A method of compressing digital signal data obtained from a signal is described. The method includes: receiving digital signal data associated with a signal and/or generating digital signal data based on a signal; transforming the digital signal data into a transform domain, thereby generating transformed digital signal data; determining at least one characteristic parameter based on the transformed digital signal data by an artificial intelligence circuit; detecting and/or classifying at least one wanted signal portion based on the at least one characteristic parameter by the artificial intelligence circuit; and storing only a subset of the digital signal data that is associated with the at least one wanted signal portion. Further, a signal compressor circuit for compressing digital signal data obtained from a signal and a computer program are described.

In a compression mode in which plaintext data is input, and compressed, a first code that is an error detection code is generated with respect to the plaintext data, and compressed. A circuit generates restored plaintext data in which the compressed data is decompressed, for confirming successfulness. A second code that is an error detection code is generated with respect to the restored plaintext data and is compared with the first code. In a case where the first code and the second code agree, the compressed data and the first or second code are output. In a decompression mode, plaintext data is generated in which the input compressed data is decompressed. A third code that is an error detection code is generated with respect to the plaintext data and is compared with an input code, and when the input code and the third code agree, the plaintext data is output.

A processing device, operatively coupled with a memory device, is configured to perform a write operation on a page of a plurality of pages of a data unit of a memory device. The processing device further generates a parity page for data stored in the page of the data unit and associates the parity page with parity data associated with the data unit. Responsive to determining that a first size of the parity data is larger than a first threshold size, the processing device compresses the parity data. Responsive to determining that a second size of the compressed parity data is larger than a second threshold size, the processing device releases at least a subset of the parity data corresponding to a subset of the data that is free from defects.

To generate an optimum compressor irrespective of the number of dimensions and a format of a multidimensional dataset. A storage system refers to dimension setting information, which is information representing an attribute for each of data dimensions of the multidimensional dataset, and generates a compressor based on the dimension setting information.

Techniques for classifier generalization in a supervised learning process using input encoding are provided. In one aspect, a method for classification generalization includes: encoding original input features from at least one input sample {right arrow over (x)}.sub.S with a uniquely decodable code using an encoder E() to produce encoded input features E({right arrow over (x)}.sub.S), wherein the at least one input sample {right arrow over (x)}.sub.S comprises uncoded input features; feeding the uncoded input features and the encoded input features E({right arrow over (x)}.sub.S) to a base model to build an encoded model; and learning a classification function {tilde over (C)}.sub.E() using the encoded model, wherein the classification function {tilde over (C)}.sub.E() learned using the encoded model is more general than that learned using the uncoded input features alone.

Codebook data compaction using a universal codebook and mismatch probability estimations to improve entropy encoding methods. Training data sets are analyzed to determine the frequency of occurrence of each sourceblock in the training data sets. A mismatch probability estimate is calculated comprising an estimated frequency at which any given data sourceblock received during encoding will not have a codeword in the codebook. Entropy encoding is used to generate codebooks comprising codewords for data sourceblocks based on the frequency of occurrence of each sourceblock. A mismatch codeword is inserted into the codebook based on the mismatch probability estimate to represent those cases when a block of data to be encoded does not have a codeword in the codebook.

A method for optical communication includes combining jointly source coding with LDPC channel coding into a nonuniform signalling by mapping low-complexity variable-length prefix codes onto a constellation; and performing arbitrary nonuniform signalling, where information bits and parity bits are transmitted with different modulation schemes.

Methods and systems for storing data include compressing data inflated from a first compression format into a second format using a processor and verifying contents of the data concurrently with compressing the data. Compression is aborted responsive to a failure of the content verification, but an output of the compression is stored to a tape drive until the compression is aborted. The tape drive is rolled back to a file start position after the compression is aborted and compression of any remaining uncompressed data is skipped after the compression is aborted. The data is stored to the tape drive after rolling the tape drive back.

Systems and methods are provided for reducing error in data compression and decompression when data is transmitted over low bandwidth communication links, such as satellite links. Embodiments of the present disclosure provide systems and methods for variable block size compression for gridded data, efficiently storing null values in gridded data, and eliminating growth of error in compressed time series data.

Methods and systems for storing data includes inflating received data having a first compression format. Blocks are created from the inflated data for a second compression format. The blocks are compressed in the second format using a processor. The contents of the blocks are verified concurrently with compressing the blocks. Compression is aborted if the verification of the contents fails. An output of the compression is stored if verification of the contents succeeds and storing the received data if verification of the contents fails.