30results about How to "Reasonable complexity" patented technology

High quality communications among a diverse set of cognitive radio (CR) nodes is permitted while minimizing interference to primary and other secondary users by employing Dynamic Spectrum Access (DSA) in a Dynamic Cellular Cognitive System (DCCS). Diverse device types interoperate, cooperate, and communicate with high spectrum efficiency and do not require infrastructure to form the network. The dynamic cellular cognitive system can expand to a wider geographical distribution via linking to existing infrastructure.

The method for compressive sensing (CS) and reconstruction of ultra-wideband (UWB) channels includes building four practically-based dictionaries related to the antenna angles of transmission and angles of arrival that enhance the sparsity of UWB signals. The dictionaries account for the practical effects of the channel, such as pulse dispersion and the unavoidable effects of the antenna. Utilizing the practically-based dictionaries CS is able to reconstruct the UWB signals more efficiently with reasonable complexity. In addition to waveform reconstruction, the dictionaries are used for channel estimation. The CS method can be used with either a single-shot full profile correlator or a Rake receiver. The Rake receiver employs CS in adjusting its parameters to take advantage of the energy available in the strongest propagation paths.

The invention relates to the field of machine learning, and especially relates to a multi-label classification method based on a gravity model, comprising the steps of: acquiring a sample set with labels to serve as a training sample set; calculating the distances from one training sample to other training samples and performing sorting to obtain a near neighbor set of the training sample; in thenear neighbor set, building a positive correlation matrix based on positive correlation properties among the labels, and building a negative correlation matrix based on negative correlation propertiesamong the labels; calculating a near neighbor set of a to-be-detected sample, and building a to-be-detected positive correlation matrix and a to-be-detected negative correlation matrix according to the near neighbor set; obtaining a positive correlation data granule and a negative correlation data granule based on the to-be-detected positive correlation matrix and the to-be-detected negative correlation matrix; and building the gravity model, and performing classification through a gravity relationship between the to-be-detected sample and the positive correlation data granule as well as thenegative correlation data granule. The multi-label classification method of the invention has the beneficial effects that: consideration about a negative correlation relationship between the labels isintroduced, the correlation between the labels is taken full advantage of, and the correlation relationship is mined in the near neighbor set, thereby avoiding global computing and reducing complexity.

The present invention concerns a receiver and a method for retrieving data from Ultra wideband radio transmission signals received by a receiver and transmitted in packets containing at least a preamble known to the receiver and a payload containing data unknown to the receiver. The payload data is formed of at least one burst containing at least one pulse. The method comprises the steps of receiving a signal corresponding to the preamble of a packet by a receiver; determining the energy of the received signal; determining weighting coefficients from the energy of the received signal; receiving a signal corresponding to the payload of a packet by a receiver; determining the energy of the received signal; calculating a threshold depending on the weighting coefficients; and applying a decision rule based on the sampled energy, weighted by said weighting coefficients and depending on said calculated threshold.

A method for providing network access to a plurality of user entities through an access point, said access point comprising a LAN interface and a broadband network interface, the method comprising the following steps at a gateway device: establishing a second secure communication link with said access point; receiving an IP address allocation request from one of said plurality of user entities via said second secure communication link; accessing a AAA server to verify whether a successful authentication of said one of said plurality of user entities on the basis of data related to a mobile subscription associated with said one of said plurality of user entities has already taken place; and upon successful verification, completing an IP address allocation scheme with said one of said plurality of user entities and enabling relaying of data between said one of said plurality of user entities and a PDN; wherein said gateway device is adapted to aggregate a plurality of instances of second secure communication links from different access points towards said PDN.

A computer system and method of automatically generating a Local Grid Refinement (LGR) gridded model of a gas reservoir. A geologic file includes information identifying the locations of one or more wells according to root grid cells within a volume of the earth to be modeled. User inputs specify the number of hydraulic fractures from each well, and such parameters as the fracture length, etc. User inputs also specify the number of “splits” of the root grid cells containing hydraulic fractures; those root grid cells are then split into finer resolution grid cells of increasing width within the root grid cells containing the fractures. For horizontal wells, user inputs indicate the number of splits of root grid cells containing the lateral portions of the wellbore. Non-orthogonal and complex fractures are processed by a “nested” LGR approach. Geologic properties are assigned to each grid cell, with a tensorial adjustment included for non-orthogonal fractures, and the resulting model is available for simulation.

The present invention relates to the field of machine learning, in particular to a multi-label classification method based on a gravitational model, comprising: obtaining a labeled sample set as a training sample set; calculating and sorting the distance between the training sample and other training samples to obtain the training sample Neighbor set; in the neighbor set, the positive correlation matrix is ​​constructed with the positive correlation between the labels, and the negative correlation matrix is ​​constructed with the negative correlation between the labels; the neighbor set of the sample to be tested is calculated, and the positive correlation matrix to be tested is constructed according to the neighbor set. The correlation matrix and the negative correlation matrix to be tested; the positive correlation matrix and the negative correlation matrix to be tested are used to obtain positively correlated data particles and negatively correlated data particles; a gravity model is constructed, and the positively correlated data particles and negatively correlated data are obtained through the sample to be tested The gravitational relationship between particles is classified; the invention introduces the consideration of the negative correlation between labels, fully utilizes the correlation between labels, and discovers the correlation in the neighbor set, avoiding global calculation and reducing the complexity.

The present invention provides a neural network-assisted iterative receiving method suitable for high-speed visible light communication. The purpose of the solution is to modify soft decision information through a neural network receiver to eliminate the influence of clipping distortion. The neural network BICM receiver includes: (1) the cost function adopts the cross entropy function; (2) the training method adopts the backpropagation algorithm; (3) the input layer includes the real part, the imaginary part and the corresponding Gaussian noise of the accepted symbol, and the output layer Get the probability value of each constellation point; (4) The hidden layer and output layer use tanh and softmax functions respectively. Compared with the existing clipping enhancement scheme, the present invention has more obvious suppression effect and reasonable algorithm complexity, and is beneficial to enhance the robustness of DCO‑OFDM against clipping distortion.

The present invention provides a method for determining channel state information, including: a terminal receives an aperiodic channel state information CSI request, and according to the terminal's ability to process channel state information process CSI Process and / or the number of CSI Processes currently configured y to determine the parameter X, and update up to X aperiodic CSI according to the parameter X; wherein, the parameter X is: at the same time, the terminal needs to update the internal CSI Process or The total number of reports. The invention also provides a terminal for determining channel state information. The present invention makes reasonable restrictions on the amount of CSI computation, ensures that the terminal has a reasonable complexity, and ensures that the terminal has a reasonable cost.

The invention relates to an NPRACH signal detection method and a device, an NPRACH receiver and a storage medium. The method comprises the following steps: acquiring a check matrix model of a terminalsignal in an NPRACH; wherein the test matrix model comprises an RCFO variable and a TA variable; carrying out eigenvalue decomposition on the test matrix model to obtain a maximum eigenvalue of the test matrix model as a test metric value; comparing the test metric value with a detection threshold value; if the test metric value is not less than the detection threshold, determining that a terminal signal exists in the NPRACH, and calculating a feature vector corresponding to the test metric value as a basic vector; constructing a signal value optimization model according to the basic vector;and solving the signal value optimization model, when the maximum value of the target function is obtained, obtaining the value of a parameter variable in the signal value optimization model, and determining the optimal detection value of the terminal signal in the NPRACH according to the value of the parameter variable. The method is reasonable in complexity, can quickly and accurately estimate the RCFO and TA in the signal, and is good in NPRACH signal detection effect.

A method is proposed for generating an OFDM type multicarrier signal including OFDM blocks constituted by M carriers modulated by source symbols. The method includes the following steps: interleaving the M symbols of a block of source symbols into R sub-blocks of N interleaved symbols; obtaining a block of M time domain samples corresponding to the block of M source symbols; forming a peak vector containing N maximum amplitudes determined from among the M samples; attenuating the extrema of each sub-block of N time domain samples corresponding to the R sub-blocks of N interleaved symbols by a correction of symbols taking account of the peak vector and delivering R sub-blocks of N corrected interleaved symbols; de-interleaving the R sub-blocks of N corrected interleaved symbols delivering a block of M corrected source symbols; generating an OFDM block of the signals corresponding to the block of M corrected source symbols.

Embodiments of the present invention provide a motion prediction or compensation method during a video coding and decoding process. A motion prediction or compensation method provided in the embodiments of the present invention includes: acquiring a candidate motion vector set; conducting a refined search for an optimal motion vector based on information of the candidate motion vector set; and performing motion prediction or compensation by using the motion vector acquired by the refined search. This improves coding performance and meanwhile maintains reasonable complexity.

The invention discloses a method and device for accelerating database operations, which are applied to a database connected with a hardware accelerator. The method includes: when receiving an initial execution plan tree sent by the database that needs to be accelerated, Supported basic operations and acceleration resources process the initial execution plan tree and generate a new execution plan tree; if the new execution cost of the new execution plan tree is less than the initial execution cost of the initial execution plan tree, according to the organization and operation of the hardware accelerator, the The new execution plan tree is distributed to the hardware accelerator for execution; the result data after the hardware accelerator accelerates the database operation is determined according to the execution result returned by the hardware accelerator, so that the execution plan tree of the database matches the execution function and capability of the accelerated hardware accelerator And maintain a reasonable complexity, and then give full play to the acceleration capability of the hardware accelerator.