A method for managing data includes obtaining a compression algorithm selection request for a data object, wherein the data object is generated by a production host, identifying, in response to the compression algorithm selection request, a set of production host performance objectives of the production host, performing a compression algorithm selection analysis using the set of production host performance objectives and a compression selection model to obtain a compression algorithm selection for a compression algorithm, specifying the compression algorithm to the production host using a data agent, wherein the data agent is operatively connected to the production host, initiating a compression on the data object using the data agent by applying the compression algorithm to obtain a compressed data object, and initiating a storage of the compressed data object.

The invention relates to the representation of digital signals. In order to improve the perception by a user of the quality of a digital signal, a first sample of first digital signal is approximated to a second sample of a second digital signal having a second number of significant bits lower than the first number of significant bits of the first sample. The second number of significant bits is also lower than a number of significant bits allowing the second digital signal, or a signal derived therefrom to match an expected bit depth of a processing unit said second digital signal, or a signal derived therefrom is to be sent to.

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.

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.

The present invention relates to methods, systems, and apparatus for processing audio signals. An exemplary method embodiment includes the steps of: removing silence from an audio signal; determining, for a plurality of time segments of the audio signal, power spectral density values of the audio signal for each of a plurality of N different frequency bins, N being an integer greater than 1; identifying (i) a plurality of dominant frequency peaks based on the determined power spectral density values, and (ii) positions in the audio signal corresponding to the identified peaks; and generating a first audio fingerprint from at least some of the identified plurality of dominant frequency peaks and the identified positions in the audio signal corresponding to the identified peaks. In various embodiments, audio fingerprints are generated from an audio signal of call and then used to determine if the call is a robocall or SPAM call.

A method for compressing a flow of CAN-bus messages, which comprises: (A) during a training stage: (a) determining at least one series-type pattern; (b) defining a compressed series-type command for each of said patterns, each command comprising parameters of: (b.1) a timestamp of a first message; (b.2) a message-ID; (b.3) a type of pattern; (b.4) an indication of a field within the messages; (b.5) a parameter value at the first message; (b.6) period between messages; and (b.7) number of messages; (B) during a compression stage: (c) dividing a record of CAN-bus messages into groups of a same message-ID; (d) within each group, finding messages of a same pattern; (e) for each series, forming a compressed command in a form as defined with values for at least several parameters; and (C) during a decompression stage: (f) using the series-type compressed commands to reconstruct the content of the series of messages.

Systems and methods include accessing streams of sensor data; constructing a corpus of seed sample data; initializing a first instance of a trained model using the corpus of seed sample data that: generates predictions of predicted sensor values; computing error values based on calculated differences between the actual sensor values and the predicted sensor values; transmitting the computed error values; initializing a second instance of the trained model based on an input of the corpus of the seed sample data, wherein the second instance of the trained model is identical to the first instance of the trained model, and wherein the second instance: generates inferences of predicted sensor values for each of the sensors based on the input of the corpus of seed sample data; reconstructing estimates of the actual sensor values based on a reconstruction computation with the parallel predicted sensor values and the error values.

A method for managing data includes obtaining a compression algorithm selection request for a data object, wherein the data object is generated by a production host, identifying, in response to the compression algorithm selection request, a set of production host performance objectives of the production host, performing a compression algorithm selection analysis using the set of production host performance objectives and a compression selection model to obtain a compression algorithm selection for a compression algorithm, specifying the compression algorithm to the production host using a data agent, wherein the data agent is operatively connected to the production host, initiating a compression on the data object using the data agent by applying the compression algorithm to obtain a compressed data object, and initiating a storage of the compressed data object.

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.

The invention relates to the representation of digital signals. In order to improve the perception by a user of the quality of a digital signal, a first sample of first digital signal is approximated to a second sample of a second digital signal having a second number of significant bits lower than the first number of significant bits of the first sample. The second number of significant bits also depends upon the value of the first sample.