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.

Systems and methods for improving noise efficiency in a Delta Sigma modulator. A bypass scheme for a noise splitter is disclosed that reduces toggling activity for small signals. In particular, a sample-by-sample bypass noise splitter is disclosed that includes a noise splitting module and a bypass line. The bypass line bypasses the noise splitting module when signals are below a selected threshold, increasing efficiency of the system.

A first value of a first data element in a first set of data elements is obtained, the first set of data elements being based on a first time sample of a signal. A second value of a second data element in a second set of data elements is obtained, the second set of data elements being based on a second, later time sample of the signal. A measure of similarity is derived between the first value and the second value. Based on the derived measure, a quantisation parameter useable in performing quantisation on data based on the first time sample of the signal is determined. Output data is generated using the quantisation parameter.

The method involves sequentially encoding the plurality of data packets, which involves, for a data packet, obtaining a reference data packet, obtaining a mask packet indicative of which of the bits in the data packet are predictable and which of the bits in the data packet are not predictable obtaining change history data indicative of previously changed bits of the mask packet, determining an updated mask packet based on the mask packet, the data packet, and the reference data packet, determining updated change history data based on the change history data, the mask packet, and the updated mask packet, determining, as unpredictable bits, all those bits of the data packet that are indicated as not predictable by the updated mask packet, and generating an encoded data packet including a representation of the updated change history data and a representation of values of the unpredictable bits of the data packet.

The invention provides a system improving signal handling, e.g., transmission and/or processing. In an embodiment, the system may include a filter circuit, a magnitude bit truncation circuit and a utility circuit. The filter circuit may be coupled to a target signal which contains one or more desired signals at one or more interested bands, for attenuating each said interested band to form a filtered signal. The magnitude bit truncation circuit may be coupled to the filter circuit, for truncating one or more bits of each sample of the filtered signal to form a truncated signal. The utility circuit may be coupled to the magnitude bit truncation circuit, for handling the truncated signal to implement handling of the target signal, so as to reduce resource requirement and enhance error tolerance comparing with directly handling the target signal.

Quantisation methods are provided which employ dither techniques to reduce the noise penalty in certain circumstances whilst still removing noise modulation. One method relates to reducing the wordwidth of audio by one bit, while another method relates to burying one bit of data in a pair of signal samples.

A MEMS microphone module includes a MEMS microphone, a modulator connected downstream of the MEMS microphone, and an interference compensation circuit to apply an interference compensation signal to an input of the modulator, the interference compensation signal being opposed to a low-frequency signal interference present at the input of the modulator or a block connected upstream of the input of the modulator.

A device includes a sensor configured to output an analog sensor signal, an analog-to-digital converter circuit configured to convert the analog sensor signal into a sigma-delta-modulated digital signal having a bit width of n bits, and a pulse width modulator configured to generate a pulse-width-modulated signal based on the sigma-delta-modulated digital signal.

A processing device for executing a machine learning neural network operation includes memory and a processor. The processor is configured to receive input data at a layer of the machine learning neural network operation, receive a plurality of sorted filters to be applied to the input data, apply the plurality of sorted filters to the input data to produce a plurality of different feature maps, compress the plurality of different feature maps according to a similarity of the feature maps relative to each other and store the plurality of different feature maps in the memory.

A first value of a first data element in a first set of data elements is obtained, the first set of data elements being based on a first time sample of a signal. A second value of a second data element in a second set of data elements is obtained, the second set of data elements being based on a second, later time sample of the signal. A measure of similarity is derived between the first value and the second value. Based on the derived measure, a quantisation parameter useable in performing quantisation on data based on the first time sample of the signal is determined. Output data is generated using the quantisation parameter.