A5022312302- Analog and Mixed-Signal Circuit Design
- Neuroscience and Neural Engineering
- Ferroelectric and Negative Capacitance Devices
- Advanced Memory and Neural Computing
- Magnetic Bearings and Levitation Dynamics
- Electric Motor Design and Analysis
- Sensorless Control of Electric Motors
- Low-power high-performance VLSI design
- Electrostatic Discharge in Electronics
- Neural dynamics and brain function
- Network Packet Processing and Optimization
- Photoreceptor and optogenetics research
- Analytical Chemistry and Sensors
- Advancements in Semiconductor Devices and Circuit Design
- CCD and CMOS Imaging Sensors
Zhejiang Lab
2021-2023
Nanjing University of Aeronautics and Astronautics
2021
Xidian University
2018-2020
In this work, we present a four-transistor-two-resistor (4T2R) ternary content addressable memory (TCAM) bit cell based on the resistive (RRAM), comprising conventional two-transistor-two-resistor (2T2R) with two additional comparison transistors. It can effectively amplify match-line signal ratio (ML-ratio), lower leakage current of match (<inline-formula> <tex-math notation="LaTeX">${I}_{{\mathrm {MATCH}}}$ </tex-math></inline-formula>), and suppress read disturbance. The proposed concept...
Neuromorphic computing based on spike neural networks (SNNs) exhibits great potential in reducing energy consumption hardware systems. Resistive random-access memory (ReRAM) is regarded as a promising candidate to construct neuromorphic hardware, attributing their high-density, nonvolatile, and compute-in-memory capability. However, the ReRAM-based chips are still infancy, cannot support multicore or with limited neuron configurability. To alleviate these problems, we propose hybrid SNN chip...
This brief presents a CMOS analog frontend (AFE) IC with high input impedance low input-referred noise, which for wearable electrocardiogram monitoring. The has three main parts, pseudo-differential chopper-stabilized instrumentation amplifier, switched capacitor filter, and low-power continuous–time <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${{\Sigma}} {{\Delta }}$ </tex-math></inline-formula>...
This paper presents a 10-bit ultra-low power least-significant bit first (LSB-first) successive approximation register analog-to-digital converter used in wearable electrocardiogram monitoring. Compared with the exsiting ones, number of bitcycles taken proposed LSB-first scheme only relates to difference between two adjacent samples and capacitor array is reduced by 50%. Fabricated 65 nm CMOS technology within bio-sensor front-end circuit, SAR ADC occupies an active area 200 × 450 μm2,...
The paper presents two high energy-efficiency switching schemes for the successive approximation register (SAR) analogue-to-digital converter (ADC). first scheme is a part of second one. new achieves no energy consumption in three comparison, and need reset energy. Thus, compared with conventional SAR architecture, 99.23 99.42% reduction achieved respectively. Moreover, total an 86.7% unit capacitor number by its special architecture.
For the traditional high frequency (HF) injection methods of bearingless motors, HF signal is always injected into armature winding, resulting in large suspension and torque ripples. In order to solve this problem, a general theory combinations auxiliary coils presented paper. This aims eliminate certain harmonics based on vector superposition basic excitation vector, can be employed for motors all pole pairs with concentrated windings. It has advantage less influence control. implemented...
Flux-switching permanent magnet (FSPM) machines can provide high torque density, strong flux-weakening capability, and reliability, which makes these attractive in electrical drive systems. FSPM always employ different control methods, such as the vector (VC) direct (DTC)methods. These methods exhibit electromagnetic dynamic performances; hence, performances oftheir rotor speeds aredifferent. However, PI controllers of speed loopin methodsare linear regulators, hardly guarantee optimal...
With the rapid growth of data in Internet Things (IoT), more biologically realistic and computationally efficient spiking neural networks (SNNs) have been applied to energy-efficient intelligent edge devices. Accelerators with in-situ learning function can adapt dynamically changing environment by adjusting network parameters. However, current neuromorphic digital computing systems usually rely on expensive SRAM for weight storage complicated circuit, which constrains their deployment...
资助项目摘要 柔性电极非常适用于生物电信号的采集, 而对生物电信号这类低活跃度的输入信号进行量化 时, 可以采用末位优先量化算法以节省 ADC 能量消耗.本文提出了一种新型的用于 SAR-ADC 的末 位优先量化算法, 在继承了传统末位优先量化算法的优点上