Circuit Response Research Articles

Physics-based compact modeling of electro-thermal memristors: Negative differential resistance, local activity, and non-local dynamical bifurcations

Leon Chua's Local Activity theory quantitatively relates the compact model of an isolated nonlinear circuit element, such as a memristor, to its potential for desired dynamical behaviors when externally coupled to passive elements in a circuit. However, the theory's use has often been limited to potentially unphysical toy models and analyses of small-signal linear circuits containing pseudo-elements (resistors, capacitors, and inductors), which provide little insight into required physical, material, and device properties. Furthermore, the Local Activity concept relies on a local analysis and must be complemented by examining dynamical behavior far away from the steady-states of a circuit. In this work, we review and study a class of generic and extended one-dimensional electro-thermal memristors (i.e., temperature is the sole state variable), re-framing the analysis in terms of physically motivated definitions and visualizations to derive intuitive compact models and simulate their dynamical behavior in terms of experimentally measurable properties, such as electrical and thermal conductance and capacitance and their derivatives with respect to voltage and temperature. Within this unified framework, we connect steady-state phenomena, such as negative differential resistance, and dynamical behaviors, such as instability, oscillations, and bifurcations, through a set of dimensionless nonlinearity parameters. In particular, we reveal that the reactance associated with electro-thermal memristors is the result of a phase shift between oscillating current and voltage induced by the dynamical delay and coupling between the electrical and thermal variables. We thus, demonstrate both the utility and limitations of local analyses to understand non-local dynamical behavior. Critically for future experimentation, the analyses show that external coupling of a memristor to impedances within modern sourcing and measurement instruments can dominate the response of the total circuit, making it impossible to characterize the response of an uncoupled circuit element for which a compact model is desired. However, these effects can be minimized by proper understanding of the Local Activity theory to design and utilize purpose-built instruments.

Noise analysis of electrical circuits on fractal set

PurposeThe purpose of this study is to originally present noise analysis of electrical circuits defined on fractal set.Design/methodology/approachThe fractal integrodifferential equations of resistor-inductor, resistor-capacitor, inductor-capacitor and resistor-inductor-capacitor circuits subjected to zero mean additive white Gaussian noise defined on fractal set have been formulated. The fractal time component has also been considered. The closed form expressions for crucial stochastic parameters of circuit responses have been derived from these equations. Numerical simulations of power spectral densities based on the derived autocorrelation functions have been performed. A comparison with those without fractal time component has been made.FindingsWe have found that the Hausdorff dimension of the middle b Cantor set strongly affects the power spectral densities; thus, the average powers of noise induced circuit responses and the inclusion of fractal time component causes significantly different analysis results besides the physical measurability of electrical quantities.Originality/valueFor the first time, the noise analysis of electrical circuit on fractal set has been performed. This is also the very first time that the fractal time component has been included in the fractal calculus-based circuit analysis.

Identification of an endocannabinoid gut-brain vagal mechanism controlling food reward and energy homeostasis.

The regulation of food intake, a sine qua non requirement for survival, thoroughly shapes feeding and energy balance by integrating both homeostatic and hedonic values of food. Unfortunately, the widespread access to palatable food has led to the development of feeding habits that are independent from metabolic needs. Among these, binge eating (BE) is characterized by uncontrolled voracious eating. While reward deficit seems to be a major contributor of BE, the physiological and molecular underpinnings of BE establishment remain elusive. Here, we combined a physiologically relevant BE mouse model with multiscale in vivo approaches to explore the functional connection between the gut-brain axis and the reward and homeostatic brain structures. Our results show that BE elicits compensatory adaptations requiring the gut-to-brain axis which, through the vagus nerve, relies on the permissive actions of peripheral endocannabinoids (eCBs) signaling. Selective inhibition of peripheral CB1 receptors resulted in a vagus-dependent increased hypothalamic activity, modified metabolic efficiency, and dampened activity of mesolimbic dopamine circuit, altogether leading to the suppression of palatable eating. We provide compelling evidence for a yet unappreciated physiological integrative mechanism by which variations of peripheral eCBs control the activity of the vagus nerve, thereby in turn gating the additive responses of both homeostatic and hedonic brain circuits which govern homeostatic and reward-driven feeding. In conclusion, we reveal that vagus-mediated eCBs/CB1R functions represent an interesting and innovative target to modulate energy balance and counteract food-reward disorders.

Correlation between Transient Response and Neuromorphic Behavior in Organic Electrochemical Transistors

AbstractThe factors controlling the neuromorphic response of organic electrochemical transistors (OECTs) are examined. In these devices, the gate voltage is used to supply the pre‐synaptic input, while the drain current is taken as the post‐synaptic output. The behavior of devices made from polymer blends of a mixed conductor (PEDOT:PSS) and an ion conductor (PSSNa) is analyzed. The experimental results highlight that the post‐synaptic response timescale depends on the size of ion in the electrolyte. Modeling shows that the neuromorphic response is controlled by the transient response of the ionic circuit of the OECT. These insights on device response time pave the way for a more rational design of OECT‐based neuromorphic devices.

Failure Region Estimation of Linear Voltage Regulator using Model-based Virtual Sensing and Non-invasive Stability Measurement

Voltage regulator (VR) stability plays an essential role in ensuring maximum power delivery and long-lasting electronic lifespan. Capacitor with a specific equivalent series resistance (ESR) range is typically connected at the VR output terminal to compensate for instability of the VR due to sudden changes in load current. The stability of VR can be measured by analyzing output voltage during load transient tests. However, the optimum ESR range obtained from the ESR tunnel graph in its datasheet can only be characterized by testing a set of data points consisting of ESR and load currents. Characterization process is performed manually by changing the value of ESR and load current for each operating point. However, the inefficient process of estimating the critical value of ESR must be improved given that it requires a large amount of time and expertise. Furthermore, the stability analysis is currently conducted on the basis of the number of oscillation counts of VR output voltage signal. Therefore, a model-based virtual sensing approach that mainly focuses on black-box modeling through system identification method and training neural network on the basis of estimated transfer function coefficients is introduced in this study. The proposed approach is used to estimate the internal model of the VR and reduce the number of data points that need to be acquired. In addition, the VR stability is analyzed using noninvasive stability measurement method, which can measure phase margin from the frequency response of the VR circuit in closed-loop conditions. Results showed that the proposed method reduces the time it takes to produce an ESR tunnel graph by 84% with reasonable accuracy (MSE of 5×10−6, RMSE of 2.24×10−3, MAE of 1×10−3, and R2 of 0.99). Therefore, efficiency and effectiveness of ESR characterization and stability analysis of the VR circuit is improved.

A Circuit Principle and Simulation Test for Negative Group Delay

Abstract Group velocity superluminal phenomenon, also known as negative group delay or negative group velocity phenomenon, refers to a group of envelope signal at the output end of the medium before the input, in the time axis, is to leave the medium envelope appears before entering the medium, but this does not violate causality. Based on the waveguide theory of negative group delay, this paper uses the transfer function, amplitude response and phase shift response of the electronic circuit to control group velocity, and introduces three first-order bandpass amplifier RC circuits to control group velocity in low frequency band, which realize positive group delay, negative group delay and filtering functions respectively. Finally, the phenomenon of negative group delay is preliminarily realized by using circuit simulation software, which lays a foundation for subsequent research. As an envelope that can carry and transmit information, the study of negative group velocity is of great significance to the improvement of signal transmission efficiency.

Output Characteristics of Side-Illuminated Photoconductive Semiconductor Switch Based on High Purity Semi-Insulating 4H-SiC

Photoconductive semiconductor switch (PCSS) allowing side illumination was fabricated on high purity semi-insulating (HPSI) 4H-SiC. A 532-nm pulsed laser with variable optical energy was used to trigger the PCSS. The performance of the PCSS was characterized under the two different load conditions, 50-Ω load and 0.05-Ω, with a current viewing resistor (CVR). The PCSS exhibited significantly different output characteristics for the two different loads. The equivalent resistance of the PCSS with the 50-Ω load, which was calculated from the output voltage and current, was inversely proportional to the optical energy, but the one with a 0.05-Ω load exhibited saturation behavior with the optical energy. While the times at peak output with the 50-Ω load were similar at various optical energies, the times at peak output with the 0.05-Ω load were dependent on the optical energy. Output current oscillation was also observed after the PCSS was turned off in the case of 0.05-Ω load condition. The different output characteristics for the different load resistances were analyzed using the transient response of the equivalent circuits. The PCSS exhibited a minimum on-state resistance of 0.27 Ω with the optical energy of 8 mJ and a maximum output current of 657 A at the bias voltage of 4.8 kV. The operating voltage of the PCSS was limited by surface flashover, which caused an additional output pulse following the first output pulse.

COMPLEX HYBRID SYMBOLIC ANALYSIS OF NONLINEAR ANALOG CIRCUITS DRIVEN BY MULTI-TONE SIGNALS

The paper presents a general symbolic method for generating the complex hybrid matrix necessary for computing the periodic or nonperiodic steady-state response of a nonlinear analog circuit driven by multitone signals. This method is remarkable by its great efficiency and generality, and it is very useful in frequency-domain approach based on harmonic balance and least square approximation. For the general case of the nonperiodic steady-state response there are three basic methods: frequency-domain approach based on Voltera series; time-domain approach and a frequency-domain approach based on harmonic balance and least square approximation. The last one is significantly more efficient when the total number of nonlinear resistors, inductors and capacitors is significantly less than the total number of linear inductors and capacitors in the circuit, as is often the case in practice.

МОДЕЛІ АЧХ І ФЧХ ДВОТАКТНИХ ПІДСИЛЮВАЧІВ ПОСТІЙНОГО СТРУМУ

A universal approach for the general analysis of frequency response and frequency response of analog circuits is considered, taking into account the fundamental relationships between the parameters of transistors without reference to a specific element base, which will reliably assess the characteristics taking into account the required number of amplifier stages.

Analytical Expressions of Time-Domain Responses of Protection Circuits to ISO Reverse Transients in Automotive Applications

As the use of semiconductors and electronic control units (ECU) in automobiles has increased, electromagnetic susceptibility has become more essential for the reliability of ECUs. Consequently, automotive ECUs are subjected to electromagnetic compatibility tests to control quality. Test pulses for electromagnetic immunity testing in the automotive industry, such as reverse transients 1 and 3a, defined in the International Organization for Standardization (ISO) 7637–2 standard document, are examined. In practice, it is necessary to analytically investigate the performance of the protection circuits against these reverse pulses. In this paper, theoretical expressions of the time-domain responses of the capacitor filter to these reverse pulses are derived. In addition, the expressions of the avalanche energy as well as the time during avalanche mode are presented. The analytical results, validated by LTspice simulation, show that for the case of pulse 1, the reversal battery-polarity protection device after the filter, i.e., a low-voltage power metal-oxide-semiconductor field-effect transistor (MOSFET), is safe despite entering the avalanche breakdown mode. In the case of pulse 3a, the filter can almost completely remove the transient voltage and hence avoid the avalanche effect of the MOSFET. The verified expressions when the suppressed voltage reaches its maximum are very helpful for hardware design engineers to quickly determine whether the MOSFET undergoes avalanche breakdown.

Temporal signaling, population control, and information processing through chromatin-mediated gene regulation

Chromatin regulation is a key pathway cells use to regulate gene expression in response to temporal stimuli, and is becoming widely used as a platform for synthetic biology applications. Here, we build a mathematical framework for analyzing the response of genetic circuits containing chromatin regulators to temporal signals in mammalian cell populations. Chromatin regulators can silence genes in an all-or-none fashion at the single-cell level, with individual cells stochastically transitioning between active, reversibly silent, and irreversibly silent gene states at constant rates over time. We integrate this mode of regulation with classical gene regulatory motifs, such as autoregulatory and incoherent feedforward loops, to determine the types of responses achievable with duration-dependent signaling. We demonstrate that repressive regulators without long-term epigenetic memory can filter out high frequency noise, and as part of an autoregulatory loop can precisely tune the fraction of cells in a population that expresses a gene of interest. Additionally, we find that repressive regulators with epigenetic memory can sum up and encode the total duration of their recruitment in the fraction of cells irreversibly silenced and, when included in a feed forward loop, enable perfect adaptation. Last, we use an information theoretic approach to show that all-or-none stochastic silencing can be used by populations to transmit information reliably and with high fidelity even in very simple genetic circuits. Altogether, we show that chromatin-mediated gene control enables a repertoire of complex cell population responses to temporal signals and can transmit higher information levels than previously measured in gene regulation.

Development of an MRI-Compatible Nasal Drug Delivery Method for Probing Nicotine Addiction Dynamics.

Substance abuse is a fundamentally dynamic disease, characterized by repeated oscillation between craving, drug self-administration, reward, and satiety. To model nicotine addiction as a control system, a magnetic resonance imaging (MRI)-compatible nicotine delivery system is needed to elicit cyclical cravings. Using a concentric nebulizer, inserted into one nostril, we delivered each dose equivalent to a single cigarette puff by a syringe pump. A control mechanism permits dual modes: one delivers puffs on a fixed interval programmed by researchers; with the other, subjects press a button to self-administer each nicotine dose. We tested the viability of this delivery method for studying the brain’s response to nicotine addiction in three steps. First, we established the pharmacokinetics of nicotine delivery, using a dosing scheme designed to gradually achieve saturation. Second, we lengthened the time between microdoses to elicit craving cycles, using both fixed-interval and subject-driven behavior. Finally, we demonstrate a potential application of our device by showing that a fixed-interval protocol can reliably identify neuromodulatory targets for pharmacotherapy or brain stimulation. Our MRI-compatible nasal delivery method enables the measurement of neural circuit responses to drug doses on a single-subject level, allowing the development of data-driven predictive models to quantify individual dysregulations of the reward control circuit causing addiction.

Using entropy-driven amplifier circuit response to build nonlinear model under the influence of L\xe9vy jump

BackgroundBioinformatics is a subject produced by the combination of life science and computer science. It mainly uses computer technology to study the laws of biological systems. The design and realization of DNA circuit reaction is one of the important contents of bioinformatics.ResultsIn this paper, nonlinear dynamic system model with Lévy jump based on entropy-driven amplifier (EDA) circuit response is studied. Firstly, nonlinear biochemical reaction system model is established based on EDA circuit response. Considering the influence of disturbance factors on the system, nonlinear biochemical reaction system with Lévy jump is built. Secondly, in order to prove that the constructed system conforms to the actual meaning, the existence and uniqueness of the system solution is analyzed. Next, the sufficient conditions for the end and continuation of EDA circuit reaction are certified. Finally, the correctness of the theoretical results is proved by numerical simulation, and the reactivity of THTSignal in EDA circuit under different noise intensity is verified.ConclusionsIn EDA circuit reaction, the intensity of external noise has a significant impact on the system. The end of EDA circuit reaction is closely related to the intensity of Lévy noise, and Lévy jump has a significant impact on the nature of biochemical reaction system.

Optimization Schemes for In-Memory Linear Regression Circuit With Memristor Arrays

Recently, an in-memory analog circuit based on crosspoint memristor arrays was reported, which enables solving linear regression problems in one step and can be used to train many other machine learning algorithms. To explore its potential for computing accelerator applications, it is of fundamental importance to improve the computing speed of the circuit, <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">i.e.</i> , the circuit response towards correct outputs. In this work, we comprehensively studied the transfer function of this circuit, resulting in a quadratic eigenvalue problem that describes the distribution of poles. The minimal real part of non-zero eigenvalues defines the dominant pole, which in turn dominates the response time. Simulations for multiple linear regression solutions with different datasets evidence that, the computing time does not necessarily increase with problem size. The dominant pole is related to parameters in the circuit, including feedback conductance, and gain bandwidth products of operational amplifiers. By optimizing these parameters synergistically, the dominant pole shifts to higher frequencies and the computing speed is consequently optimized. Our results provide a guideline for design and optimization of in-memory machine learning accelerators with analog memristor arrays. Also, issues including power consumption, impact of noise and variation of sources and memristors are investigated to offer a comprehensive evaluation of the circuit performance.

An Improved Analytical Model of a Spectrometer for Optical Coherence Tomography

We present an improved analytical model of a spectrometer for optical coherence tomography (OCT), which more accurately describes the OCT in-depth sensitivity fall-off. The model considers the intrinsic spectral resolution of the dispersive element and the influence of additional components (inequidistance-correcting prism). The model is validated by experimental data obtained both from other studies and our own experiments. The influence of the frequency response of the CCD electrical circuit and the analog-to-digital converter to the OCT signal fall-off was also detected and was shown to be significant in some cases.

Intelligent Fault Detection and Identification Approach for Analog Electronic Circuits Based on Fuzzy Logic Classifier

Analog electronic circuits play an essential role in many industrial applications and control systems. The traditional way of diagnosing failures in such circuits can be an inaccurate and time-consuming process; therefore, it can affect the industrial outcome negatively. In this paper, an intelligent fault diagnosis and identification approach for analog electronic circuits is proposed and investigated. The proposed method relies on a simple statistical analysis approach of the frequency response of the analog circuit and a simple rule-based fuzzy logic classification model to detect and identify the faulty component in the circuit. The proposed approach is tested and evaluated using a commonly used low-pass filter circuit. The test result of the presented approach shows that it can identify the fault and detect the faulty component in the circuit with an average of 98% F-score accuracy. The proposed approach shows comparable performance to more intricate related works.

Magnetic Coupling-Based Battery Impedance Measurement Method

The battery impedance is an important indicator of battery health status. In this paper, a magnetic coupling-based impedance measurement method for electrochemical batteries is proposed. Without affecting the energy injection stage, the designed suppression resistance can minimize the influence of the primary circuit response, and the under-damped oscillation waveform containing the battery impedance information can be directly obtained on the primary inductance. The change of the mutual inductance value within a certain range will not affect the measurement results. Therefore, the measurement system has high stability and robustness. By utilizing the discrete Fourier transform (DFT)-based algorithm to calculate the damped oscillation parameters, the battery impedance is accurately derived from the calculated attenuation coefficient and damped oscillation frequency. The accuracy of this method under different coupling parameters is analyzed and verified by simulation and experiment on a Li-ion battery, which could be employed to estimate the state of charge (SOC).

Parameterized Periodic Steady-State Analysis via Reduced-Order Modeling

This article presents a new approach to construct reduced-order models for large nonlinear circuits excited by periodical or quasi-periodical sources. The key feature in the constructed reduced model is that it enables, through solving a much smaller system, tracing the variations in the periodical steady-state response of the original circuit with regards to variations in selected design parameters. The proposed approach is based on the notion of using discrete empirical interpolation to project the nonlinear operator of the circuit equation onto a smaller subspace. In addition, the original system equations are projected onto the subspace spanned by the first few derivatives of the solution with respect to the selected design parameters. Computational savings are made possible through solving a reduced system of equations instead of the full system. Numerical examples are presented to validate the accuracy and efficiency of the proposed approach.

Research on the efficiency of single-wire power transmission

With the development of related theoretical research on Single Wire Power Transfer(SWPT), the SWPT system has demonstrated its advantages in a variety of special environments. In this paper, the influence of capacitance and inductance on transmission efficiency is studied in order to improve the transmission efficiency of swpt system. This article simplifies and analyzes the circuit model of the SWPT system. It can be found that the system is a second-order circuit, and its response distribution trend conforms to the Gaussian function distribution. There should be an optimal ratio between the capacitor and the inductance to maximize the circuit response. Through the influence of different capacitance, inductance, and transmission distance on transmission efficiency, multiple sets of experiments and simulations are carried out. The experiment found that the capacitance, inductance, and transmission efficiency are in accordance with the Gaussian non-normal distribution, and the acquired data is fitted by the Gaussian function. The average relative error of the fitting is less than 1% under different transmission distances, which can be better reflect the relationship between the three. The study of single-wire power transmission system will provide a key reference for wireless power transmission.

Wavelength-dependent electrical response of an organic circuit for color sensing without external filters

The use of organic semiconductors in photodetectors has led to promising results in low-cost light sensing. Although the relatively narrow absorption band of most organic compounds limits their use as wide-band photodetectors, the selection of materials with the desired spectral properties permits the fabrication of wavelength-selective sensors without external color filters. Here, we present a polymer-gated organic complementary inverter circuit exhibiting wavelength-dependent output voltage change that enables dual color sensing via the use of organic semiconductors (PTCDI-C5 and pentacene) with distinct absorption spectra. When illuminated, the inverter circuit shows a wavelength (color)-dependent output voltage change due to the difference in the spectral properties of the semiconductors. Compared to the dark state, the output voltage of the circuit increases under long-wavelength and decreases under short-wavelength illumination. These findings demonstrate a novel use of photoresponsive organic semiconductors to construct simple dual-color sensitive sensors which may simplify the fabrication of multi-wavelength detector circuits.