human face image to be processed, and transformation grain coordinates are obtained; finally, image pasting materials are drawn on the corresponding characteristic points of the human face image to be processed through the transformation grain coordinates, and an effect human face image is obtained. Therefore, the method and system can adapt to human face portions in various shapes by itself, the processed effect human face image is more natural, and the problem of robustness of automatic decoration is solved.

The invention discloses a voice signal enhancement system and a voice signal enhancement method. The method comprises the following steps of: filtering an input signal by an adaptive filter to obtain a voice reference signal and performing noise extraction processing on the input signal by using a block matrix to obtain a noise reference signal; filtering the noise reference signal and the voice reference signal through multi-channel Wiener filtering to obtain a denoised voice signal; performing voice enhancement processing on the denoised voice signal according to the noise reference signal to obtain an enhanced voice signal and a voice existence probability signal; and updating a filter coefficient of the adaptive matching filter, the block matrix and a filter coefficient and a learning step length of a multi-channel Wiener filter according to the voice existence probability signal. By the voice signal enhancement system and the voice signal enhancement method, under the condition that a microphone array is relatively simple, the problems that convergence cannot be guaranteed, the speed is low and the real-time enhancement distortion is high during real-time tracking of a target source in a practical application environment can be solved.

The invention discloses a depth image estimating method of a binocular stereo video, which comprises the following steps of: (1) collecting a binocular stereo video image from a binocular stereo camera; (2) performing parallax estimation based on graph cut stereo matching on the binocular stereo video image; (3) performing uniformity check on a parallax image obtained by the graph cut stereo matching, and deleting the unreliable matching by self-adapting matching to reduce the wrong matching of the depth image; (4) converting the parallax image into a depth image according to the relation of the parallax and the depth; (5) performing correction optimization on the obtained depth image by a multilateral filter; and (6) outputting the depth image to finish the depth image estimation of the binocular stereo video. The method disclosed by the invention has the advantages of effectively eliminating the errors in the depth image estimation, and finally obtaining an accurate and dense depth image so as to satisfy the demand of rebuilding image quality based on a real scene.

An integrated variable voltage diode capacitor topology applied to a circuit providing a variable voltage load for controlling variable capacitance. The topology includes a first pair of anti-series varactor diodes, wherein the diode power-law exponent n for the first pair of anti-series varactor diodes in the circuit is equal or greater than 0.5, and the first pair of anti-series varactor diodes have an unequal size ratio that is set to control third-order distortion. The topology also includes a center tap between the first pair anti-series varactor diodes for application of the variable voltage load. In preferred embodiments, a second pair of anti-series varactor diodes is arranged anti-parallel to the first pair of anti-series varactor diodes so the combination of the first pair of anti-series varactor diodes and the second pair of anti-series varactor diodes control second-order distortion as well.

According to the general concept disclosed herein, a circuit for adaptive matching of a load impedance to a predetermined load-line impedance of a load-line connected to a power amplifier output includes a fixed matching network between the power transistor and an adaptive matching network, whereby the fixed matching network acts as an impedance inverter which results in a relatively low insertion loss at high power. Results indicate that the impedance-inverting network can be used over more than a factor of 10 in impedance variation. Further, the usage of the fixed matching network, close to the power transistor, allows for the implementation of transmission zeros and/or for a well defined load impedance at a predetermined harmonic frequency, independent of the (variable) load impedance at the fundamental frequency.

Background noise from relevant data sets, including for example over-the-counter sales data, absenteeism data, etc., is subtracted using a background estimation algorithm that outputs residual data. The effects of hypothetical anomalous events, such as a bio-terrorist attack, on the relevant data sets are modeled to create replica data. The replica data may be based on input from epidemiologists and various scenario templates including information on disease manifestation and other intelligence. The residual data and the replica data are then matched using a detector. Types of detectors include for example adaptive matched-filter detectors, change detectors and Bayesian Inference Networks. An alarm is triggered if a real anomalous event similar to a hypothetical anomalous event is detected. A Geographical Information System (GIS) may be used to display data from individual zip codes.

The invention relates to an overlay network layered multicast optimal resource allocation method for a scalable video stream, and provides a new measurement standard for the multicast performance, namely layer extensity which is used for measuring end-to-end time delay of video layers during data distribution aiming at layered multicast communication of the scalable video stream in the overlay network. In order to realize the overall minimization of the layer extensity, the method carries out the combined optimization on the network code of relay nodes, the receiving end driven flow control, and multi-path route strategy, and adopts a linear programming method to establish a layered multicast resource optimum allocation model for the overlay network. On one hand, the method adaptively matches the interlayer dependency of the scalable video code; on the other hand, the method allows a receiving node to decide and regulate the required video quality of own accord. In addition, the invention also provides a distributed heuristic algorithm which has low complexity, approaches the globally optimal solution and is applied to the construction of a scalable video flow distribution network.

The invention discloses a self-adaptive reconstruction and an uncompressing method for power quality data based on a compressive sensing theory. A power quality data compression process with concurrent sampling and compression is achieved through a random measurement matrix, compressive sensing thoughts are used to perform sparse decomposition on the power quality data, sparse signals are subjected to Gaussian measurement encoding, and a self-adaptive matching pursuit algorithm is applied to reconstruct signals. According to the self-adaptive reconstruction and the uncompressing method, the random measurement matrix is simple in structure and quick in operation, in no need of intermediate variable storage space and independent of power disturbance signal characteristics, and has universality; compared with greedy algorithms of an orthogonal matching pursuit and the like, known sparseness is not needed, self adaption and regularization processes are provided, the operation time is short, and accurate reconstruction can be achieved; and constraints of compression after sampling of traditional data compression methods are broken through, little sampling can recover original power quality signals well, and accordingly, requirements for hardware can be reduced, and the compression efficiency is improved.

Adaptive matching of similar data in a data repository to determine if two or more data items are related in accordance with configurable criteria. Matches are adapted by learning and presenting appropriate match criteria based on previous user input. The system can merge the data items into one master data item, group similar items and perform further processing based on the result. The configurable match criteria presented to a user are adapted by the system based on previous interactions of the system with users. Matching is performed by selecting data items to match, removing frequently used strings, normalizing data, tokenizing multi-word data items, assigning weights to each token, calculating a score using the assigned weights, generating groups of similar records, assigning thresholds for match levels. Adapting choices of match criteria for a user based on past interaction allows for rapid match creation and match maintenance that optimizes data integrity across an enterprise.

The invention discloses a broadband radar detection method based on weighted sequence statistics and multiple-pulse coherence accumulation. The method can be used to mainly solve a detection problem under an unknown scene of a high-speed moving target space distribution state. The method is characterize by: generating broadband radar target multipulse echo with clutter and performing FFT to the echo along a distance domain; calculating a clutter normalization covariance matrix; performing prewhitening processing and chirp-z transformation to distance frequency domain data; estimating a target speed and performing phase-coherent accumulation; performing IFFT to the pulse which is performed with the phase-coherent accumulation; calculating each distance unit square envelope of the pulse and performing descending order; carrying out weighted processing to the data after being performed with the descending order; initializing a counter; calculating the adaptive matched filter energy accumulation of a counting distance unit; detecting whether the target exists according to a threshold. By using the method of the invention, the clutter can be effectively inhibited. Migration through resolution cell of the echo can be corrected. Through descending-order weighted processing, the radar can rapidly detect the target under the unknown target space distribution state.

The invention discloses a viewing-angle greatly-variable gait recognition method based on gait three-dimensional contour matching synthesis. The method is characterized by comprising the following steps: detecting a moving body on the basis of a double-mass-center self-adaptive matching for a color and depth image collected by a single depth camera, extracting a gait depth image with background being removed, and repairing the gait depth image on the basis of multi-curve fitting and gauss distribution information fusion; carrying out cloud extraction on gait points; fusing data of all three-dimensional gait surface models within one gait period to generate a three-dimensional fusion gait energy model; rotating two fusion gait models of two training viewing angles to the same viewing angle, completing the surface butt joint of different viewing-angle three-dimensional gait models through the three-dimensional contour matching, and extracting the multi-viewing-angle gait fuzzy contour data; completing the three-dimensional gait classification recognition with the viewing angle being greatly varied through a gait sub-image which is fused with the gait fuzzy contour and an integration classifier. By adopting the method, the problem that the difficulty of viewing-angle greatly-variable gait recognition cannot be solved by the existing gait recognition method can be solved.

The invention discloses an underwater acoustic sparse channel estimation variable step sparsity adaptive matching tracking method, which fully utilizes the underwater acoustic channel sparse multipathcharacteristic and avoids the waste of frequency spectrum resources caused by the excessive number of pilots in the traditional channel estimation technology. The method does not need sparseness as apriori information, and the size of the support set is the estimated sparseness at the end of iteration by expanding the support set through step size. In addition, the signal reconstruction processis divided into several stages by combining stage idea and variable step size, the number of atoms in the support set in a certain phase remains constant, and the adjacent phases gradually expand thesupport set by different step sizes. The invention improves the recovery accuracy on the premise of not significantly increasing the calculation amount, that is, obtains a better trade-off between thereconstruction accuracy and the calculation complexity. Compared with the prior classical greedy algorithm, the invention does not need sparseness as a prior information, and the step size adaptive change can give consideration to the algorithm accuracy and the operation efficiency.

The invention discloses an intelligent hypercompact combination navigation method of a vehicle-mounted GPS software-based receiver, which carries out switching of the intelligent navigation work mode, self-adaptive matching of multi-source system, filter and intelligent navigation positioning against for the hypercompact combination mode of a software GPS (global satellite positioning system) receiver/low cost MINS (Micro Inertia Navigation System). Whether in the high dynamic environment or in the weak satellite signal environment, the method can adequately utilize the information obtained by the subsystems, can intelligently allocate the main system, the auxiliary system and the combination form thereof, can instantly correct and compensate the error, and can effectively realize the vehicle-mounted seamless positioning of the urban traffic.

The invention discloses a terminal equipment software and hardware self-adaptive matching method, which comprises: providing an analog voltage-hardware version lookup list; providing a micro controller which can read the analog voltage-hardware version lookup list; providing a analog to digital converter; providing an analogue voltage division circuit, connecting one end of the analog to digital converter to the voltage division circuit and collecting a voltage division value; and transmitting the voltage division value collected by the analog to digital converter to the micro controller, wherein the micro controller reads the analog voltage-hardware version lookup list according to the obtained voltage division value, searches for a hardware version corresponding to the voltage division value and starts the software of a version corresponding to the hardware version. The method also provides terminal equipment using the method.

A beamforming system including a multiplier stage for providing a plurality of steered signal terms, each term being a product of an input signal term and a steering signal term. A filter multiplies the steered signal terms by a plurality of respective filter weights to provide a plurality of weighted products. The weighted products are summed to provide an output beam directionally responsive to the steering signal. A microprocessor provides the steering signal terms and the filter weights in response to the input signal and/or user input. In the preferred embodiment, the filter is a reconfigurable, general purpose matched filter configured to multiply a plurality of delayed representations of a respective one of the steered signal terms by a plurality of the weights to provide a plurality of intermediate weighted product terms. The filter further includes a summing circuit for accumulating the intermediate weighted product terms to provide a respective one of the plurality of weighted products. The inventive beamforming system cancels unwanted interference, while forming a beam to allow a desired signal to be received with a maximum signal-to-interference-plus-noise ratio (SINR). Through a data-capture RAM, the system allows interference samples to be collected and passed to a microprocessor to calculate the optimum filter weights. The received beam may be steered to any desired direction to form an optimal space-time adaptive matched filter.

A method and system which adaptively recommends potential relationships to individual users based on a set of items that are known to be of interest to the user, such as a set of potential matches previously messaged by the user. The system generates the adaptive recommendations using previously-generated user activity that indicates the user's preferences of particular attributes.

An improved self-adaptive sparse sampling fault classification method belongs to the technical field of fault diagnosis. A traditional sparse classification method is improved. Firstly, a wavelet module maximum value and a kurtosis method are used for carrying out feature enhancement processing on signals, and on the premise that signal sparsity is guaranteed, a unit matrix is adopted to replace aredundant dictionary. Secondly dimension reduction is carried out on data by adopting a Gaussian random measurement matrix, thereby reducing redundant information in the signal, and reserving effective and small amount of data. Then, a sparse coefficient is solved by adopting a sparsity adaptive matching pursuit (SAMP) algorithm, and the compressed signal is reconstructed; and finally, a cross correlation coefficient is adopted as a judgment basis of the category of the fault, so that an improved adaptive sparse sampling fault classification method is provided. Experimental verification proves that redundant information in signals is effectively reduced, the influence of time shift deviation on fault type judgment is avoided, meanwhile, the operation complexity is reduced, and the calculation speed and the reconstruction precision are improved.

A method provides space-time adaptive processing (STAP) for target detection using adaptive matched filters (AMF). A generalized likelihood ratio test (GLRT) is determined where spatial and temporal correlation matrices Q and A are assumed. Then, the correlation matrices A and Q are replaced with maximum likelihood (ML) estimates obtained only from training signals subject to a persymmetric constraint.

The invention discloses an interface matching method, device and system for a PON (passive optical network). The method comprises the following step: PON equipment determines the type of the current network based on a received signal; whether the interface mode of the PON equipment is matched with the type of the current network is judged; the PON equipment enters into the normal working state if the interface mode of the PON equipment is matched with the type of the current network; and then the PON equipment automatically selects an interface matched with the type of the current network and enters the normal working state if the interface mode of PON equipment is not matched with the type of the current network. In the embodiment of the invention, adaptive matching of interfaces can be realized by automatic selection of the PON equipment, thus obviously reducing the equipment management and maintenance cost of network operators.

The invention relates to a method for self-adaptive matching with an aided driving system. The method comprises the steps that the current running speed of a vehicle is compared with preset speeds todetermine whether a first scene or a second scene is enabled for matching, wherein the preset speeds include a first preset speed and a second preset speed; under the situation that the current running speed of the vehicle is greater than the first preset speed, the first scene is enabled for matching, and under the situation that the current running speed of the vehicle is smaller than the secondpreset speed, the second scene is enabled for matching; if specified conditions are met during first scene matching, a first function for aided driving is enabled; if specified conditions are met during second scene matching, a second function for aided driving is enabled. The environment sensing capability of a mature vehicle-mounted radar can be combined to conduct driving state analysis on vehicles running around a vehicle body, the running state of the vehicle and traffic indicating mark information sensed through machine vision are combined to achieve self-adaptive matching with variousfunctions of the aided driving system.

A content addressable memory (CAM) device having any number of rows, each of the rows including a match line connected to a plurality of CAM cells, a match line detector circuit, and a pre-charge circuit. The detector circuit detects a voltage of the match line and generates a feedback signal based on the detected match line voltage. The pre-charge circuit adaptively charges the match line in response to the feedback signal.

The invention provides a device for conducting self-matching on data formats. The device is arranged in a sender web system and comprises a format recognition unit, a judgment unit, a format conversion unit and a data interaction unit. The format recognition unit is used for recognizing the data formats of data to be transmitted in the sender web system, the judgment unit is used for judging whether the data formats of the data to be transmitted are matched with required data formats or not, the data conversion unit is used for converting the data formats of the data to be transmitted into the required data formats under the mismatching condition, and the data interaction unit is used for sending the data to be transmitted after the format conversion to a receiver web system under the mismatching condition, or directly sending the data to be transmitted to the receiver web system. The invention further discloses a method for conducting the self-matching on the data formats. According to the technical scheme, a corresponding achievement can be added to each data format at a client terminal or a service terminal, namely, compatibility of the various data formats can be achieved in data transmission, and the self-adaption matching of the data formats is ensured.

The invention relates to a compressive sensing image reconstruction method based on a pseudo-inverse adaptive matching pursuit (PIAMP), which is characterized by comprising the steps that a gauss random matrix is selected for projecting an image to form a measurement signal matrix; an image sparse base is constructed; each column of the measurement signal matrix is reconstructed by adopting the PIAMP to form a sparse coefficient of each column of the image; and the sparse coefficients of the columns of the image are arrayed and subjected to cosine transformation to form a reconstruction image. The method particularly takes account of the dictionary relevance, iteration stage division and the like in a sparse coefficient reconstruction process, so that selection of the sparse coefficients is more accurate, and the precision of image reconstruction is higher.

The invention discloses a multichannel self-adaptive matching network power amplifier with variable gain, which comprises a state controller, an input matching network, a multichannel power amplifier module with variable gain and an output matching network. The power amplifier adjusts impedance matching networks of the input matching network and the output matching network. The state controller provides a matching selection signal to be used for adjusting the input matching network and the output matching network for various application so as to obtain high linearity and low power consumption. Power amplifier units of the multichannel power amplifier module with variable gain respectively have different saturation output powers. Based on a channel selection signal provided by the state controller, one of the power amplifier units is in operation; therefore, comparatively high efficiency can be obtained in two modes of a mode of comparatively high output power and a mode of comparatively low output power. In quite wide range of the output power, the transmission efficiency of the signals can be improved. The power amplifier of the invention can be applied to various application occasions and have good performance parameters, compared with the existing power amplifier.

The invention provides a variable step size regularized adaptive compressed sampling matching pursuit method, specifically relates to a reconstruction method based on compressed sensing, and a solution aims at the prior two problems in the regularized orthogonal matching pursuit (ROMP) method. One of the problems is that the sparseness K is difficult to be obtained in reality, then the method provides that the adaptive idea of the sparse adaptive matching pursuit (SAMP) is applied in ROMP; the other problem is that once an atom which is selected in a support set will not able be deleted, then the method provides that the backtrack idea of the compressed sampling matching pursuit (CoSaMP) is applied in ROMP. In addition, the method adopts a stage orthogonal matching pursuit (StOMP) idea to set the threshold condition so as to stop the iteration, and the problem including lack of accuracy and over estimated caused by the fixed step size of the introduced SAMP is improved. The method provided by the invention greatly improves the reconstruction performance, estimated accuracy and application range of the reconstruction method based on the compressed sampling.