Abstract: An embodiment of the present disclosure takes the form of a sensor device including a base structure with a plurality of ports extending into the base structure, a plurality of cells within the base structure and fluidly coupled to the plurality of ports, and an electrically conductive material disposed within the cells. The sensor device also includes a sensorized lattice structure disposed on the base structure and an electrically conductive layer disposed on top of the sensorized lattice structure.

Abstract: This disclosure relates to data converters for electronic systems. An example system includes a primary analog to digital converter (ADC) circuit, a slope calculation circuit, a digital phase lock loop (DPLL) circuit, a sampling error circuit, and a summing circuit. The primary ADC circuit samples an input signal and produces a digital output signal representative of the input signal. The slope calculation circuit generates a digital slope signal representative of slope of the input signal, and the DPLL circuit provides a sampling clock signal to the primary ADC circuit. The sampling error circuit generates a sampling error signal representative of sampling error by the primary ADC circuit using the digital slope signal and the sampling clock signal. The summing circuit receives the sampling error signal and the digital output signal of the primary ADC circuit and generates an adjusted digital output signal representative of the input signal.

Abstract: Systems and techniques are described for matching the resonance frequencies of multiple resonators. In some embodiments, a resonator generates an output signal reflecting the resonator's response to an input drive signal and an input noise signal. The output signal is then compared to the noise signal to derive a signal representative of the resonance frequency of the resonator. Comparing that signal to the output signal of a second resonator gives an indication of whether there is a difference between the resonance frequencies of the two resonators. If there is, one or both of the resonators may be adjusted. In this manner, the resonance frequencies of resonators may be matched during normal operation of the resonators.

Abstract: This disclosure relates to data converters for electronic systems. An example system includes a primary analog to digital converter (ADC) circuit, a slope calculation circuit, a digital phase lock loop (DPLL) circuit, a sampling error circuit, and a summing circuit. The primary ADC circuit samples an input signal and produces a digital output signal representative of the input signal. The slope calculation circuit generates a digital slope signal representative of slope of the input signal, and the DPLL circuit provides a sampling clock signal to the primary ADC circuit. The sampling error circuit generates a sampling error signal representative of sampling error by the primary ADC circuit using the digital slope signal and the sampling clock signal. The summing circuit receives the sampling error signal and the digital output signal of the primary ADC circuit and generates an adjusted digital output signal representative of the input signal.

Abstract: Systems and techniques are described for matching the resonance frequencies of multiple resonators. In some embodiments, a resonator generates an output signal reflecting the resonator's response to an input drive signal and an input noise signal. The output signal is then compared to the noise signal to derive a signal representative of the resonance frequency of the resonator. Comparing that signal to the output signal of a second resonator gives an indication of whether there is a difference between the resonance frequencies of the two resonators. If there is, one or both of the resonators may be adjusted. In this manner, the resonance frequencies of resonators may be matched during normal operation of the resonators.

Abstract: For continuous-time multi-stage noise shaping analog to digital converters (CT MASH ADCs), quantization noise cancellation often requires estimation of transfer functions, e.g., a noise transfer function of the front end modulator. To estimate the noise transfer function, a dither signal can be injected in the front end modulator. However, it is not trivial how the dither signal can be injected, since the dither signal can potentially leak to the back end modulator and cause overall noise degradation. To address some of these issues, the dither signal is injected post the flash analog to digital converter (ADC) of the front end modulator. Furthermore, dummy comparator structures can be used to synchronize the dither with the quantization noise of the targeted flash ADC.

Abstract: For continuous-time multi-stage noise shaping analog-to-digital converters (CT MASH ADCs), quantization noise cancellation often requires accurate estimation of transfer functions, e.g., a noise transfer function of the front end modulator and a signal transfer function of the back end modulator. To provide quantization noise cancellation, digital quantization noise cancellation filters adaptively tracks transfer function variations due to integrator gain errors, flash-to-DAC timing errors, as well as the inter-stage gain and timing errors. Tracking the transfer functions is performed through the direct cross-correlation between the injected maximum length linear feedback shift registers (LFSR) sequence and modulator outputs and then corrects these non-ideal effects by accurately modeling the transfer functions with programmable finite impulse response (PFIR) filters.

Abstract: Typically, complex systems require a separate and expensive equalizer at the output of an analog-to-digital converter (ADC). Rather than providing a separate equalizer, the effective Signal Transfer Function (STF) of a Multi-stAge noise SHaping (MASH) ADC can be modified by leveraging available digital filtering hardware necessary for quantization noise cancellation. The modification can involves adding calculations in the software previously provided for computing digital quantization noise cancellation filter coefficients, where the calculations are added to take into account equalization as well. As a result, the signal transfer function can be modified to meet ADC or system-level signal-chain specifications without additional equalization hardware. The method is especially attractive for high-speed applications where magnitude and phase responses are more challenging to meet.

Abstract: For analog-to-digital converters (ADCs) which utilize a feedback digital-to-analog converter (DAC) for conversion, the final analog output can be affected or distorted by errors of the feedback DAC. A digital measurement technique can be implemented to determine timing mismatch error for the feedback DAC in a continuous-time delta-sigma modulator (CTDSM) or in a continuous-time pipeline modulator. The methodology utilizes cross-correlation of each DAC unit elements (UEs) output to the entire modulator output to measure its timing mismatch error respectively. Specifically, the timing mismatch error is estimated using a ratio based on a peak value and a value for the next tap in the cross-correlation function. The obtained errors can be stored in a look-up table and fully corrected in digital domain or analog domain.

Abstract: For continuous-time multi-stage noise shaping analog to digital converters (CT MASH ADCs), quantization noise cancellation often requires estimation of transfer functions, e.g., a noise transfer function of the front end modulator. To estimate the noise transfer function, a dither signal can be injected in the front end modulator. However, it is not trivial how the dither signal can be injected, since the dither signal can potentially leak to the back end modulator and cause overall noise degradation. To address some of these issues, the dither signal is injected post the flash analog to digital converter (ADC) of the front end modulator. Furthermore, dummy comparator structures can be used to synchronize the dither with the quantization noise of the targeted flash ADC.

Abstract: For continuous-time multi-stage noise shaping analog-to-digital converters (CT MASH ADCs), quantization noise cancellation often requires accurate estimation of transfer functions, e.g., a noise transfer function of the front end modulator and a signal transfer function of the back end modulator. To provide quantization noise cancellation, digital quantization noise cancellation filters adaptively tracks transfer function variations due to integrator gain errors, flash-to-DAC timing errors, as well as the inter-stage gain and timing errors. Tracking the transfer functions is performed through the direct cross-correlation between the injected maximum length linear feedback shift registers (LFSR) sequence and modulator outputs and then corrects these non-ideal effects by accurately modeling the transfer functions with programmable finite impulse response (PFIR) filters.

Abstract: For analog-to-digital converters (ADCs) which utilize a feedback digital-to-analog converter (DAC) for conversion, the final analog output can be affected or distorted by errors of the feedback DAC. A digital measurement technique can be implemented to determine timing mismatch error for the feedback DAC in a continuous-time delta-sigma modulator (CTDSM) or in a continuous-time pipeline modulator. The methodology utilizes cross-correlation of each DAC unit elements (UEs) output to the entire modulator output to measure its timing mismatch error respectively. Specifically, the timing mismatch error is estimated using a ratio based on a peak value and a value for the next tap in the cross-correlation function. The obtained errors can be stored in a look-up table and fully corrected in digital domain or analog domain.

Abstract: Typically, complex systems require a separate and expensive equalizer at the output of an analog-to-digital converter (ADC). Rather than providing a separate equalizer, the effective Signal Transfer Function (STF) of a Multi-stAge noise SHaping (MASH) ADC can be modified by leveraging available digital filtering hardware necessary for quantization noise cancellation. The modification can involves adding calculations in the software previously provided for computing digital quantization noise cancellation filter coefficients, where the calculations are added to take into account equalization as well. As a result, the signal transfer function can be modified to meet ADC or system-level signal-chain specifications without additional equalization hardware. The method is especially attractive for high-speed applications where magnitude and phase responses are more challenging to meet.

Abstract: The present disclosure describes a mechanism to digitally correct for the static mismatch of the digital-to-analog converter (DAC) in at least the first-stage of a multi-stage noise shaping (MASH) analog-to-digital converter (ADC). The correction is applicable to continuous-time implementations, and is especially attractive for high-speed applications.

Abstract: Digital-to-analog converters (DACs) are used widely in electronics. The DACs are usually not ideal and typically exhibits errors, e.g., static mismatch errors. This disclosure describes a digital calibration technique for DAC static mismatch in continuous-time delta-sigma modulators (CTDSMs). The methodology utilizes the DAC unit elements (UEs) themselves to measure each other's mismatch. There are no extra circuitries except for the logic design inside DAC drivers or comparators. The methodology is an attractive calibration technique for high performance CTDSMs, especially for high speed system in multi-gigahertz range with low over-sampling rate (OSR).

Abstract: The present disclosure describes a mechanism to digitally correct for the static mismatch of the digital-to-analog converter (DAC) in at least the first-stage of a multi-stage noise shaping (MASH) analog-to-digital converter (ADC). The correction is applicable to continuous-time implementations, and is especially attractive for high-speed applications.

Abstract: Digital-to-analog converters (DACs) are used widely in electronics. The DACs are usually not ideal and typically exhibits errors, e.g., static mismatch errors. This disclosure describes a digital calibration technique for DAC static mismatch in continuous-time delta-sigma modulators (CTDSMs). The methodology utilizes the DAC unit elements (UEs) themselves to measure each other's mismatch. There are no extra circuitries except for the logic design inside DAC drivers or comparators. The methodology is an attractive calibration technique for high performance CTDSMs, especially for high speed system in multi-gigahertz range with low over-sampling rate (OSR).

Abstract: An automatic gain control circuit includes an input gain stage for receiving and amplifying an analog input signal; an analog-to-digital converter for receiving the amplified analog input signal and providing a digital output signal; and an overload management module. The overload management module is arranged to receive the digital output signal; determine therefrom whether the received, amplified analog input signal exceeds an operating range of the analog-to-digital converter; and provide a first control signal to the input gain stage to adjust a gain of the input gain stage in response thereto.

Abstract: An automatic gain control circuit includes an input gain stage for receiving and amplifying an analog input signal; an analog-to-digital converter for receiving the amplified analog input signal and providing a digital output signal; and an overload management module. The overload management module is arranged to receive the digital output signal; determine therefrom whether the received, amplified analog input signal exceeds an operating range of the analog-to-digital converter; and provide a first control signal to the input gain stage to adjust a gain of the input gain stage in response thereto.

Abstract: A circuit for calibrating selective coefficients of a delta-sigma modulator is provided. The circuit includes a calibration logic module that is coupled to one of a plurality of stages of the delta-sigma modulator. The calibration logic module measures the oscillating frequency of a respective stage and compares it to a reference frequency. The calibration logic adjusts a selective circuit component associated with the respective stage so that the reference frequency and the oscillating frequency match.