Provided is an analog to digital converter configured to receive a continuous input signal. The analog to digital converter includes an integrating block, comprising at least an integrating stage, which output is coupled to a flash analog to digital converter. The analog to digital converter apparatus includes a feedback path coupled to the output of said flash analog to digital converter. The feedback path includes at least a digital to analog conversion block which output is compared at least to the input signal to obtain an error signal which is brought as input to said integrating block. A control block is configured to perform control comprising at least a digital integration, is coupled between the output of said flash analog to digital converter and said feedback path.

An embodiment electronic circuit includes an electronic switch comprising a load path, a first protection circuit configured to generate a first protection signal based on a current-time-characteristic of a load current through the load path of the electronic switch, and a drive circuit configured to drive the electronic switch based on the first protection signal. The first protection circuit includes a logarithmic analog-to-digital converter (ADC) configured to receive an ADC input signal representing the load current and to output an ADC output signal that includes a sequence of values such that each of the values represents a respective sample of the ADC input signal, a filter configured to filter the ADC output signal and output a filter output signal, and a comparator circuit configured to generate the first protection signal based on comparing the filter output signal with a predefined threshold.

A non-linearity correction circuit includes a non-linearity coefficient estimation circuit. The non-linearity coefficient estimation circuit includes a data capture circuit, a non-linearity term generation circuit, a time-to-frequency conversion circuit, a bin identification circuit, a residual non-linearity conversion circuit, and a non-linearity coefficient generation circuit. The non-linearity term generation circuit is coupled to the data capture circuit. The time-to-frequency conversion circuit is coupled to the data capture circuit and the non-linearity term generation circuit. The bin identification circuit is coupled to the time-to-frequency conversion circuit. The residual non-linearity conversion circuit is coupled to the bin identification circuit. The non-linearity coefficient generation circuit is coupled to the bin identification circuit and the residual non-linearity conversion circuit.

Multipliers and Multiply-Accumulate (MAC) circuits are fundamental building blocks in signal processing, including in emerging applications such as machine learning (ML) and artificial intelligence (AI) that predominantly utilize digital-mode multipliers and MACs. Generally, digital multipliers and MACs can operate at high speed with high resolution, and synchronously. As the resolution and speed of digital multipliers and MACs increase, generally the dynamic power consumption and chip size of digital implementations increases substantially that makes them impractical for some ML and AI segments, including in portable, mobile, near edge, or near sensor applications. The multipliers and MACs utilizing the disclosed current mode data-converters are manufacturable in main-stream digital CMOS process, and they can have medium to high resolutions, capable of low power consumptions, having low sensitivity to power supply and temperature variations, as well as operating asynchronously, which makes them suitable for high-volume, low cost, and low power ML and AI applications.

A non-linearity correction circuit includes a non-linearity coefficient estimation circuit. The non-linearity coefficient estimation circuit includes a data capture circuit, a non-linearity term generation circuit, a time-to-frequency conversion circuit, a bin identification circuit, a residual non-linearity conversion circuit, and a non-linearity coefficient generation circuit. The non-linearity term generation circuit is coupled to the data capture circuit. The time-to-frequency conversion circuit is coupled to the data capture circuit and the non-linearity term generation circuit. The bin identification circuit is coupled to the time-to-frequency conversion circuit. The residual non-linearity conversion circuit is coupled to the bin identification circuit. The non-linearity coefficient generation circuit is coupled to the bin identification circuit and the residual non-linearity conversion circuit.

Transit-time based ultrasonic flow meter with analog-to-digital conversion for measuring ultrasonic signals, wherein accuracy of measurements is improved by making several measurements with different input offset, reference voltage, frame offset or sample rate in an analog-to-digital conversion stage.

Multipliers and Multiply-Accumulate (MAC) circuits are fundamental building blocks in signal processing, including in emerging applications such as machine learning (ML) and artificial intelligence (AI) that predominantly utilize digital-mode multipliers and MACs. Generally, digital multipliers and MACs can operate at high speed with high resolution, and synchronously. As the resolution and speed of digital multipliers and MACs increase, generally the dynamic power consumption and chip size of digital implementations increases substantially that makes them impractical for some ML and AI segments, including in portable, mobile, near edge, or near sensor applications. The multipliers and MACs utilizing the disclosed current mode data-converters are manufacturable in main-stream digital CMOS process, and they can have medium to high resolutions, capable of low power consumptions, having low sensitivity to power supply and temperature variations, as well as operating asynchronously, which makes them suitable for high-volume, low cost, and low power ML and AI applications.

In accordance with an embodiment, a method of monitoring a data converter includes determining a multiplicity of time-associated linearity parameters that describe a linearity of the data converter at a multiplicity of different times, and determining a state of the data converter based on comparing at least one linearity parameter of the multiplicity of time-associated linearity parameters with a comparison parameter.

Transit-time based ultrasonic flow meter with analog-to-digital conversion for measuring ultrasonic signals, wherein accuracy of measurements is improved by making several measurements with different input offset, reference voltage, frame offset or sample rate in an analog-to-digital conversion stage.

Multipliers are fundamental building blocks in signal processing, including in emerging applications such as machine learning (ML) and artificial intelligence (AI) that predominantly utilize digital-mode multipliers. Generally, digital multipliers can operate at high speed with high precision, and synchronously. As the precision and speed of digital multipliers increase, generally the dynamic power consumption and chip size of digital implementations increases substantially that makes solutions unsuitable for some ML and AI segments, including in portable, mobile, or near edge and near sensor applications. The present invention discloses embodiments of multipliers that arrange data-converters to perform the multiplication function, operating in mixed-mode (both digital and analog), and capable of low power consumptions and asynchronous operations, which makes them suitable for low power ML and AI applications.