Invensense, Inc.

Hcl Technologies Italy S.p.a

Alessandro Magnani

Stefano Valle

Igor Mucha

Nicola Vannucci

Pascal Trotta

Disclosed embodiments provide flexible performance, high dynamic range, microelectromechanical (MEMS) multipath digital microphones, which allow seamless, low latency transitions between audio signal paths without audible artifacts over interruptions in the audio output signal. Disclosed embodiments facilitate performance and power saving mode transitions maintaining high dynamic range capability.

Microphone with flexible performance

Disclosed embodiments provide glitch prediction based on machine learning algorithms in mixed analog and digital systems, particularly directed to digital microelectromechanical (MEMS) multipath acoustic sensors or microphones, which allow seamless, low latency gain changes without audible artifacts or interruptions in the audio output signal.

Machine learning glitch prediction

The present disclosure relates to system(s) and method(s) for real time compression of a data frame. The system receives the data frame comprising a set of symbols. Further, the system identifies frequency of each symbol, from the set of symbols. The system further sorts the symbols in descending order of frequency, associated with each symbols. Further, the system computes a compression gain associated with each predefined case type, a set of predefined case types. Furthermore, the system selects a target predefined case type, based on the comparison of the compression gain of each predefined case types. The system further assigns a compressed code to Most Frequent Symbols (MFS), in the data frame. The compressed code is assigned based on the target predefined case type. Further, the system generates a compressed frame, associated with the data frame. The compressed frame comprises a header and a sequence of compressed symbols.

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Milan, Italy

Alessandro Magnani