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77 results about "Random mapping" patented technology

When the data vectors are high-dimensional it is computationally infeasible to use data analysis or pattern recognition algorithms which repeatedly compute similarities or distances in the original data space. It is therefore necessary to reduce the dimensionality before, for example, clustering the data. Random Mapping (RM) is a fast dimensionality reduction method categorized as feature extraction method. The RM consists in generation of a random matrix that is multiplied by each original vector and result in a reduced vector. In Text mining context, it is demonstrated that the document classification accuracy obtained after the dimensionality has been reduced using a random mapping method will be almost as good as the original accuracy if the final dimensionality is sufficiently large (about 100 out of 6000). In fact, it can be shown that the inner product (similarity) between the mapped vectors follows closely the inner product of the original vectors.

Method based on linear programming for locating near-field targets and system thereof

The invention provides a method based on linear programming for locating near-field targets and a system thereof, particularly a method for locating near-field targets on the basis of the compressivesensing theory. The method comprises the following steps: selecting a reference array element under the condition that the signal form is unknown, allowing the reference array element to work at the normal sampling frequency, and the other array elements to work at far below the Nyquist sampling frequency; taking the output signal of the reference array element as the reference target signal, to acquire the sample data of all the array elements; generating a time-delay table and a sparse basis array; generating a random mapping array and obtaining a coefficient array; obtaining a sparse vectorby linear programming solution; and acquiring the location information of the near-field target from the predetermined location-distance collection on the basis of the acquired estimation results ofthe sparse vector. According to the invention, the sensor does not need to work beyond the Nyquist sampling frequency, thereby greatly reducing the sampling rate, reducing the operating energy consumption of the sensor and improving the resource utilization rate of the system; and the method has no limits to the target bandwidth, so that the method is applicable to the target location of both narrowband and wideband, and the method is further applicable to non-Gaussian target location.
Owner:INST OF ACOUSTICS CHINESE ACAD OF SCI

Physical signal collaborative compression sensing system and method for sensor network

The invention discloses physical signal collaborative compression sensing system and method for a sensor network. The system comprises physical signal sensing nodes, a physical signal reconstruction node and a time synchronization node; wherein all physical signal sensing nodes are used for sampling physical signals, carrying out random mapping on sampled signal vectors to obtain a random mapping value, simultaneously carrying out statistic calculation on sampled signals to obtain a statistic value and transmitting the random mapping value and the statistic value into the physical signal reconstruction node; and the physical signal reconstruction node is used for collecting the random mapping value and the statistic value from the physical signal sensing nodes, finishing the matrix normalization of the random mapping value and realizing the physical signal reconstruction on the basis of a compression sensing reconstruction algorithm. The invention can reduce the data communication volume of each node, prolongs the service life of the whole wireless sensing network and simultaneously realizes the reconstruction and the effective sensing of the physical signals under the conditions of deep fading channel environment, local node failure and high data packet loss rate.
Owner:上海中科赛思信息工程有限公司

Remote biological feature identity authentication method for strengthening privacy protection

The invention provides a remote biological feature identity authentication method for strengthening privacy protection. The method comprises a preprocessing stage, a registration stage and an authentication stage, wherein the preprocessing stage comprises the following steps: inputting a safety parameter, generating a user terminal private key and an application-side public-private key pair, obtaining a transform key for each user terminal to prestore at an application-end; the registration stage comprises the following steps: transmitting the public key to the user terminal through the application-side, generating a saving template for the input biological feature in a TrustZone trust computing zone of the user terminal by using the improved random mapping algorithm, and performing encryption protection on the random mapping matrix; the authentication stage comprises the following steps: generating the transform feature for the input biological feature by using the improved random mapping algorithm, and performing the feature matching by the application-side to realize the identity authentication. By using the technical scheme provided by the invention, the privacy protection of the user fingerprint can be strengthened, and the technical scheme has high attack resistance and the universality of the application.
Owner:WUHAN UNIV

Phase change memory abrasion balancing method and system based on random mapping

The invention provides a phase change memory abrasion balancing method based on random mapping. The method includes the steps that a memory address random mapping table is generated to serve as a current memory address random mapping table; s / M table items are included in the current memory address random mapping table; s represents the size of a phase change memory, and M represents the size of a phase change memory row; when memory writing operation occurs, if a writing time counter does not reach a preset writing time threshold value, whether adjustment zone bits of corresponding table items in the current memory address random mapping table have been set is judged; if the adjustment zone bits of corresponding table items in the current memory address random mapping table have been set, a mapping relation between a logical memory address and a physical memory address of the current memory address random mapping table is utilized for address conversion; otherwise, a memory adjustment process is conducted, and physical address values and the adjustment zone bits of corresponding table items in the current memory address random mapping table are corrected. According to the method, the phase change memory abrasion balancing effect can be improved, the service life of a phase change memory is prolonged, and influences on performance are reduced to minimum.
Owner:TSINGHUA UNIV

Beam selection method and device based on beam forming, base station and terminal

The invention provides a beam selection method and device based on beam forming, a base station and a terminal. The method comprises a step of generating a pseudo random orthogonal reference signal sequence, a step of determining an alternative reference signal and an alternative emission beam corresponding to each sub frame sequence according to a first preset pseudo random mapping relation among a reference signal sequence, an emission beam sequence and a sub frame number, a step of sending the alternative reference signal corresponding to the current sub frame number to the terminal by the alternative emission beam corresponding to the current sub frame number through a mode of beam forming according to a time sequence, and a step of carrying out beam selection through a target emission beam and the target reception beam of the terminal according to the beam information of the target emission beam returned by the terminal. According to the beam selection method and device based on beam forming, the base station and the terminal, the inter-cell interference can be greatly reduced, a flash effect is effectively overcome, a problem of the wrong selection of the target emission beam and the target reception beam caused by reference signal collision is reduced, and the performance of the communication system is improved.
Owner:BEIJING XIAOMI MOBILE SOFTWARE CO LTD

Foundation cloud atlas classification method based on spatial pyramid random mapping

The invention discloses a foundation cloud atlas classification method based on spatial pyramid random mapping. The method comprises the following steps of firstly, extracting local features from each training foundation cloud atlas sample in a denseness sampling manner; then, carrying out dimensionality reduction on each local feature by applying random mapping, and mapping an original high-dimensionality feature set to a low-dimensionality subspace; then, clustering features which are subjected to dimensionality reduction in the low-dimensionality subspace, so as to obtain a codebook; then, dividing a sample image into different areas according to a spatial pyramid model, obtaining area features of the different areas according to the codebook, combining the area features, and taking the combined area features as final feature representation of the sample image; finally, obtaining a classification result of a tested foundation cloud atlas by applying a support vector machine classifier. According to the method, spatial information of the image can be obtained through applying the spatial pyramid model, so that information in the cloud atlas can be better represented; meanwhile, the local features of the image are subjected to dimensionality reduction by adopting random mapping, so that the efficiency of a foundation cloud atlas classification system can be increased, the time expense is reduced, and the dimensionality disaster can be avoided.
Owner:康江科技(北京)有限责任公司

Bearing fault diagnosis method based on hierarchical extreme learning machine

The invention provides a bearing fault diagnosis method based on a hierarchical extreme learning machine, and belongs to the technical field of mechanical part fault diagnosis, and the method comprises the steps: decomposing a vibration acceleration signal into a plurality of modal components through a VMD algorithm; selecting the first four modals sorted according to the size of the center frequency, carrying out feature extraction through an SVD algorithm, mapping input feature data into a random sparse hidden layer space, obtaining hidden information between training samples, and carrying out random mapping again on the feature data processed by the previous layer by each hidden layer through a sparse automatic encoder; and obtaining an optimal neural network weight through a fast iterative shrinkage algorithm (FISTA), so that the actual output is close to the specified label data. According to the method, noise reduction and accurate classification are realized at the same time, and the recognition accuracy and the feature information utilization rate can be improved under the condition of a hierarchical extreme learning machine; compared with an original extreme learning machine, higher recognition precision and higher training speed can be achieved in fault diagnosis of rolling bearing signals.
Owner:BEIJING JIAOTONG UNIV

Human body posture recognition method based on convolutional neural network

The invention discloses a human body posture recognition method based on a convolutional neural network. The method comprises the steps that original data of a mobile sensor are collected and labeled,data frequency down-sampling and normalization processing are conducted, a training set and a test set are divided, the convolutional neural network is trained, and a model is transplanted to an Android terminal for human body posture recognition. The method is used for human body posture recognition according to a convolutional neural network. According to the method, a Spit-Transform-Merge strategy is introduced into the implementation of the method; a group of Lego convolution kernels with a smaller channel number is provided, the convolution kernels are stacked according to a random mapping and cyclic matrix method so as to realize convolution operation, and finally, generated Lego feature maps are vertically combined and sent to a classifier through a full connection layer for sensordata identification. The method has the advantages of being high in recognition speed, high in recognition accuracy, small in calculation amount, high in generalization capacity and the like, and meanwhile the method plays a very important role in smart home, health detection, motion tracking and the like.
Owner:NANJING NORMAL UNIVERSITY

Random mapping code-based data transmission method in wireless relay system

The invention relates to a random mapping code-based data transmission method in a wireless relay system. The method includes the following steps that: S1, a weight vector w is given, a source node obtains RPC symbols through adopting a random mapping mode establishing method and based on w and a binary information sequence, and broadcasts an RPC symbol x; S2, a relay node receives an RPC symbol ysr which is broadcasted by the source node through a channel and performs Coset encoding on the RPC symbol ysr so as to obtain an RPC symbol lr which has been subjected to quantized modulo operation, and forwards the RPC symbol lr to a destination node; S3, the destination node receives an RPC symbol ysd which is broadcasted by the source node through a channel and an RPC yrd which is broadcasted by the relay node through a channel, and performs joint decoding on the RPC symbol ysd and the RPC yrd to obtain the binary information sequence. Compared with the prior art, and according to the method of the invention, the peak signal to noise ratio of signals can be decreased through quantized compression at the relay node, a random mapping code-based receiving end link adaptive relaying strategy can be realized, and the throughput of a system can be obtained.
Owner:TONGJI UNIV
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