Goodix Technology

Embodiments of the present application provide a signal processing method, circuit, and chip and an electronic device. The signal processing method includes: processing an input digital signal based on a PWM synchronization clock signal to obtain an analog differential signal; performing chopping processing on an intermediate common-mode voltage signal based on a chopping clock signal to obtain a common-mode voltage signal, where the intermediate common-mode voltage signal is used to stabilize a common-mode voltage of the analog differential signal, and an edge of a pulse included in the chopping clock signal is not aligned with an edge of a pulse included in the PWM synchronization clock signal in a time sequence; performing noise shaping and then PWM modulation on the analog differential signal to obtain a PWM signal; and performing voltage domain conversion on the PWM signal to obtain an output signal. This solution can improve signal processing performance.

Embodiments of the present disclosure provide a load driver, an audio amplifier, a chip, and an electronic device. The load driver comprises an output stage and a control module. The control module is connected to the output stage; and the control module is configured to control the output stage so that an output node of the output stage outputs a load drive signal, a rising edge of the load drive signal has a plurality of segments, and a rising slope of a previous segment among the plurality of segments of the rising edge is larger than a rising slope of a next segment. Based on the above solutions, the load driver provided in the embodiments of the present disclosure has a high switch-on speed, and satisfies EMI requirements.

A method for calibrating and/or verifying an implantable detecting device and an implantable detecting device are provided. The method includes: outputting a square wave signal to an implantable detecting device that has been implanted into a subject, where the implantable detecting device is configured to detect a concentration of an analyte in the subject, and a potential of the square wave signal increases incrementally over time; receiving a first current signal produced by the implantable detecting device in response to the square wave signal; generating a calibration curve based on a correspondence between the first current signal and the square wave signal; and performing calibration and/or functional verification on the implantable detecting device based on the calibration curve.

A method for processing a signal, a method for acquiring data, and an electronic device are provided. The method includes: processing, based on first parameter information stored in a parameter register, an analog signal obtained by sampling a to-be-measured signal to obtain a first digital signal; replacing, when receiving second parameter information sent by a second processing module, the first parameter information in the parameter register with the second parameter information; and processing the analog signal obtained by sampling the to-be-measured signal, based on the second parameter information stored in the parameter register to obtain a second digital signal, and setting a target identifier for a first digital signal of the second digital signal obtained through processing based on the second parameter information.

The example of the present application provides a physiological signal sensing method and apparatus, and an electronic device, where an apparatus part includes: one or more light emitters which are used for emitting first light; one or more photoelectric sensors which are used for detecting second light obtained through reflecting the first light via biological tissue and generating a corresponding first signal; a capacitive sensor which is used for detecting changes of a capacitor which is in contact with the biological tissue and generating a corresponding second signal; and a signal processing module which is used for carrying out motion artifact elimination on the first signal according to the second signal, so as to obtain a third signal. In some examples, the one or more photoelectric sensors are multiplexed as the capacitive sensor. Spatial correlation between the first signal and the second signal is higher, and then a better motion artifact elimination effect is achieved.

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Embodiments of the present application provide a fingerprint detection method and apparatus, a program product, and a storage medium. The method includes: obtaining native domain information of a to-be-detected fingerprint, where the native domain information is original data collected when the to-be-detected fingerprint is verified; executing fingerprint feature extraction on the native domain information to obtain a fingerprint feature matrix of the to-be-detected fingerprint; executing a classification operation on the fingerprint feature matrix through a trained medium classification network to obtain a fingerprint medium classification vector of the to-be-detected fingerprint, where the fingerprint medium classification vector is used for representing, in a vector form, a probability that the to-be-detected fingerprint belongs to a plurality of medium types respectively; and determining a medium type of the to-be-detected fingerprint based on the fingerprint medium classification vector. The present application solves the problem that the type of a fingerprint medium cannot be effectively detected in related technologies.

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The present disclosure relates to the technical field of signal processing, and discloses a method for recognizing fingerprint medium consistency, comprising: obtaining current to-be-verified fingerprint data; searching for target fingerprint template data matching the current to-be-verified fingerprint data in a registered fingerprint template dataset; searching for a target feature descriptor corresponding to the target fingerprint template data in a template feature descriptor set; and generating a verification feature descriptor using the pre-trained feature extraction network based on the current to-be-verified fingerprint data, and generating a current medium consistency probability of a verification fusion feature using a pre-trained feature fusion classification network based on the verification feature descriptor and the target feature descriptor. The present disclosure improves the accuracy of fingerprint classification and recognition.

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