Output Noise Research Articles

Narrow Linewidth Half-Open-Cavity Random Laser Assisted by a Three-Grating Ring Resonator for Strain Detection.

A stabilized narrow-linewidth random fiber laser for strain detection, based on a three-grating ring (TGR) resonator and half-open-cavity structure, is proposed and investigated experimentally. The half-open-cavity structure proved to provide double optical gain of erbium-doped fiber, which was beneficial to increase the photon lifetime as well as further narrow the linewidth. Meanwhile, the stability and frequency noise of narrow lasing output was improved by suppressing the competition-induced undesired residual random lasing modes with the TGR resonator. The TGR resonator is composed of a double-cavity fiber Bragg grating Fabry–Perot (FBG-FP) interferometer, a section of single-mode fiber, and a circulator. The specially designed double-cavity FBG-FP interferometer embedded in the TGR resonator acted as the strain-sensing element and improved the resolution of the dynamic strain. A stable ultra-narrow linewidth of about 205 Hz was obtained. The frequency noise was reduced to about 2 Hz/√Hz. A high dynamic strain measuring resolution of 35 femto-strain (fε)/√Hz was achieved.

A 3.95 ppm/°C 7.5 μW Second-Order Curvature Compensated Bandgap Reference in 0.11 μm CMOS

In order to meet the requirements of modern portable electronics for high accuracy and low power consumption of bandgap reference circuits, a new low-voltage bandgap reference with a second-order compensated circuit at 1.8 V is proposed. It features a new self-biased fully symmetric differential operational amplifier circuit with the help of split transistors for achieving low power consumption and high accuracy; by adding a new sub-threshold compensated circuit. The results of simulation show that the temperature coefficient of the second-order circuit is 3.95 ppm/°C in the temperature range of −40 to 125 °C, and the power consumption is only 7.5 μW; this meets both the requirements of high precision and low power consumption. At the same time, the output noise voltage of the design is less than 30 μV/sqrt (Hz) at a frequency of 100 Hz, and the low-frequency supply voltage rejection ratio is −103 dB@100 Hz; these are acceptable for bandgap reference circuits.

Quadstable logical stochastic resonance-based reconfigurable Boolean operation subjected to heavy noise floor

Logical stochastic resonance (LSR) is a paradigm to realize reconfigurable robust Boolean operations using specific nonlinearity in the presence of background noise. The stable-state number of the traditional LSR is less than four, which restricts its upper limit in the heavy noise floor. To further improve the noise robustness and output quality of LSR, we proposed quadstable nonlinearity based LSR system for the first time in this work. Using the parameters determined by the ant lion optimizer, we compare the performance of proposed quadstable LSR (QLSR) and traditional tristable LSR (TLSR) as reconfigurable logic gates in the heavy noise floor. The results show that in the heavy noise floor with noise intensity fluctuation, the maximum noise intensity that the QLSR can withstand is significantly higher than the that of TLSR. When the heavy noise floor contains pulses, the pulse robustness of QLSR and TLSR is comparable. Nevertheless, the quantitative indexes reveal that larger stable-state numbers endow the QLSR a stronger ability to extract noise energy for enhancing logic information; thus, the output quality of QLSR is better than that of TLSR.

Resilient Model Predictive Adaptive Control of Networked Z-Source Inverters Using GMDH

Power grids are increasingly evolving into more efficient smart grids thanks to advancements in information technology. However, these intelligent communication-dependant power systems are becoming more susceptible to cyberattacks than their traditional peers. Power inverters are one of the main network connected devices supporting grid stability, which can potentially be targets for cyber-threats. This article presents an attack-resilient model predictive adaptive controller for a class of inverters, called Z-source inverters, to protect them against deception attacks. The proposed control structure includes a model predictive controller equipped with an unknown input Kalman filter and an estimator for system perturbations. The group method of data handling technique is used to estimate system uncertainties and make the system robust against perturbations. The unknown input Kalman filter is also adopted to estimate the states and unknown inputs in the presence of noisy measurements and cyberattacks on the control signal. We mathematically prove that in the presence of noise and perturbations, the proposed controller guarantees the stability of the system under a deception attack, which causes a delay, less than a sampling time, in control signals. Simulation results reveal the effectiveness of the presented controller in protecting the system against pulse, scaling and random attacks in the presence of system uncertainties, source and load fluctuations and output noises.

Minimization of crosstalk noise and delay using reduced graphene nano ribbon (GNR) interconnect

In this paper, we proposed a side-contact reduced graphene nano-ribbon (SC-RGNR) interconnect model to reduce crosstalk noise and delay for next generation high performance integrated circuit (IC) design. The SC-RGNR interconnect structure is designed with latest 11 nm ITRS (International Technological Road Map for Semiconductor) technology node. A comparative crosstalk noise, delay and power consumption analysis has been performed with side-contact graphene nano-ribbon (SC-GNR) interconnect model. The SC-RGNR and SC-GNR interconnect both model parameters are applied in standard (STD) bus and staggered (STAGG) bus model with different interconnect lengths (10 μm–500 μm) and four standard mean free paths (MFP) (i.e., 300 nm, 419 nm, 1000 nm and 1200 nm) values. Five different switching conditions (i.e., SP1 to SP5) are applied on tri-interconnect driver-load circuit to check the performance of SC-RGNR and SC-GNR interconnect in-terms of crosstalk noise and delay. In our analysis, it is shown that, the higher MFP based SC-RGNR interconnect shows less dynamic delay compared with SC-GNR interconnect for both STD and STAGG interconnect model with worst-case switching condition (SP5) and best-case switching condition (SP2). For STD interconnect model with worst-case switching condition (SP5) the dynamic delay of SC-RGNR interconnect is ∼1.33–2.62 × lesser than SC-GNR interconnect. Similarly, for STAGG model with worst-case switching condition (SP5) the dynamic delay of SC-RGNR interconnect is ∼1.26–2.16 × lesser than SC-GNR interconnect. Although, the STAGG interconnect model performs ∼1.5–2 × faster than STD interconnect model in terms of delay. In our analysis, it is also observed that, the output noise peak is ∼2.91–17.5 × less in SC-RGNR compared with SC-GNR at 500 μm interconnect length and higher MFP. Our analysis also shows that, the switching power consumption in SC-RGNR is ∼1.66–2.2 × less than SC-GNR for both STD and STAGG model for both best and worst-case switching condition (SP2 and SP5).

Smartphone-Based and Data-Driven Superstructure State Prediction Method for Highway Bridges in Service.

Survival analysis is a data-driven approach that is widely used in various fields of biomedical prognostic research, and it is highly reliable in the processing of time-event data. This study developed a method for evaluating the service performance of bridge superstructures using the built-in acceleration sensor of smartphones and the prediction of survival analysis theory. It will be used to assist in the daily maintenance and repair of small and medium bridges. The effects of the upper load-bearing structure, upper general structure, bearings, deck paving, expansion joints, and frequency ratio on the deterioration of the bridge superstructure were investigated. The results show that the first-order vibration frequency of the bridge can be effectively detected by the built-in acceleration sensor of the mobile phone, but its low sensitivity and high output noise make it impossible to accurately detect the higher-order frequencies of the bridge. The upper load-bearing members, the upper general structure, the bearing, the deck pavement, and the frequency ratio are all related to the changing trend of the technical condition level of the bridge superstructure.

Investigation on Temperature Behavior for a GaAs E-pHEMT MMIC LNA.

In order to investigate the temperature behavior for monolithic microwave integrated circuits (MMICs) under alpine conditions, the performance parameters of a 0.4–3.8 GHz gallium arsenide (GaAs) enhancement pseudomorphic high-electron-mobility transistor (E-pHEMT) low-noise amplifier (LNA) are tested at different temperatures. The typical temperatures of −39.2 °C, −32.9 °C, −25.3 °C, −11.3 °C, −4.9 °C, 0 °C and 23 °C are chosen as the alpine condition. The major performance indexes including the direct current (DC) characteristics, S-parameters, stability, radio frequency (RF) output characteristics, output third-order intersection point (OIP3) and noise figure (NF), which were inspected and analyzed in detail. The results show that the DC characteristics, small-signal gain (S21), RF output characteristics and NF all deteriorate with the rising temperature due to the decrease in two-dimensional electron gas mobility (). Contrary to this trend, the special design makes stability and OIP3 increase. For further application of this MMIC LNA under alpine conditions, several measures can be utilized to remedy performance degradation. This paper can provide some significant engineering value for the reliable design of MMICs.

Improving Patient Comfort in MRI with Predictive Acoustic Noise Cancelling.

With sound pressure levels reaching up to 130 dB, acoustic noise in Magnetic Resonance Imaging (MRI) is one of the main sources of patient discomfort in otherwise one of the safest medical imaging modalities. In this work, a noise prediction-based approach, termed predictive noise cancelling (PNC), is applied, for the first time, to suppress noise in MRI. In PN C the noise from the scanner gradient coils is predicted based on linear time-invariant models, which relate the individual gradient coil (X, Y and Z) input to the acoustic noise output. A model setup was constructed of a custom speaker box and MRI -compatible microphone to demonstrate live noise reduction. Additional tuning steps, including output channel equalization and clock mismatch correction, were performed to maximize noise reduction. A calibration sequence was designed to determine the model and tuning parameters. Analysis of actual scanner noise shows an upper limit of 21 dB noise reduction with the proposed linear model. For the components of a clinical example sequence, the setup demonstrated in-bore live noise reduction of up to 10 dB (7.01 ± 0.31 dB, 6.42 ± 2.04 dB and 9.28 ± 0.26 dB for X, Y and Z gradient coils respectively) in the presence of system imperfections. Clinical relevance - The results indicate promising noise attenuation without the need to modify scanner hardware or compromises in acquisition speed or quality. This has potential to substantially and cost effectively improve patient comfort in clinical MRI.

Design of fractional-order NPID controller for the NPK model of advanced nuclear reactor

Advanced heavy water reactor (AHWR) is a type of advanced nuclear reactor which is the most efficient nuclear fission reactor for power generation due to the large thorium reserve. Its safe, stable, and efficient operations are critical for the revival of the fission energy sector. Incorporation of a robust control scheme into the nuclear reactor model is required for proper trajectory tracking of demand power. The AHWRs are coupled, significantly nonlinear, and multi-input multi-output (MIMO) systems. External disruptions and time-varying characteristics harm the systems' performance. As a result, the controller built for these systems must be able to deal with the complexity, which is most challenging for control engineers. A fractional-order nonlinear proportional, integral, and derivative (FONPID) control method is presented in this study for normalized power distribution management of the AHWR using normalized point kinetic equations (NPKEs) for trajectory tracking, disturbance rejection, and noise suppression tasks to improve the output power. All controller settings are fine-tuned using a genetic algorithm (GA) with the sum integral of time and square error (ITSE). The suggested FONPID controllers' performance is compared to its integer-order control structure, i.e., NPID and classical PID control structure. External disturbances at controller output and random noise at the sensor output are tested for resilience to establish the usefulness of the suggested control methods. The simulation results showcased that the proposed FONPID controller outperforms its integer-order (IO) counterpart as well as the traditional PID controller.

Numerical study of the effects of pulsed plasma actuator on physical behavior of the fluid flow around a ducted wind turbine

As with other types of wind turbines, the ducted wind turbine has a bright future. On the other hand, flow separation has a consistent effect on this type of turbine, resulting in aerodynamic losses and load fluctuations. As a result, flow control systems for ducted wind turbines are critical for improving aerodynamic performance. Additionally, in this technological age, noise pollution has developed into a serious problem that must be minimized and controlled to the greatest extent feasible. This research investigates the impact of a plasma actuator as an active control approach on the flow dynamics on the blades using a finite volume code. To decrease computing costs, the URANS model and mesh adaptive methods are applied. The numerical results are confirmed by comparing them to a previously collected experimental dataset. The flow dynamics and noise emission of a micro dielectric-barrier-discharge plasma actuator were examined under the impact of discontinuous pulsing. This actuator was fitted in three distinct places at the beginning point of separation in the blade without using the ducted wind turbine’s control approach. The results indicated that positioning the actuator near the blades’ tip improves aerodynamic performance. Additionally, when the plasma actuator’s power is raised, the vortex cancellation is maximized. The results indicated that the DBD actuator generated a considerable portion of reverse flow, in this case in the opposite direction to the tip flow. The reverse flow was used to alter the pressure gradient in the tip gap area, thereby eliminating the vortex. Also, using the plasma actuator reduces the ducted wind turbine’s noise output by cutting down on the wake zone and vortices, which are the main sources of noise.

Giant-Cavity-Based Quantum Sensors With Enhanced Performance

Recent progress has revealed that quantum systems with multiple position-dependent couplings, e.g., giant atoms, can exhibit some unconventional phenomena, such as non-exponential decay. However, their potential applications are still open questions. In this paper, we propose a giant-cavity-based quantum sensor for the first time, whose performance can be greatly enhanced compared to traditional cavity-based sensors. In our proposal, two cavities are coupled to a dissipative reservoir at multiple points while they couple to a gain reservoir in a single-point way. To detect an unknown parameter entering the sensor, a waveguide is coupled to one of the cavities where detecting fields can pass through for homodyne detection. We find that multiple position-dependent couplings can induce an inherent non-reciprocal coupling between the cavities, which can enhance the performance of sensors. Compared to the results in the work of Lau and Clerk, (Nat Commun, 2018, 9: 4,320), our output noise can remain at the shot noise level, which is about one order of magnitude lower. In addition, the signal-to-noise ratio per photon is also enhanced by about one order of magnitude. These results showed that the multiple-point coupling structure is beneficial to existing quantum devices.

Modification over Dithered DPLL to reduce the effect of narrowband channel interference

Digital signal processing based digital phase locked loop (DSP DPLL) are most commonly used for carrier phase tracking in the recent times. Phase locked loop (PLL) behaves in nonlinear fashion at the time of signal acquisition. The linearity is restored in the PLL behavior once acquisition is over and signal tracking is taking place. But the same PLL or DSP-DPLL shows non-linearity both during acquisition and tracking when narrowband channel interference is present in the received signal. In this paper, a single tone signal is introduced as channel interference to study the effect on DPLL and its modified versions. To overcome the effect of channel interference, a single tone dither signal is included in the loop of DPLL. Although an improvement in acquisition and tracking performance is observed, but addition of dither signal contributes to the phase error variance and consequently output noise to increase. Therefore, a further modification is proposed by incorporating an additional phase control in the digital control oscillator (DCO) of the loop to improve the output SNR. The proposed loop is implemented on reconfigurable logic platform using System Generator, a tool from Xilinx used to design real time DSP application. The hardware simulation results demonstrate a comparison among traditional DPLL, dithered DPLL and phase controlled dithered DPLL where the proposed version of the loop outperforms others in terms of acquisition and noise rejection. Keywords DSP Digital Phase Locked Loop, Phase Controlled DPLL, Channel Interference, Dither DPLL, VHDL System Design, Modified DCO

Ultra low phase noise and high output power monolithic microwave integrated circuit oscillator for 5G applications

novel structure of low phase noise and high output power monolithic microwave integrated circuit (MMIC) oscillator is presented in order to use it in 5G applications. The oscillator is based on the ED02AH process which allows us to design a microwave oscillator keeping a minimum size which is impossible to have it using other technologies since microwave oscillators are sensitive components above 20 GHz. The oscillator is studied, designed, and optimized on a GaAs substrate from the OMMIC foundry using the advanced design system (ADS) simulator in order to obtain a miniaturized oscillator (1.1×1.3 mm<sup>2</sup>) generating two signals of different frequencies f<sub>o1</sub>=26 GHz and f<sub>o2</sub>=30 GHz. The objective is to design an oscillator with high output power and low phase noise while respecting its specifications. The optimization of the proposed microwave oscillator shows satisfying results. Indeed, at 26 GHz and 30 GHz, the output powers are respectively 13.33 dBm and 14.89 dBm. The oscillator produces a sinusoidal signal of 1.5 V and 1.75 V amplitude respectively at 26 GHz and 30 GHz. The oscillator phase noise at f<sub>o1</sub> and f<sub>o2</sub> resonance frequencies using the liquid crystal (LC) resonator shows respectively -109 dBc/Hz and -110 dBc/Hz at 10 MHz offset.

Superconducting hot-electron bolometer mixers and their applications

Superconducting hot electron bolometer (HEB) mixers are the most sensitive heterodyne detectors at frequencies beyond 1 THz, and are used for many astronomical observations. HEB, consisting of a narrow and short superconducting thin film patch connected to an antenna via contact pads, is brought into a highly sensitive operating regime by applying a DC current and a certain amount of local-oscillator power. Potentially, superconducting HEB mixers are capable of exhibiting high sensitivity for frequencies up to several tens of THz, as their output noise and conversion gain are nearly frequency independent according to the mixing mechanism. Moreover, the understanding of mixing mechanism has evolved over time from lumped-element model to distributed hot-spot model. In this review, we provide an overview of theoretical and experimental studies on HEBs and their applications, especially in astronomical observations on ground, airborne and space telescopes.

Profit Sharing and Incentives

We model a firm as a team production process subject to moral hazard and derive the optimal profit sharing scheme between productive workers and outside investors together with incentive contracts based on noisy performance signals. More productive agents with noisier performance signals are more likely to receive shares which can explain why managers are motivated by shares, and law or consulting firms form partnerships. A firm that grows by opening branches is held almost entirely by outside investors when its output noise grows faster than the number of branches. Otherwise, insiders hold substantial amount of a large firm’s shares.

Design and characterization of third-order Sallen–Key digital filter in nuclear signal processing

The Gaussian filter shaping circuit is widely used in the nuclear pulse signal processing due to its good performance in amplitude extraction and pulse counting. A third-order Sallen–Key (3rd S–K) filter shaping circuit is designed based on a RC integrator and a second-order Sallen–Key (2nd S–K) circuit. According to the digital 3rd S–K, the transfer functions is derived in the Laplacian domain, and the numerical recurrence model is analyzed and researched, the purpose is to obtain its transfer function and amplitude–frequency response curve in the z-domain. For the simulation and actual sampling of the nuclear signal, digital shaping processing is performed at different parameters, three parameters (d, SNR, δ) are defined to compare and analyze the amplitude extraction, noise suppression and symmetry of the digital shaping method, which shows that as the shaping parameters increases, the digital shaping output noise suppression performance is better, the SNR increased from 49.25 to 64.21, the waveform is more symmetrical, the δ reduced from 34.05 to 0.22. At the same parameters, it is compared and analyzed with CR-RC3 and 2nd S–K shaping methods, according to the digital Gaussian shaping results, the 3rd S–K digital shaping method has better pulse amplitude extraction(d = 36.06%), noise suppression performance (SNR = 64.21) and waveform symmetry (δ = 0.22). Under different shaping methods, the energy resolution and pulse counting rate of the Fe characteristic X-ray energy spectrum are compared based on a Si-PIN detector. The results show that the 3rd S–K digital shaping method has better energy resolution performance and comprehensive performance indicators, which can be further applied for digital shaping of nuclear pulse signals.

On nonlinear robust state estimation for generalized Persidskii systems

A state observer is designed for a class of generalized Persidskii systems with nonlinear measurements, state disturbances, and output noise. We assume that all nonlinearities are diagonal and belong to a sector. The robust stability and convergence conditions for the estimation error are obtained by applying the theory of input-to-output stability. These conditions are established in the form of linear matrix inequalities. We provide numerical examples to demonstrate the efficacy and performances of the proposed observer.

A Stabilized Single-Longitudinal-Mode and Wide Wavelength Tunability Erbium Laser

An erbium-doped fiber (EDF) laser with quad-ring is designed to reach the broad continuous-wave (CW) tunability and single-longitudinal-mode (SLM) behavior. Here, while a C-band erbium-based gain medium is exploited, the tunable scope can be extended from C- to part of L-bands and narrow the linewidth to several kHz by the presented compound-ring configuration. Additionally, the optical signal to noise ratio (OSNR), output power, and stability behavior of every lasing wavelength are also demonstrated.

Parameter learning for the nonlinear system described by Hammerstein model with output disturbance

AbstractA novel parameter learning scheme using multi‐signal processing is developed that aims at estimating parameters of the Hammerstein nonlinear model with output disturbance in this paper. The Hammerstein nonlinear model consists of a static nonlinear block and a dynamic linear block, and the multi‐signals are devised to estimate separately the nonlinear block parameters and the linear block parameters; the parameter estimation procedure is greatly simplified. Firstly, in view of the input–output data of separable signals, the linear block parameters are computed through correlation analysis method, thereby the influence of output noise is effectively handled. In addition, model error probability density function technology is employed to estimate the nonlinear block parameters with the help of measurable input–output data of random signals, which not only controls the space state distribution of model error but also makes error distribution tends to normal distribution. The simulation results demonstrate that the developed approach obtains high learning accuracy and small modeling error, which verifies the effectiveness of the developed approach.

Prediction Error Identification for Closed Loop System with Errors-in-Variables

In order to study whether the predictive error method can also obtain satisfactory results in the closed-loop system with variable errors, the closed-loop situation is deduced by imitating the predictive error method in the open-loop system. The results show that the prediction error method can be used to identify the classical closed-loop system. When the input and output noise are all white noise with mean 0 and variance 1, the closed-loop system with errors-in-variables can be used to identify the prediction error.