Patents by Inventor Ali Tasdighi

Ali Tasdighi has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • Patent number: 10915298
    Abstract: Methods of performing mixed-signal current-mode multiply-accumulate (MAC) operations for binarized neural networks in an integrated circuit are described in this disclosure. While digital machine learning circuits are fast, scalable, and programmable, they typically require bleeding-edge deep sub-micron manufacturing, consume high currents, and they reside in the cloud, which can exhibit long latency, and not meet private and safety requirements of some applications. Digital machine learning circuits also tend to be pricy given that machine learning digital chips typically require expensive tooling and wafer fabrication associated with advanced bleeding-edge deep sub-micron semiconductor manufacturing.
    Type: Grant
    Filed: July 31, 2020
    Date of Patent: February 9, 2021
    Inventor: Ali Tasdighi Far
  • Patent number: 10884705
    Abstract: Multipliers, Multiply-Accumulate (MAC), and Square-Accumulate (SAC) 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, MACs, and SACs. Generally, digital multipliers, MACs, and SACs can operate at high speed with high resolution, and synchronously. As the resolution and speed of digital multipliers, MACs, and SACs 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.
    Type: Grant
    Filed: February 26, 2020
    Date of Patent: January 5, 2021
    Inventor: Ali Tasdighi Far
  • Patent number: 10862501
    Abstract: 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.
    Type: Grant
    Filed: January 19, 2020
    Date of Patent: December 8, 2020
    Inventor: Ali Tasdighi Far
  • Patent number: 10862495
    Abstract: Single-stage and multiple-stage current-mode Analog-to-Digital converters (iADC)s utilizing apparatuses, circuits, and methods are described in this disclosure. The disclosed iADCs can operate asynchronously and be free from the digital clock noise, which also lowers dynamic power consumption, and reduces circuitry overhead associated with free running clocks. For their pseudo-flash operations, the disclosed iADCs do not require their input current signals to be replicated which saves area, lowers power consumption, and improves accuracy. Moreover, the disclosed methods of multi-staging of iADCs increase their resolutions while keeping current consumption and die size (cost) low. The iADC's asynchronous topology facilitates decoupling analog-computations from digital-computations, which helps reduce glitch, and facilitates gradual degradation (instead of an abrupt drop) of iADC's accuracy with increased input current signal frequency. The iADCs can be arranged with minimal digital circuitry (i.e.
    Type: Grant
    Filed: January 6, 2020
    Date of Patent: December 8, 2020
    Inventor: Ali Tasdighi Far
  • Patent number: 10848167
    Abstract: 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.
    Type: Grant
    Filed: January 19, 2020
    Date of Patent: November 24, 2020
    Inventor: Ali Tasdighi Far
  • Patent number: 10833692
    Abstract: Single-stage and multiple-stage current-mode Analog-to-Digital converters (iADC)s utilizing apparatuses, circuits, and methods are described in this disclosure. The disclosed iADCs can operate asynchronously and be free from the digital clock noise, which also lowers dynamic power consumption, and reduces circuitry overhead associated with free running clocks. For their pseudo-flash operations, the disclosed iADCs do not require their input current signals to be replicated which saves area, lowers power consumption, and improves accuracy. Moreover, the disclosed methods of multi-staging of iADCs increase their resolutions while keeping current consumption and die size (cost) low. The iADC's asynchronous topology facilitates decoupling analog-computations from digital-computations, which helps reduce glitch, and facilitates gradual degradation (instead of an abrupt drop) of iADC's accuracy with increased input current signal frequency. The iADCs can be arranged with minimal digital circuitry (i.e.
    Type: Grant
    Filed: January 6, 2020
    Date of Patent: November 10, 2020
    Inventor: Ali Tasdighi Far
  • Patent number: 10832014
    Abstract: Analog multipliers circuits can provide signal processing asynchronously and clock free and with low power consumptions, which can be advantageous, including in emerging mobile, portable, and at edge or near sensor artificial intelligence (AI) and machine learning (ML) applications. As such, analog multipliers can process signals memory-free in AI and ML applications, which avoids the power consumption and latency delays attributed to memory read-write cycles in conventional AI and ML digital processors. Based on standard digital Complementary-Metal-Oxide-Semiconductor (CMOS) manufacturing process, the present invention discloses embodiments of multi-quadrant current-mode analog multiplier (iMULT) circuits that can be utilized in current-mode multiply-accumulate (iMAC) circuits and artificial neural network (ANN) end-applications that require high-volumes, low costs, medium precision, low power consumptions, and clock free asynchronous signal processing.
    Type: Grant
    Filed: December 30, 2019
    Date of Patent: November 10, 2020
    Inventor: Ali Tasdighi Far
  • Patent number: 10826525
    Abstract: 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.
    Type: Grant
    Filed: January 19, 2020
    Date of Patent: November 3, 2020
    Inventor: Ali Tasdighi Far
  • Patent number: 10819283
    Abstract: Analog multipliers can perform signal processing with approximate precision asynchronously (clock free) and with low power consumptions, which can be advantageous including in emerging mobile and portable artificial intelligence (AI) and machine learning (ML) applications near or at the edge and or near sensors. Based on low cost, mainstream, and purely digital Complementary-Metal-Oxide-Semiconductor (CMOS) manufacturing process, the present invention discloses embodiments of current-mode analog multipliers that can be utilized in multiply-accumulate (MAC) signal processing in end-application that require low cost, low power consumption, (clock free) and asynchronous operations.
    Type: Grant
    Filed: December 30, 2019
    Date of Patent: October 27, 2020
    Inventor: Ali Tasdighi Far
  • Patent number: 10804921
    Abstract: A family of current mode analog to digital converters, or TiADC, utilizing methods, circuits, and apparatuses, are disclosed with the following benefits: (1) There are normal and random non-systematic mismatch between devices in silicon manufacturing, that introduce non-linearity in current mode analog to digital converter's, or iADC, reference network. The iADC's linearity is improved by utilizing a thermometer current mode signal conditioning method, SCM. Successive applications of the SCM effectuates a segmented current reference network to function like a thermometer network, which operates based on the function of summation. Having a TiADC with a thermometer reference network, where current segments are summed or accumulated incrementally, would inherently reduce the impact of statistical distribution of component's random mismatch on the iADC's non-linearity.
    Type: Grant
    Filed: December 31, 2019
    Date of Patent: October 13, 2020
    Inventor: Ali Tasdighi Far
  • Patent number: 10804925
    Abstract: 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.
    Type: Grant
    Filed: January 19, 2020
    Date of Patent: October 13, 2020
    Inventor: Ali Tasdighi Far
  • Patent number: 10797718
    Abstract: Single-stage and multiple-stage current-mode Analog-to-Digital converters (iADC)s utilizing apparatuses, circuits, and methods are described in this disclosure. The disclosed iADCs can operate asynchronously and be free from the digital clock noise, which also lowers dynamic power consumption, and reduces circuitry overhead associated with free running clocks. For their pseudo-flash operations, the disclosed iADCs do not require their input current signals to be replicated which saves area, lowers power consumption, and improves accuracy. Moreover, the disclosed methods of multi-staging of iADCs increase their resolutions while keeping current consumption and die size (cost) low. The iADC's asynchronous topology facilitates decoupling analog-computations from digital-computations, which helps reduce glitch, and facilitates gradual degradation (instead of an abrupt drop) of iADC's accuracy with increased input current signal frequency. The iADCs can be arranged with minimal digital circuitry (i.e.
    Type: Grant
    Filed: January 6, 2020
    Date of Patent: October 6, 2020
    Inventor: Ali Tasdighi Far
  • Patent number: 10789046
    Abstract: 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.
    Type: Grant
    Filed: January 19, 2020
    Date of Patent: September 29, 2020
    Inventor: Ali Tasdighi Far
  • Patent number: 10700695
    Abstract: 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.
    Type: Grant
    Filed: February 26, 2020
    Date of Patent: June 30, 2020
    Inventor: Ali Tasdighi Far
  • Patent number: 10594334
    Abstract: 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.
    Type: Grant
    Filed: April 11, 2019
    Date of Patent: March 17, 2020
    Inventor: Ali Tasdighi Far
  • Patent number: 10581448
    Abstract: A family of current mode analog to digital converters, or TiADC, utilizing methods, circuits, and apparatuses, are disclosed with the following benefits: (1) There are normal and random non-systematic mismatch between devices in silicon manufacturing, that introduce non-linearity in current mode analog to digital converter's, or iADC, reference network. The iADC's linearity is improved by utilizing a thermometer current mode signal conditioning method, SCM. Successive applications of the SCM effectuates a segmented current reference network to function like a thermometer network, which operates based on the function of summation. Having a TiADC with a thermometer reference network, where current segments are summed or accumulated incrementally, would inherently reduce the impact of statistical distribution of component's random mismatch on the iADC's non-linearity.
    Type: Grant
    Filed: February 3, 2019
    Date of Patent: March 3, 2020
    Inventor: Ali Tasdighi Far
  • Patent number: 10560058
    Abstract: Methods, circuits, and apparatuses that provide Buffer Amplifier, containing Amplifiers and Buffer Drivers, one or more of the following: ultra low power Buffer Amplifier, capable of having high gain, low noise, high speed, near rail-to-rail input-output voltage span, high sink-source current drive capability for an external load, and able to operate at low power supply voltages. Methods, circuits, and apparatuses that provide regulated cascode (RGC) current mirrors (CM) capable of operating at low power supply and having wide input-output voltage spans.
    Type: Grant
    Filed: October 27, 2018
    Date of Patent: February 11, 2020
    Inventor: Ali Tasdighi Far
  • Patent number: 10536117
    Abstract: Methods, circuits, and apparatuses that provide Buffer Amplifier, containing Amplifiers and Buffer Drivers, one or more of the following: ultra low power Buffer Amplifier, capable of having high gain, low noise, high speed, near rail-to-rail input-output voltage span, high sink-source current drive capability for an external load, and able to operate at low power supply voltages. Methods, circuits, and apparatuses that provide regulated cascode (RGC) current mirrors (CM) capable of operating at low power supply and having wide input-output voltage spans.
    Type: Grant
    Filed: October 26, 2018
    Date of Patent: January 14, 2020
    Inventor: Ali Tasdighi Far
  • Patent number: 10491167
    Abstract: Methods, circuits, and apparatuses are disclosed that provide a buffer amplifier with lower output noise by narrow banding the amplifier. To reinvigorate the speed of the narrow-banded amplifier, a boost-on signal is initiated. The boost-on signal dynamically and rapidly injects a substantial current into the amplifier's bias current network to speed up its slew rate, when the amplifier's inputs get unbalanced when being subjected to a large transient differential input signal. Subsequently, after the amplifier regulate itself and as the amplifier's inputs approach substantial balance, a boost-off signal dynamically injects a slow and decaying current (that converges to the level of static steady-state bias current) into amplifier's bias circuitry, instead of turning off the boost current rapidly, which improves the amplifier's settling time.
    Type: Grant
    Filed: August 22, 2018
    Date of Patent: November 26, 2019
    Inventor: Ali Tasdighi Far
  • Patent number: 10411597
    Abstract: A family of bandgap embodiments are disclosed herein, capable of operating with very low currents and low power supply voltages, using neither any custom devices nor any special manufacturing technology, and fabricated on mainstream standard digital CMOS processes. As such, manufacturing cost can be kept low, manufacturing yields of digital CMOS system-on-a-chip (SOC) that require a reference can be kept optimal, and manufacturing risk can be minimized due to its flexibility with respect to fabrication process node-portability. Although the embodiments disclosed herein use novel techniques to achieve accurate operations with low power and low voltage, this family of bandgaps also uses parasitic bipolar junction transistors (BJT) available in low cost digital CMOS process to generate proportional and complementary to absolute temperature (PTAT and CTAT) voltages via the base-emitter voltage (VEB) of BJTs and scaling VEB differential pairs to generate the BJTs thermal voltage (VT).
    Type: Grant
    Filed: September 29, 2017
    Date of Patent: September 10, 2019
    Inventor: Ali Tasdighi Far