Low Noise Density Research Articles

Soft Fibrous Syringe Architecture for Electricity-Free and Motorless Control of Flexible Robotic Systems.

Flexible robotic systems (FRSs) and wearable user interfaces (WUIs) have been widely used in medical fields, offering lower infection risk and shorter recovery, and supporting amiable human-machine interactions (HMIs). Recently, soft electric, thermal, magnetic, and fluidic actuators with enhanced safety and compliance have innovatively boosted the use of FRSs and WUIs across many sectors. Among them, soft hydraulic actuators offer great speed, low noise, and high force density. However, they currently require bulky electric motors/pumps, pistons, valves, rigid accessories, and complex controllers, which inherently result in high cost, low adaptation, and complex setups. This paper introduces a novel soft fibrous syringe architecture (SFSA) consisting of two or more hydraulically connected soft artificial muscles that enable electricity-free actuation, motorless control, and built-in sensing ability for use in FRSs and WUIs. Its capabilities are experimentally demonstrated with various robotic applications including teleoperated flexible catheters, cable-driven continuum robotic arms, and WUIs. In addition, its sensing abilities to detect passive and active touch, surface texture, and object stiffness are also proven. These excellent results demonstrate a high feasibility of using a current-free and motor-less control approach for the FRSs and WUIs, enabling new methods of sensing and actuation across the robotic field.

Traveling fronts in vibrated polar disks: At the crossroad between polar ordering and jamming.

We investigate experimentally the collective motion of polar vibrated disks in an annular geometry, varying both the packing fraction and the amplitude of the angular noise. For low enough noise and large enough density, an overall collective motion takes place along the tangential direction. The spatial organization of the flow reveals the presence of polar bands of large density, as expected from the commonly accepted picture of the transition to collective motion in systems of aligning polar active particles. However, in our case, the low density phase is also polar, consistent with what is observed when jamming takes place in a very high density flock. Interestingly, while in that case the particles in the high density bands are arrested, resulting in an upstream propagation at a constant speed, in our case the bands travel downstream with a density-dependent speed. We demonstrate from local measurements of the packing fraction, alignment, and flow speeds that the bands observed here result both from a polar ordering process and a motility induced phase separation mechanism.

Polymeric piezoelectric accelerometers with high sensitivity, broad bandwidth, and low noise density for organic electronics and wearable microsystems

Piezoelectric accelerometers excel in vibration sensing. In the emerging trend of fully organic electronic microsystems, polymeric piezoelectric accelerometers can be used as vital front-end components to capture dynamic signals, such as vocal vibrations in wearable speaking assistants for those with speaking difficulties. However, high-performance polymeric piezoelectric accelerometers suitable for such applications are rare. Piezoelectric organic compounds such as PVDF have inferior properties to their inorganic counterparts such as PZT. Consequently, most existing polymeric piezoelectric accelerometers have very unbalanced performance metrics. They often sacrifice resonance frequency and bandwidth for a flat-band sensitivity comparable to those of PZT-based accelerometers, leading to increased noise density and limited application potentials. In this study, a new polymeric piezoelectric accelerometer design to overcome the material limitations of PVDF is introduced. This new design aims to simultaneously achieve high sensitivity, broad bandwidth, and low noise. Five samples were manufactured and characterized, demonstrating an average sensitivity of 29.45 pC/g within a ± 10 g input range, a 5% flat band of 160 Hz, and an in-band noise density of 1.4 µg/Hz\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\sqrt{{Hz}}$$\\end{document}. These results surpass those of many PZT-based piezoelectric accelerometers, showing the feasibility of achieving comprehensively high performance in polymeric piezoelectric accelerometers to increase their potential in novel applications such as organic microsystems.

A polymeric piezoelectric MEMS accelerometer with high sensitivity, low noise density, and an innovative manufacturing approach

The piezoelectric coupling principle is widely used (along with capacitive coupling and piezoresistive coupling) for MEMS accelerometers. Piezoelectric MEMS accelerometers are used primarily for vibration monitoring. Polymer piezoelectric MEMS accelerometers offer the merits of heavy-metal-free structure material and simple microfabrication flow. More importantly, polymeric piezoelectric MEMS accelerometers may be the basis of novel applications, such as fully organic inertial sensing microsystems using polymer sensors and organic integrated circuits. This paper presents a novel polymer piezoelectric MEMS accelerometer design using PVDF films. A simple and rapid microfabrication flow based on laser micromachining of thin films and 3D stereolithography was developed to fabricate three samples of this design. During proof-of-concept experiments, the design achieved a sensitivity of 21.82 pC/g (equivalent open-circuit voltage sensitivity: 126.32 mV/g), a 5% flat band of 58.5 Hz, and a noise density of 6.02 µg/√Hz. Thus, this design rivals state-of-the-art PZT-based counterparts in charge sensitivity and noise density, and it surpasses the performance capabilities of several commercial MEMS accelerometers. Moreover, this design has a 10-times smaller device area and a 4-times larger flat band than previous state-of-the-art organic piezoelectric MEMS accelerometers. These experimentally validated performance metrics demonstrate the promising application potential of the polymeric piezoelectric MEMS accelerometer design presented in this article.

Transient response improvement of half‐bridge LLC resonant converter with full‐bridge rectifier for DC microgrid

AbstractLLC resonant converter has the features of low noise, high efficiency and power density, which is suitable to be integrated into DC microgrid. Due to severe stresses in the resonant tank, achieving fast and safe transient performance has been challenging for resonant converters. With less switch number and voltage stress, half‐bridge LLC resonant converter with full‐bridge rectifier (H‐F LLC resonant converter) are more suitable for high‐voltage application. To improve the transient response of the converter, this paper proposes a method based fixed center state trajectory for the converter to achieve soft start‐up. To reduce dynamic response time during start‐up, each step of fixed center state‐trajectory is designed optimally for the shortest path with symmetrical current limitation. In addition, the proposed method is also applicable to full‐bridge LLC converters. Moreover, according to the state‐plane analysis, load stepping‐up and stepping‐down transient state trajectories with the shortest path are carried out as well. To minimize the adverse effect of digital delay, fast load transient control based on 3D look‐up table is given based on FPGA‐EP3C25E144I7, which would also significantly reduce the computation requirement of the hardware controllers. The experimental results are verified on a 380V/12V LLC converter prototype at 130 kHz.

Study and implementation of fluxgate current sensor with wireless connectivity for finger exoskeleton rehabilitation

SummaryA fully integrated fluxgate magnetometer has been developed to monitor motor current in a finger exoskeleton device. The use of a fluxgate sensor can provide more accurate and natural movement of the fingers, as well as reducing the weight and complexity of the exoskeleton design. The sensor we developed incorporates several advanced features that provide enhanced sensitivity and accuracy compared to existing state‐of‐the‐art sensors. These features include a fluxgate frontend readout circuit with chopping stabilization technology, which achieves a gain of 14.3 V/T, a low noise density of 4.5 nT/√Hz, and a wide measurement range of ±1.5 mT. The gain variation of the sensor is only 1.5% at an 850 kHz bandwidth, and it has a wide dynamic current range from 0.005 mA to 100 A. The sensor also features an integrated 2.4 GHz wireless circuit for easy data transmission. The use of a fluxgate sensor in monitoring motor torque in the proximal interphalangeal joint can provide more precise and natural finger movement and reduce the weight and complexity of the exoskeleton design.

Noise-robustness test for ultrasound breast nodule neural network models as medical devices.

Deep learning technology has been widely applied to medical image analysis. But due to the limitations of its own imaging principle, ultrasound image has the disadvantages of low resolution and high Speckle Noise density, which not only hinder the diagnosis of patients' conditions but also affect the extraction of ultrasound image features by computer technology. In this study, we investigate the robustness of deep convolutional neural network (CNN) for classification, segmentation, and target detection of breast ultrasound image through random Salt & Pepper Noise and Gaussian Noise. We trained and validated 9 CNN architectures in 8617 breast ultrasound images, but tested the models with noisy test set. Then, we trained and validated 9 CNN architectures with different levels of noise in these breast ultrasound images, and tested the models with noisy test set. Diseases of each breast ultrasound image in our dataset were annotated and voted by three sonographers based on their malignancy suspiciousness. we use evaluation indexes to evaluate the robustness of the neural network algorithm respectively. There is a moderate to high impact (The accuracy of the model decreased by about 5%-40%) on model accuracy when Salt and Pepper Noise, Speckle Noise, or Gaussian Noise is introduced to the images respectively. Consequently, DenseNet, UNet++ and Yolov5 were selected as the most robust model based on the selected index. When any two of these three kinds of noise are introduced into the image at the same time, the accuracy of the model will be greatly affected. Our experimental results reveal new insights: The variation trend of accuracy with the noise level in Each network used for classification tasks and object detection tasks has some unique characteristics. This finding provides us with a method to reveal the black-box architecture of computer-aided diagnosis (CAD) systems. On the other hand, the purpose of this study is to explore the impact of adding noise directly to the image on the performance of neural networks, which is different from the existing articles on robustness in the field of medical image processing. Consequently, it provides a new way to evaluate the robustness of CAD systems in the future.

Bi-directional gated recurrent unit recurrent neural networks for failure prognosis of proton exchange membrane fuel cells

With zero pollution, low noise and high power density, proton exchange membrane fuel cells (PEMFC) are widely used in automobiles, ships, mobile power and other applications. However, the lifetime of the PEMFC is constrained by degradation. In this paper, a bi-directional gated recursive unit (Bi-GRU) recurrent neural network is proposed for power reactor failure prediction in both dynamic and static cases. In performing degradation prediction, the hyperparameters of the model are adjusted after the selection of variables to obtain the combination of hyperparameters that gives the best results. The proposed model was compared with gated recursive units (GRU), superimposed gated recursive units (St-GRU) and existing studies for better performance. It has better performance compared to other models when one model is used to predict both dynamic and static datasets. And it's very suitable for fault prediction with very high accuracy and the relative error in remaining life prediction is about 0.029%–0.12%.

Identifying the physical mechanisms of polycrystalline lead salt photoconductors

Polycrystalline infrared lead salt detectors exhibit exceptionally high sensitivity near room temperature and, as such, are ubiquitous in commercial instruments such as spectrometers and flame detectors. The underlying physical mechanism behind this remarkable performance has been the subject of speculation for many years. In this treatise, data from work performed at BAE Systems and St. John's Optical Systems and from the published literature are analyzed to identify common mechanisms that contribute to the photoconductivity of polycrystalline lead salt detectors from a multitude of material deposition and process technologies, and it was concluded that much of the behavior can be attributed to surface-related phenomenon. Physical models are proposed to explain the observations. Finally, there is a brief description of measurements related to noise in these complex structures, indicating the importance of ohmic contacts, but the observed low frequency spectral noise density remains a mystery.

Energy Management Strategy of Fuel-Cell Backup Power Supply Systems Based on Whale Optimization Fuzzy Control

A backup power supply system can provide electrical energy for load in harsh environment without power grid, and plays a very important role in natural disaster rescue and military application. Compared with traditional energy sources, the proton-exchange membrane fuel cell has the advantages of good low temperature start-up performance, low noise, high efficiency and high power density, and no carbon emission, which gradually becomes the main energy source of the backup power supply system. This paper designs the backup power system topology of the “dual fuel cell and lithium battery” and researches energy management strategy based on fuzzy control (FC). Considering that it is difficult for the fuzzy controller to obtain the optimal membership function parameters according to working conditions, this paper aims to reduce the hydrogen consumption of the system, uses the whale optimization algorithm to optimize the membership function of the fuzzy controller, and proposes an energy management strategy based on whale optimization fuzzy control (WO-FC). The energy management strategies are verified and compared by simulations. The results show that the membership function of the optimized fuzzy controller based on WO-FC energy management strategy has changed greatly: The hydrogen consumption of the system obviously decreased compared with no optimization, and the overall efficiency of the fuel cell also significantly improved. To be more precise, the energy management strategy based on WO-FC reduces the hydrogen consumption of the system by 5.35% and improves the overall efficiency of the fuel cell by 1.56%.

A strip line technique based 1 Gb/s, 70-dB linear dynamic range transimpedance amplifier towards LiDAR unmanned vehicle application

1This work reports a Microstrip Line (MSL) based Dual-Gate MOSFET (DGMOSFET) Transimpedance amplifier (TIA) for LIDAR unmanned vehicle application under different weather conditions. TIA (Design-I) is proposed under normal weather, while TIA (Design-II) for foggy weather conditions. TIA (Design-I) employs a variable gain common gate topology with post-amplification, resulting in high gain, wide bandwidth, and high dynamic range (DR). TIA (Design-II) incorporates a series MSL section at the input of TIA (Design-I), which further enhances the bandwidth performance. TIA (Design-I) realizes a fractional bandwidth of 104.3% with a transimpedance gain of 100.4 dBΩ and low input-referred noise (IRN) density of 4.29 pA/√Hz. TIA (Design-II) achieves a fractional bandwidth of 178.4% with transimpedance gain, IRN, and DR of 100.42 dBΩ, 3.81 pA/√Hz, and 70 dB, respectively. TIA (Design-II) demonstrates a 1 Gb/s data rate with a bit-error-rate < 10−10. The TIA (Design-I) and TIA (Design-II) consume the power of 33 mW and 39 mW under the supply voltage of 2 V.

Active Magnetoelectric Motion Sensing: Examining Performance Metrics with an Experimental Setup.

Magnetoelectric (ME) sensors with a form factor of a few millimeters offer a comparatively low magnetic noise density of a few / in a narrow frequency band near the first bending mode. While a high resonance frequency (kHz range) and limited bandwidth present a challenge to biomagnetic measurements, they can potentially be exploited in indirect sensing of non-magnetic quantities, where artificial magnetic sources are applicable. In this paper, we present the novel concept of an active magnetic motion sensing system optimized for ME sensors. Based on the signal chain, we investigated and quantified key drivers of the signal-to-noise ratio (SNR), which is closely related to sensor noise and bandwidth. These considerations were demonstrated by corresponding measurements in a simplified one-dimensional motion setup. Accordingly, we introduced a customized filter structure that enables a flexible bandwidth selection as well as a frequency-based separation of multiple artificial sources. Both design goals target the prospective application of ME sensors in medical movement analysis, where a multitude of distributed sensors and sources might be applied.

High CMRR Voltage Mode Instrumentation Amplifier Using a New CMOS Differential Difference Current Conveyor Realization

This paper describes a new CMOS realization of differential difference current conveyor circuit. The proposed design offers enhanced characteristics compared to DDCC circuits previously exhibited in the literature. It is characterized by a wide dynamic range with good accuracy thanks to use of adaptive biasing circuit instead of a constant bias current source as well as a wide bandwidth (560 MHz) and a low parasitic resistance at terminal X about 6.86 Ω. A voltage mode instrumentation amplifier circuit (VMIA) composed of a DDCC circuit and two active grounded resistances is shown as application. The proposed VMIA circuit is intended for high frequency applications. This configuration offers significant improvement in accuracy as compared to the state of the art. It is characterized by a controllable gain, a large dynamic range with THD less than 0.27 %, a low noise density (22 nV/Hz1/2) with a power consumption about 0.492 mW and a wide bandwidth nearly 83 MHz. All proposed circuits are simulated by TSPICE using CMOS 0.18 μm TSMC technology with ± 0.8 V supply voltage to verify the theoretical results.

A piezoelectric AlN MEMS hydrophone with high sensitivity and low noise density

This paper presents a micromachined hydrophone with high sensitivity and low noise density. The hydrophone is composed of a 10by10 piezoelectric aluminum nitride (AlN) membrane array, a low noise amplification circuit, and packaged by an acoustic transparent material. Equivalent noise model is used to analyze the equivalent input noise of receiving system, which can be effective to reducing the noise floor by choosing appropriate components. Moreover, a new pouring method is applied to improve the acoustic performance of the matching layer. The experiment results show that the packaged MEMS hydrophone achieves an acoustic sensitivity of -178 dB (Ref. 1 V/μPa), a bandwidth from 100 Hz to 1600 Hz, and an equivalent noise density of 52.6 dB@100 Hz (Ref. μPa/√Hz). The enhanced hydrophone is beneficial to achieve weak signals detecting in pipeline leak detection, marine noise monitoring and many other low frequency engineering applications.

Silence is sexy: soundscape complexity alters mate choice in túngara frogs

Abstract Many animals acoustically communicate in large aggregations, producing biotic soundscapes. In turn, these natural soundscapes can influence the efficacy of animal communication, yet little is known about how variation in soundscape interferes with animals that communicate acoustically. We quantified this variation by analyzing natural soundscapes with the mid-frequency cover index and by measuring the frequency ranges and call rates of the most common acoustically communicating species. We then tested female mate choice in the túngara frog (Physalaemus pustulosus) in varying types of background chorus noise. We broadcast two natural túngara frog calls as a stimulus and altered the densities (duty cycles) of natural calls from conspecifics and heterospecifics to form the different types of chorus noise. During both conspecific and heterospecific chorus noise treatments, females demonstrated similar preferences for advertisement calls at low and mid noise densities but failed to express a preference in the presence of high noise density. Our data also suggest that nights with high densities of chorus noise from conspecifics and heterospecifics are common in some breeding ponds, and on nights with high noise density, the soundscape plays an important role diminishing the accuracy of female decision-making.

Sub-1-V BGR and POR Hybrid Circuit With 2.25-μA Current Dissipation and Low Complexity

Based on three groups of different offset voltages, a bandgap reference (BGR) and power-ON reset (POR) hybrid circuit is implemented in 65-nm CMOS. The BGR using amplifier offset voltage and current matching, and the POR using offset voltage comparison and loop settling feature, respectively, are proposed. This circuit, with low-quiescent current, not only generates a stable reference voltage independent of voltage and temperature variations, but also provides a high-robust supply-ramp-rate-tolerant power-ON/brown-out reset signal with a hysteretic window of 18–24 mV. Experimental results show that the circuit with line regulations (LNRs) of 2.63%–4.28%/V and temperature coefficients (TCs) of 22–32 ppm/°C across multiple chips has a power dissipation around $2.25~\mu \text{W}$ from a 1-V supply voltage. The circuit achieves a low noise density of 18.5 nV/ $\surd $ Hz at 100-Hz offset frequency and a good figure of merit (FoM) performance. With an active core area of 0.014 mm2, the circuit has fixed reset trip voltages under the supply ramp time of 0.4–100 ms.

A novel median based image impulse noise suppression system using spiking neurons on FPGA

ABSTRACT The most common impulse noise suppression methods are based on the median filter. They are suitable for low noise densities, but employing a separate noise detection step makes them suitable for higher noise rates. Instead, this may degrade the performance for lower noise. Particularly, the adaptive median noise removal algorithm improves the results for both low and high noise corruption rates. This paper presents a novel noise detection and filtering algorithm that uses leaky integrate and fire spiking neurons which model natural computing of the brain. In the proposed method, at each process of the detection and the filtering, all pixels of an adaptive sliding window are fed to the spiking neurons performing the operations in parallel. As a result, higher processing speed and higher operating frequency are achieved. An FPGA is used to implement the algorithm due to its real-time application and reconfigurable structure. The proposed architecture represents a slight increase in the PSNR values, whereas it consumes less hardware resources compared to the previous works. The design is implemented on Cyclone IV device from Altera family. It includes 3231 LUTs and the maximum operating frequency of 187 MHz is achieved.

A 0.6-µW Chopper Amplifier Using a Noise-Efficient DC Servo Loop and Squeezed-Inverter Stage for Power-Efficient Biopotential Sensing.

To realize an ultra-low-power and low-noise instrumentation amplifier (IA) for neural and biopotential signal sensing, we investigate two design techniques. The first technique uses a noise-efficient DC servo loop (DSL), which has been shown to be a high noise contributor. The proposed approach offers several advantages: (i) both the electrode offset and the input offset are rejected, (ii) a large capacitor is not needed in the DSL, (iii) by removing the charge dividing effect, the input-referred noise (IRN) is reduced, (iv) the noise from the DSL is further reduced by the gain of the first stage and by the transconductance ratio, and (v) the proposed DSL allows interfacing with a squeezed-inverter (SQI) stage. The proposed technique reduces the noise from the DSL to 12.5% of the overall noise. The second technique is to optimize noise performance using an SQI stage. Because the SQI stage is biased at a saturation limit of 2VDSAT, the bias current can be increased to reduce noise while maintaining low power consumption. The challenge of handling the mismatch in the SQI stage is addressed using a shared common-mode feedback (CMFB) loop, which achieves a common-mode rejection ratio (CMRR) of 105 dB. Using the proposed technique, a capacitively-coupled chopper instrumentation amplifier (CCIA) was fabricated using a 0.18-µm CMOS process. The measured result of the CCIA shows a relatively low noise density of 88 nV/rtHz and an integrated noise of 1.5 µVrms. These results correspond to a favorable noise efficiency factor (NEF) of 5.9 and a power efficiency factor (PEF) of 11.4.

Probabilistic Decision Based Average Trimmed Filter for the Removal of High-Density Salt and Pepper Noise

The paper focuses on the evacuation of salt and pepper noise from a contaminated image. A probabilistic decision based average trimmed filter (PDBATF) is proposed for both high and low noise density. The proposed algorithm addresses the issue related to even number of noise-free pixel in trimmed median filter for the calculation of processing pixel. The proposed average trimmed filter is incorporated for low noise density while the proposed patch else average trimmed filter is applied for high noise density. Finally, they are combined together to develop the proposed PDBATF. The proposed algorithm show an excellent noise removal capability compared to the recently developed algorithms in terms of peak signal to noise ratio, image enhancement factor, mean absolute error and execution time. It works very efficiently in de-noising contaminated medical images such as chest-x-ray and malaria-blood-smear.

Low frequency noise and trap density in GaN/AlGaN field effect transistors

We report experimental results on the low-frequency noise in GaN/AlGaN transistors fabricated under different conditions and evaluate different methods to extract the effective trap density using the McWhorter model. The effective trap density is found to be below 1019 cm−3 for some of the wafers. This trap density is of the same order of magnitude as that reported in Si MOSFETs with a high-k dielectric. One of the structures manifested about two orders of magnitude higher noise level. These measurements correlate with the results of secondary ion mass spectroscopy and terahertz electroluminescence measurements which indicated a ∼30% higher concentration of uncompensated oxygen in this structure. Effective trap density extracted from noise measurements is proven to be a very sensitive figure of merit parameter for the GaN/AlGaN field effect transistors and material quality assessment.