A method for text compression comprises recognizing a prefix string of one or more text characters preceding a target string of a plurality of text characters to be compressed. The prefix string is provided to a natural language generation (NLG) model configured to output one or more predicted continuations each having an associated rank. If the one or more predicted continuations include a matching predicted continuation relative to the next one or more text characters of the target string, the next one or more text characters are compressed as an NLG-type compressed representation. If no predicted continuations match the next one or more text characters of the target string, a longest matching entry in a compression dictionary is identified. The next one or more text characters of the target string are compressed as a dictionary-type compressed representation that includes the dictionary index value of the longest matching entry.

Significance flags in advanced video compression systems are coded using contexts adaptive to the last N significance flags coded taken in a scanning order. One embodiment uses the last N significance flags in scanning order as a predictor to determine which of a plurality of sets of significance flag contexts to use for coding subsequent significance flags. A second embodiment uses the last N significance flags in scanning order as a predictor in order to modulate the probability value associated with significance flag contexts that are used to code significance flags for future coding.

A disclosure for lossless data compression can include receiving a data block by a processor, performing, by the processor, a sparse transform extraction on the data block, selecting, by the processor, a transform matrix for the data block, modeling, by the processor, the selected transform matrix for the data block, selecting, by the processor, a transform coefficient model for the data block, modeling, by the processor, the selected transform coefficient model for the data block, compressing, by the processor, the data in the data block using the selected transform matrix and the selected transform coefficient model.

The present disclosure provides a data processing system and method. The method may include obtaining preliminary data. The method may also include generating first encoded data by compressing the preliminary data in a first encoding procedure. The method may further include determining whether a compression ratio of the first encoded data is below a compression threshold. The method may still further include generating second encoded data by compressing the preliminary data in a second encoding procedure in response to determining that the compression ratio of the first encoded data is below the compression threshold, wherein the first encoding procedure and the second encoding procedure are lossless compressions.

The present disclosure pertains to systems and methods to compress an input signal representing a parameter in an electric power system. In one embodiment, a system includes a data acquisition subsystem to receive an input signal comprising a plurality of high-speed representations of electrical conditions. A linear prediction subsystem generates an excitation signal estimate based on the input signal, a plurality of linear prediction coefficients based on the input signal, and an estimated signal based on the excitation signal estimate and the plurality of linear prediction coefficients. An error encoding subsystem may generate an encoding of an error signal based on a difference between the input signal and the estimated signal. A non-transitory computer-readable storage medium may store an encoded and compressed representation of the input signal comprising the excitation signal estimate, the plurality of linear prediction coefficients, and the encoding of the error signal.

A method, device, and system for data compression and decompression are provided. The method for data compression comprises, converting data to be transmitted within each period, from the time domain to the frequency domain, wherein, a default time length is set as a period; identifying weak power frequencies in the frequency domain data according to a set identification rule; weighting data transmitted on the identified weak power frequencies to obtain corresponding weighting information; converting other data converted to the frequency domain and the weighted data back to time domain; compressing the data converted back to the time domain; and transmitting, the compressed data along the weighting information.

The technology in this application compresses multi-antenna, complex-valued signals by exploiting both a spatial and a temporal correlation of the signals to remove redundancy within the complex-valued signals and substantially reduce the capacity requirement of backhaul links. At a receiver, the compressed signal is received, and a decompressor decompresses the received signal over space and over time to reconstruct the multiple antenna stream.

Temporal link encoding, including: identifying a data type of a data value to be transmitted; determining that the data type is included in one or more data types for temporal encoding; and transmitting the data value using temporal encoding.

A data management system includes a process reception processing unit that receives input of data in each of processes in plural stages of an item, a compression processing unit that compresses the received data in a case where the process reception processing unit receives the data, and stores the compressed data into a compressed data database, and a decompression processing unit that decompresses the compressed data stored in the compressed database at the predefined date and time before an acquisition process of acquiring data in another process, stored in the compressed database is started, and stores the decompressed data into a decompressed database, the acquisition process being included in the processes in the plural stages.

To reduce data amount while ensuring tactile reproducibility of a two-dimensional tactile signal, and improve the efficiency of a system related to tactile reproduction.

Coding is performed to compress information amount by orthogonally transforming a two-dimensional tactile signal based on a time signal. By orthogonally transforming a two-dimensional tactile signal based on a time signal, it is possible to compress information amount by removing frequency components that are difficult for humans to perceive, as in the case of an image signal, for example. Accordingly, it is possible to reduce data amount while ensuring tactile reproducibility of a two-dimensional tactile signal, and improve the efficiency of a system related to tactile reproduction.