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465 results about "Generator matrix" patented technology

In coding theory, a generator matrix is a matrix whose rows form a basis for a linear code. The codewords are all of the linear combinations of the rows of this matrix, that is, the linear code is the row space of its generator matrix.

Density evolution based polarization code constructing method and polarization code coding and decoding system

The invention discloses a density evolution based polarization code constructing method and polarization code coding and decoding system. According to the invention, the code length N and the information bit length K of an information code to be processed are obtained, an expectation value set of a log-likelihood ratio probability density function of N bit channels, K bit channels are selected as the information bit channels according to the expectation value set and information bit information index vector quantity is generated; an information bit sequence and a fixed bit sequence are mixed and the mixed bit vector quantity is multiplied by a polarization code for generating a matrix so as to output an encoding sequence; the encoding sequence is modulated and input into a transmission channel and the sequence output by the transmission channel is subjected to decoding operation by adopting a polarization code decoding algorithm, bit error probability and frame error rate of the decoded code are calculated and a design signal to noise ratio is changed, the above operation is repeated until the bit error probability and frame error rate become the minimum. The method and system provided by the invention are suitable for general binary system memoryless channels, the bit error probability and frame error rate are low, the calculation complexity is low and the communication performance of a communication system is improved.
Owner:SHENZHEN UNIV

Computationally Efficient Transfer Processing and Auditing Apparatuses, Methods and Systems

The Computationally Efficient Transfer Processing and Auditing Apparatuses, Methods and Systems (“CETPA”) transforms transaction record inputs via CETPA components into matrix and list tuple outputs for computationally efficient auditing. A blockchain transaction data auditing apparatus comprises a blockchain recordation component, a matrix Conversion component, and a bloom filter component. The blockchain recordation component receives a plurality of transaction records for each of a plurality of transactions, each transaction record comprising a source address, a destination address, a transaction amount and a timestamp of a transaction; the source address comprising a source wallet address corresponding to a source digital wallet, and the destination address comprising a destination wallet address corresponding to a destination virtual currency wallet; verifies that the transaction amount is available in the source virtual currency wallet; and when the transaction amount is available, cryptographically records the transaction in a blockchain comprising a plurality of hashes of transaction records. The Bloom Filter component receives the source address and the destination address, hashes the source address using a Bloom Filter to generate a source wallet address, and hashes the destination address using the Bloom Filter to generate a destination wallet address. The Matrix Conversion component adds the source wallet address as a first row and a column entry to a stored distance matrix representing the plurality of transactions, adds the destination wallet address as a second row and column entry to the stored distance matrix representing the plurality of transactions, adds the transaction amount and the timestamp as an entry to the row corresponding to the source wallet address and the column corresponding to the destination wallet address; and generate a list representation of the matrix, where each entry in the list comprises a tuple having the source wallet address, the destination wallet address, the transaction amount and the timestamp.
Owner:FMR CORP

Method for classifying multi-spectral remote sensing data land use based on semi-supervisor manifold learning

InactiveCN102129571ALow costRealize Land Use ClassificationCharacter and pattern recognitionHat matrixSensing data
The invention discloses a method for classifying multi-spectral remote sensing data land use based on semi-supervisor manifold learning, relating to a land use classification method. The method comprises the following steps of: taking the multi-spectral remote sensing data as a sample data set according to a wave band generator matrix of the data; selecting a part of sample data from the sample data set, marking sample class labels according to priori knowledge, and randomly selecting a part of sample data as unmarked data from the sample data set; establishing a similarity graph and a difference graph to measure the similarity and the difference of data points, and calculating a weight matrix; calculating according to an optimal target function to obtain a projection matrix; projecting the whole multi-spectral remote sensing data; and executing the land use classification by using a K-adjacent classification algorithm. The invention adds the randomly selected unmarked sample data by utilizing a semi-supervisor manifold learning method, calculates the projection matrix by the optimal target function so as to increase the precision of the land use classification and effectively saves the cost of marking the training sample classes at the same time.
Owner:CHONGQING UNIV
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