Encoding of a plurality of encoded symbols is provided wherein an encoded symbol is generated from a combination of a first symbol generated from a first set of intermediate symbols and a second symbol generated from a second set of intermediate symbols, each set having at least one different coding parameter, wherein the intermediate symbols are generated based on the set of source symbols. A method of decoding data is also provided, wherein a set of intermediate symbols is decoded from a set of received encoded symbols, the intermediate symbols organized into a first and second sets of symbols for decoding, wherein intermediate symbols in the second set are permanently inactivated for the purpose of scheduling the decoding process to recover the intermediate symbols from the encoded symbols, wherein at least some of the source symbols are recovered from the decoded set of intermediate symbols.

A processing device includes an accelerator circuit to identify a byte in a byte stream, determine whether a first byte string starting from a first byte position of the byte matches a second byte string starting from a second byte position, responsive to determining that the first byte string matches the second byte string, generate a token comprising a first symbol encoding a length of the first byte string and a second symbol encoding a byte distance between the first byte position and the second byte position, and responsive to determining that the first byte string does not match another byte string, generate the token comprising the first symbol comprising the byte and a second symbol encoding a determined value.

An MAP algorithm-based Turbo decoding method and apparatus. The method includes: iteratively estimating an information symbol by using an MAP algorithm, acquiring an and window boundary values of each sliding window by means of window boundary value inheritance, acquiring an block boundary value and block boundary value of each sub-block by means of block boundary value inheritance, and recursively calculating posterior probability Log Likelihood Ratio (LLR) values of a whole window and a whole block according to the boundary values and the boundary values (101); and performing decoding decision according to the LLR values (102).

Compressing and restoring data using a multi-level autoencoder and a correlation network. The multi-level autoencoder compresses (in the encoder section) and decompresses (in the decoder section) data streams, and a separate correlation network trained on groups of input data sets restores lost data by leveraging correlations between the data sets.

A system, method, and non-transitory computer readable medium for in-field seismic data compression. The system includes geophones each having a 1-bit adaptive delta modulation for converting analog seismic signals to a modulated signal and transmitting the modulated signal, and a data collection center having a 1D convolutional neural network for receiving and compressing the transmitted modulated signal. The 1D CNN is configured to suppress quantization and random noise in the modulated signal.

The transmission of broadcast data, such as financial data and news feeds, is accelerated over a communication channel using data compression and decompression to provide secure transmission and transparent multiplication of communication bandwidth, as well as reduce the latency. Broadcast data may include packets having fields. Encoders associated with particular fields may be selected to compress those particular fields.

A system utilizing a high throughput residual coding mode for CABAC in HEVC is described. The system may include an electronic device configured to obtain a bitstream; recover a binary symbol from the obtained bitstream; determine whether the binary symbol is to be decoded using a high throughput residual coding mode; in response to determining that the binary symbol is not to be decoded using the high throughput residual coding mode, use a first coding technique to obtain a block of Transformed and Quantized Coefficients (TQCs); and, in response to determining that the binary symbol is to be decoded using the high throughput residual coding mode, use a second different coding technique to obtain a residual sample.

Disclosed are methods and systems for significantly compressing sparse multidimensional ordered series data comprised of indexed data sets, wherein each data set comprises an index, a first variable and a second variable. The methods and systems are particularly suited for compression of data recorded in double precision floating point format.

A method and apparatus for conversion of a time interval to a digital word, the time interval being mapped to a difference of a length of a reference time and a length of a signal time. Reference time is generated from an instant when the beginning of the time interval is detected, and the signal time is generated from an instant when the end of the time interval is detected by the use the control module. The generation of the reference time and the signal time is terminated at the same instant. In the apparatus, bottom plates of capacitors of the set of capacitors are connected to a ground of the circuit, and top plates of these capacitors are connected, respectively, to moving contacts of change-over switches. First, second, and third stationary contacts are connected to the signal rail, the ground of the circuit, and to the reference rail.

A compression engine and method for optimizing the high compression of a content addressable memory (CAM) and the efficiency of a static random access memory (SRAM) by synchronizing a CAM with a relatively small near history buffer and an SRAM with a larger far history buffer. An input stream is processed in parallel through the near history and far history components and an encoder selects for the compressed output the longest matching strings from matching strings provided by each of the near history and far history components.