Reset Conditions Research Articles

A Compact Model of Program Window in HfO<italic>x</italic> RRAM Devices for Conductive Filament Characteristics Analysis

This paper presents a physics-based compact model for the program window in HfOx resistive random access memory devices, defined as the ratio of the resistances in high resistance state (HRS) and low resistance state (LRS). This model allows extracting the characteristics of the conductive filament (CF) in HRS. For a given forming current compliance limit, the program window is shown to be correlated to the thickness of the reoxidized portion of the CF in HRS, which can be modulated by the reset voltage amplitude. On the other hand, the statistical distribution of the memory window depends exponentially on the barrier thickness variations that points to the critical role of reset conditions for the performance optimization of RRAM devices.

A study on HfO2 RRAM in HRS based on I–V and RTN analysis

This paper presents a statistical characterization of random telegraph noise (RTN) in hafnium-oxide-based resistive random access memories (RRAMs) in high resistive state (HRS). Complex RTN signals are analyzed exploiting a Factorial Hidden Markov Model (FHMM) approach, which allows to derive the statistical properties of the RTN signals, directly related to the physical properties of the traps responsible for the multi-level RTN measured in these devices. Noise characteristics in different reset conditions are explored through consecutive switching cycles. Noise spectral analysis is also performed to fully support the investigation. An RRAM compact model is also exploited to estimate the physical properties of the conductive filament and of the dielectric barrier from simple I–V data. These tools are combined together to prove the existence of a direct statistical relation between the reset conditions, the volume of the dielectric barrier created during the reset operation and the average number of active traps contributing to the RTN.

Resistive Switching Performance Improvement of ${\rm Ta}_{2}{\rm O}_{5-x}/{\rm TaO}_{y}$ Bilayer ReRAM Devices by Inserting ${\rm AlO}_{\delta}$ Barrier Layer

By inserting a thin AlOδ barrier layer between the electrode and tantalum oxide resistive switching layer, the triple-layer ReRAM devices with improved resistive switching performance are demonstrated. Pulsed programming measurements without external current compliance show 1011 cycle endurance without performance degradation. The ON/OFF ratio exceeds 1000. Low operation current is achieved using a smaller SET compliance current. Multilevel states are obtained through adjusting SET and RESET conditions, and retention longer than 104 s at 125°C is reported.

Reset control systems with reset band: Well-posedness, limit cycles and stability analysis

Reset controllers provide a simple way to improve performance when controlling strongly traded-off plants. A reset controller operates most of the time as a linear system, but when some condition holds, it performs a zero resetting action on its state. Recently, some generalizations have been proposed, for example, the anticipation of the reset condition with the so-called reset band. There is a lack of analysis tools for reset systems with reset band. In this paper we address this problem by means of Poincaré maps (PM). It is shown how PM can predict the existence and stability of limit cycles, and give also information on pathologies such as Zenoness, and provide parameter ranges where the system is guarded against those behaviors and thus global asymptotical stability (GAS) is guaranteed.

Conductive Filament Expansion in TaOx Bipolar Resistive Random Access Memory during Pulse Cycling

The post-cycling data retention of filamentary operated resistive random access memory (ReRAM) can be improved by minimizing conductive filament expansion during pulse cycling. We find that filament size gradually grows with increasing pulse cycles due to oxygen diffusion from the region surrounding each filament. To achieve long term use of ReRAM while suppressing filament expansion, the key is to control both electric power and pulse width input during switching. We minimize CF expansion based on this concept and demonstrate long data retention even after 106 pulse switchings under optimized reset conditions.

Brian 2 - the second coming: spiking neural network simulation in Python with code generation

Brian 2 is a fundamental rewrite of the Brian [1,2] simulator for spiking neural networks. Brian is written in the Python programming language and focuses on simplicity and extensibility: neuronal models can be described using mathematical formulae (differential equations) and with the use of physical units. Depending on the model equations, several integration methods are available, ranging from exact integration for linear differential equations to numerical integration for arbitrarily complex equations. The same formalism can also be used to specify synaptic models, allowing the user to easily define complex synapse models. Brian 2 keeps most of the syntax and functionality consistent with previous versions of Brian, but achieves more consistency and modularity as well as adding new features such as a simpler and more general new formulation of refractoriness. A consistent interface centered around human-readable descriptions using mathematical notation allows the specification of neuronal models (including complex reset, threshold and refractory conditions), synaptic models (including complex plasticity rules) and synaptic connections. Every aspect of Brian 2 has been designed with extensibility and adaptability in mind, which, for example, makes it straightforward to implement new numerical integration methods. Even though Brian 2 benefits from the ease of use and the flexibility of the Python programming language, its performance is not limited by the speed of Python: At the core of the simulation machinery Brian 2 makes use of fully automated runtime code generation [3], allowing the same model to be run in the Python interpreter, in compiled C++ code or on a GPU using CUDA libraries[4]. The code generation system is designed to be extensible to new target languages and its output can also be used on its own: for situations where high performance is necessary and/or where a Python interpreter is not available (for example for robotics applications), Brian 2 offers tools to assist in assembling the generated code into a stand-alone version that runs independently of Brian or a Python interpreter. To ensure the correctness and maintainability of the software, Brian 2 includes an extensive, full coverage test suite. Debugging of simulation scripts is supported by a configurable logging system, allowing simple monitoring of the internal details of the simulation process. Brian is made available under a free software license and all development takes place in public code repositories [5].

A Generalization of Gray and Whaley's Option

Options markets display interesting features. Most options are executed when they are near the money. However, the underlying asset price varies significantly during the life-time option. It is therefore difficult to predict the future option position. In order to make options' markets more liquid, the paper proposes to replace all options into At-the-Money (ATM) ones by resetting the strike price X to the asset price at pre-specified time point t, before maturity time T. Strike price is locked in at the then underlying asset price S_{t} regardless whether it is above or below S_{t}.The reset condition is in exchange for deposit in the Clearing House. The idea is to provide a general valuation of reset option of Gray and Whaley (1999) in which reset condition does not depend on the relation between the strike price and the underlying asset price. The contribution of this paper is double. First, it shows that our general model option, under specific conditions, can be generalized to the most common ones like for example Black-Scholes-Merton, forward-start and strike reset pricing formulae etc... Second, in line with Haug and Haug (2001), we use the CRR binominal approach (Cox et al., 1979) and an estimation program of the cumulative bivariate normal distribution to provide closed-form solution for the pricing of the generalized European reset option.

Frequency domain properties of reset systems with multiple reset anticipations

A reset controller is a controller that operates most of the time as a linear system, except when some condition holds. The typical reset condition is the zero crossing of the tracking error signal, e ( t ) = 0. At this moment, the controller performs a zero resetting action on its state. It has been shown that reset control is able to overcome fundamental linear limitations. This article studies, within a frequency-domain framework, the generalisation of reset control systems based on including some anticipation on the reset condition.This has a favourable phase lead effect. The paper discusses different reset anticipations schemes, including multiple reset actions in the same period, computes Fourier harmonics and describing function of general reset controllers and shows explicitly the overcoming of frequency-domain limitations (Bode's gain-phase relation).

RTS noise characterization of HfOx RRAM in high resistive state

In this paper we analyze Random Telegraph Signal (RTS) noise and Power Spectral Density (PSD) in hafnium-based RRAMs. RTS measured in HRS exhibits fast and slow multilevel switching events. RTS characteristics are examined through novel color-coded time-lag plots and Hidden Markov Model (HMM) time-series analyses. Results are validated by comparing simulated and experimental PSD. Noise is examined at different reset conditions to provide an insight into the conduction mechanisms in HRS. Higher reset voltages are found to result in greater RTS complexity due to a larger number of active traps as confirmed by PSD.

Effect of the Active Layer Thickness and Temperature on the Switching Kinetics of GeS2-Based Conductive Bridge Memories

In this paper, the effect of the active layer thickness and temperature on the switching kinetics of GeS2-based conductive bridge memories is addressed through electrical characterization. Results are explained in terms of a thermally and field driven ion hopping model for reversible resistance switching. The combined analysis reveals that at high temperature the set voltage and the set resistance decrease. Furthermore, the study suggests that applying the same reset condition, for GeS2 thicknesses lower than 50 nm, the conductive filament is almost dissolved, while for thicker layers a portion of the filament still remains.

Uncertainty quantification in hybrid dynamical systems

Uncertainty quantification (UQ) techniques are frequently used to ascertain output variability in systems with parametric uncertainty. Traditional algorithms for UQ are either system-agnostic and slow (such as Monte Carlo) or fast with stringent assumptions on smoothness (such as polynomial chaos and Quasi-Monte Carlo). In this work, we develop a fast UQ approach for hybrid dynamical systems by extending the polynomial chaos methodology to these systems. To capture discontinuities, we use a wavelet-based Wiener–Haar expansion. We develop a boundary layer approach to propagate uncertainty through separable reset conditions. We also introduce a transport theory based approach for propagating uncertainty through hybrid dynamical systems. Here the expansion yields a set of hyperbolic equations that are solved by integrating along characteristics. The solution of the partial differential equation along the characteristics allows one to quantify uncertainty in hybrid or switching dynamical systems. The above methods are demonstrated on example problems.

Sistemas de Control basados en Reset

A reset control system is formed by a linear controller endowed with certain resetting mechanism, that sets to zero the state. This zeroing of some of the state coordinates is applied when certain condition holds. The condition that triggers resetting is usually the zero crossing of the tracking error. The idea of re-set control dates back to Clegg Integrator (CI) in 1958, and was adopted in the 70's by I. Horowitz, who emphasized the ability of reset systems to overcome fundamental limitations of linear systems with delays or with poles or zeros in the right half-plane. Left aside for some time, the idea was recovered in the last decade and was given a new impulse by several research teams that contribute with advances in analysis, design and application of reset control systems. This interest appears in the context of the present boom of hybrid systems: a reset system is a particular case of hybrid system that, in spite of its simplicity, enables the possibility of overcoming linear limitations. The objetive of this work is to present, in the form of a tutorial, the current panorama in the field. First, a historical review is introduced, on the three main approaches to reset control: the classical approach (based on zero-crossing of the tracking error), the impulsive approach (where reset is applied on a temporal basis) and the hybrid approach (where some sector reset condition is defined). Next, a summary of results is presented on analysis topics (relation to fundamental limitations, stability) and finally several design proposals are discussed, focused to the tuning of PI+CI compensators.

Delay-dependent stability of reset control systems with anticipative reset conditions

Typical reset conditions can be the zero crossing of the tracking error signal e(t) = 0 or when input and output of the reset controller have opposite signs eT(t)u(t) ≤ 0. This paper studies the delay-dependent stability properties for delayed systems with state-dependent reset impulses when anticipation reset actions are used on the reset event conditions. The analysis includes the application of a Lyapunov-Krasovskii functional technique in the time domain for dealing with stability conditions and a frequency domain approach. The effectiveness and the drawback of such an approach are illustrated on an example.

Optimal reset adaptive observer design

A reset adaptive observer (ReAO) is an adaptive observer consisting of an integrator and a reset law that resets the output of the integrator depending on a predefined reset condition. The inclusion of reset elements can improve the observer performance but it can also destroy the stability of the estimation process if the ReAO is not properly tuned. As contribution, a method to optimally tune the parameters and gains of the ReAO is presented. They are optimally chosen by solving the L 2 gain minimization problem, which can be rewritten as an equivalent LMI problem. The effectiveness of the proposed method is checked by simulations comparing the results of an optimal ReAO with an optimal traditional adaptive observer.

Urodynamic characteristics of women with pelvic organ prolapse in prolapse and reset condition

To study the urodynamic characteristics of women with pelvic organ prolapse in prolapse and reset condition. From Jan. 2010 to Apr. 2010, 30 patients with pelvic organ prolapse (POP), including 1 case in grade I, 6 cases in grade II, 21 cases in grade III and 2 cases in grade IV, treated in Peking University People's Hospital were analyzed their urodynamical changes at status of prolapse and reset with pessary. (1) The symptoms: in the prolapse condition, there were 11 patients with bladder outlet obstruction (BOO), 7 patients with residual volume more than 100 ml, and 4 patients with stress urinary incontinence (SUI). In the reset condition, there were 5 patients with BOO, 5 patients with residual volume more than 100 ml, and 4 SUI patients. (2) Characteristics of urodynamic: there were significant difference in first desire to void (FD, P = 0.047), normal desire to void (ND, P = 0.007), strong desire to void (SD, P = 0.001), maximum cystometric capacity (MCC, P = 0.001), maximum flow rate (Q(max), P = 0.001), average flow rate (Q(ave), P = 0.001), and residual volume (RV, P = 0.025) between prolapse and reset condition among all patients. In patients with grade I to II prolapse, Q(max) were (11 ± 6) ml/s in prolapse condition and (15 ± 4) ml/s in reset condition (P = 0.014), Q(ave) were (6 ± 4) ml/s in prolapse condition and (7 ± 3) ml/s in reset condition (P = 0.237), RV were (29 ± 46) ml in prolapse condition and (15 ± 25) ml in reset condition (P = 0.157). Among patients with grade III to IV prolapse, Q(max) were (11 ± 8) ml/s in prolapse condition and (17 ± 10) ml/s in reset condition (P = 0.001), Q(ave) were (5 ± 4) ml/s in prolapse condition and (7 ± 4) ml/s in reset condition (P = 0.002), RV were (105 ± 169) ml in prolapse condition and (47 ± 92) ml in reset condition (P = 0.037). Patients with pelvic organ prolapse III-IV may present pseudo BOO, recessive stress urinary incontinence and residual volume more than 100 ml. There were significant improvement in cystometric sensation, capacity, flow rate, and residual volume after reset. The urodynamic test for patients with pelvic organ prolapse in the reset condition might be much better in evaluating lower urinary tract function.

Reset observers applied to MIMO systems

Abstract A Reset observer (ReO) is a novel sort of observer consisting of an integrator, and a reset law that resets the output of the integrator depending on a predefined switching condition. For SISO systems, the switching condition is defined in such a manner that the ReO is reset when the output estimation error and the reset term have different sign. However, the way to define the reset condition to deal with MIMO systems has not been analyzed previously. As contributions, we provide a formulation to handle ReO for MIMO systems, and an algorithm to compute its L 2 gain for performance purposes. Additionally, the effectiveness of our proposed MIMO ReO is analyzed by simulations.

Analysis by simulation of amorphization current in phase change memory applied to pillar and GST confined type cells

In this work comparative simulations and analysis of amorphization current are presented for pillar type and GST confined type PCRAM structures. The simulations are realized with the PCM model of Sentaurus Device using an analytical phase transition model coupled with a drift–diffusion electro-thermal model for the transport. The objectives of this work are the selection of optimized cell structures for reset conditions. It is confirmed that regarding I reset the GST confined cell is more efficient than the pillar type. Our study points out that a compromise has to be found in some devices where the conditions of an optimized amorphous current correspond to a lowered resistivity contrast between the amorphous and crystalline states. A compromise has also to be found between optimal structures as designed by simulation and technological constraints associated to their fabrication.

Reset compensation for temperature control: Experimental application on heat exchangers

This work aims at improving the control of an industrial heat exchanger by using reset compensation. The goal is investigating the potentials of a hybrid compensator previously developed by the authors, the PI+CI reset compensator, in the robust control when significant uncertainty is present. To this end, a PI+CI compensator has been designed by using a two step method: firstly, a robust base PI compensator is tuned by using the Quantitative Feedback Theory to satisfy (robust) relative stability and tracking specifications; and secondly, a partial reset action is added to the base lineal PI compensator to improve transitory response. In addition, a PI compensator is tuned by using the Internal Model Control for comparison purposes. Finally, the reset conditions are simply modified in the PI+CI compensator to overcome the effect of the dominant time delay over the reset action, through the introduction of a reset band which can have fixed or variable values along the time.

Structural origin of set-reset processes in Ge15Te83Si2 glass investigated using in situ Raman scattering and transmission electron microscopy

We report here that the structural origin of an easily reversible Ge15Te83Si2 glass can be a promising candidate for phase change random access memories. In situ Raman scattering studies on Ge15Te83Si2 sample, undertaken during the amorphous set and reset processes, indicate that the degree of disorder in the glass is reduced from off to set state. It is also found that the local structure of the sample under reset condition is similar to that in the amorphous off state. Electron microscopic studies on switched samples indicate the formation of nanometric sized particles of c-SiTe2 structure.

Exact simulation of final, minimal and maximal values of Brownian motion and jump-diffusions with applications to option pricing

We introduce a method for generating $$(W_{x,T}^{(\mu,\sigma)},m_{x,T}^{(\mu,\sigma)},M_{x,T}^{(\mu,\sigma)})$$ , where $$W_{x,T}^{(\mu,\sigma)}$$ denotes the final value of a Brownian motion starting in x with drift μ and volatility σ at some final time T, $$m_{x,T}^{(\mu,\sigma)} = {\rm inf}_{0\leq t \leq T}W_{x,t}^{(\mu,\sigma)}$$ and $$M_{x,T}^{(\mu,\sigma)} = {\rm sup}_{0\leq t \leq T} W_{x,t}^{(\mu,\sigma)}$$ . By using the trivariate distribution of $$(W_{x,T}^{(\mu,\sigma)},m_{x,T}^{(\mu,\sigma)},M_{x,T}^{(\mu,\sigma)})$$ , we obtain a fast method which is unaffected by the well-known random walk approximation errors. The method is extended to jump-diffusion models. As sample applications we include Monte Carlo pricing methods for European double barrier knock-out calls with continuous reset conditions under both models. The proposed methods feature simple importance sampling techniques for variance reduction.