scholarly journals A Simple Method to Estimate Time-Varying Statistics for the Lifespan Distribution of Products Using Stock and Flow Data

2019 ◽  
Vol 15 (1) ◽  
pp. 70-85
Author(s):  
Takuya HARA
Keyword(s):  
Time Varying ◽  
Flow Data ◽  
Simple Method ◽  
Lifespan Distribution

scholarly journals Damping Effects Induced by a Mass Moving along a Pendulum

2014 ◽  
Vol 2014 ◽  
pp. 1-9 ◽  
Author(s):  
E. Gandino ◽  
S. Marchesiello ◽  
A. Bellino ◽  
A. Fasana ◽  
L. Garibaldi
Keyword(s):  
Linear Time ◽  
Damping Ratio ◽  
System Response ◽  
Time Varying ◽  
Simple Method ◽  
Equivalent Damping ◽  
Stochastic Subspace Identification ◽  
Time Varying Systems ◽  
Instantaneous Frequencies ◽  
Short Time

The experimental study of damping in a time-varying inertia pendulum is presented. The system consists of a disk travelling along an oscillating pendulum: large swinging angles are reached, so that its equation of motion is not only time-varying but also nonlinear. Signals are acquired from a rotary sensor, but some remarks are also proposed as regards signals measured by piezoelectric or capacitive accelerometers. Time-varying inertia due to the relative motion of the mass is associated with the Coriolis-type effects appearing in the system, which can reduce and also amplify the oscillations. The analytical model of the pendulum is introduced and an equivalent damping ratio is estimated by applying energy considerations. An accurate model is obtained by updating the viscous damping coefficient in accordance with the experimental data. The system is analysed through the application of a subspace-based technique devoted to the identification of linear time-varying systems: the so-called short-time stochastic subspace identification (ST-SSI). This is a very simple method recently adopted for estimating the instantaneous frequencies of a system. In this paper, the ST-SSI method is demonstrated to be capable of accurately estimating damping ratios, even in the challenging cases when damping may turn to negative due to the Coriolis-type effects, thus causing amplifications of the system response.

Dynamics of a Class of Nonautonomous Lorenz-Type Systems

2016 ◽  
Vol 26 (12) ◽  
pp. 1650208 ◽  
Author(s):  
Xu Zhang
Keyword(s):  
Type Systems ◽  
Initial Position ◽  
Time Varying ◽  
Lorenz Model ◽  
Simple Method ◽  
Varying Parameters ◽  
Weather And Climate ◽  
Time Varying Parameters ◽  
Strange Nonchaotic Attractors ◽  
Ultimate Bound

The dynamical properties of a kind of Lorenz-type systems with time-varying parameters are studied. The time-varying ultimate bounds are estimated, and a simple method is provided to generate strange attractors, including both the strange nonchaotic attractors (SNAs) and chaotic attractors. The approach is: (i) take an autonomous system with an ultimate bound from the Lorenz family; (ii) add at least two time-varying parameters with incommensurate frequencies satisfying certain conditions; (iii) choose the proper initial position and time by numerical simulations. Three interesting examples are given to illustrate this method with computer simulations. The first one is derived from the classical Lorenz model, and generates an SNA. The second one generates an SNA or a Lorenz-like attractor. The third one exhibits the coexistence of two SNAs and a Lorenz-like attractor. The nonautonomous Lorenz-type systems present more realistic models, which provide further understanding and applications of the numerical analysis in weather and climate predication, synchronization, and other fields.

A Simple Spike Train Decoder Inspired by the Sampling Theorem

1996 ◽  
Vol 8 (1) ◽  
pp. 67-84 ◽  
Author(s):  
David A. August ◽  
William B Levy
Keyword(s):  
Firing Rate ◽  
Spike Train ◽  
Sampling Theorem ◽  
Time Varying ◽  
Average Firing Rate ◽  
Simple Method ◽  
Postsynaptic Cell ◽  
Neural Information ◽  
Neural Information Processing ◽  
Dc Bias

Reconstructing a time-varying stimulus estimate from a spike train (Bialek's “decoding” of a spike train) has become an important way to study neural information processing. In this paper, we describe a simple method for reconstructing a time-varying current injection signal from the simulated spike train it produces. This technique extracts most of the information from the spike train, provided that the input signal is appropriately matched to the spike generator. To conceptualize this matching, we consider spikes as instantaneous “samples” of the somatic current. The Sampling Theorem is then applicable, and it suggests that the bandwidth of the injected signal not exceed half the spike generator's average firing rate. The average firing rate, in turn, depends on the amplitude range and DC bias of the injected signal. We hypothesize that nature faces similar problems and constraints when transmitting a time-varying waveform from the soma of one neuron to the dendrite of the postsynaptic cell.

Observing unobservable: estimating the time-varying efficiency of intellectual capital

2017 ◽  
Vol 21 (4) ◽  
pp. 377-387 ◽  
Author(s):  
Petr Parshakov
Keyword(s):  
Panel Data ◽  
Intellectual Capital ◽  
Stochastic Frontier Analysis ◽  
Performance Standard ◽  
Time Varying ◽  
Dynamic Efficiency ◽  
Data Set ◽  
Simple Method ◽  
Content Type ◽  
Frontier Analysis

Purpose Company intellectual capital (IC) is nowadays considered as a key resource that can transform a company’s value. For this reason, the efficiency of IC is crucial for all stakeholders. Evaluating efficiency is difficult, because IC is partly unobservable and its efficiency varies across time. The aim of this study is to suggest a methodology for estimating the dynamic efficiency of a company’s intellectual resources. Design/methodology/approach The panel data model suggested by Kneip et al. (2012) is used to estimate dynamic efficiency. The main feature of this model is that the unobservable component has a multi-dimensional factor structure. Taking advantage of the ability of this model to control for unobserved complex heterogeneity, the authors use the results in further stochastic frontier analysis. A data set containing information about Russian companies for the period from 2001 to 2010 is used. Findings In this paper, the dynamic efficiency of Russian companies is estimated. It is shown that, using the traditional efficiency estimate, companies can be overestimated. Research limitations/implications The main limitation of the suggested methodology is that it is necessary to have a long panel data structure. Practical implications Taking advantage of time-varying efficiency, one can estimate the efficiency growth rate as a measure of performance, standard deviation as a measure of risk and autocorrelation as a measure of stability. Originality/value This is the first study to present clear evidence of the time-varying nature of IC efficiency. On the methodological side, the paper presents a fairly simple method capable of estimating various indicators of a company’s efficiency.

Interactions between TGF-dependent and myogenic oscillations in tubular pressure and whole kidney blood flow in both SDR and SHR

2006 ◽  
Vol 290 (3) ◽  
pp. F720-F732 ◽  
Author(s):  
Ramakrishna Raghavan ◽  
Xinnian Chen ◽  
Kay-Pong Yip ◽  
Donald J. Marsh ◽  
Ki H. Chon
Keyword(s):  
Blood Flow ◽  
Tubuloglomerular Feedback ◽  
Nonlinear Interactions ◽  
Time Varying ◽  
Nonlinear Coupling ◽  
Flow Data ◽  
Sprague Dawley ◽  
Spontaneously Hypertensive ◽  
Kidney Blood Flow ◽  
Time Invariant

We previously showed that nonlinear interactions between the two renal autoregulatory mechanics (tubuloglomerular feedback and the myogenic mechanism) were observed in the stop flow pressure (SFP) and whole kidney blood flow data from Sprague-Dawley rats (SDR) using time-invariant bispectrum analysis ( 3 , 4 ). No such nonlinear interactions were observed in either SFP or whole kidney blood flow data obtained from spontaneously hypertensive rats (SHR). We speculated that the failure to detect nonlinear interactions in the SHR data may be related to our observation that these interactions were not continuous and therefore had time-varying characteristics. Thus the absence of such nonlinear interactions may be due to an inappropriate time-invariant method being applied to data that are especially time varying in nature. We examine this possibility in this paper by using a time-varying bispectrum approach, which we developed for this purpose. Indeed, we found significant nonlinear interactions in SHR ( n = 18 for SFP; n = 12 for whole kidney blood flow). Moreover, the duration of nonlinear coupling is found statistically to be longer ( P = 0.001) in SFP data from either SDR or SHR than it is in whole kidney data from either type of rat. We conclude that nonlinear coupling is present at both the single nephron as well as the whole kidney level for SDR and SHR. In addition, SHR data at the whole kidney level exhibit the most transient nonlinear coupling phenomena.

scholarly journals H∞ and Passive Fuzzy Control for Non-Linear Descriptor Systems with Time-Varying Delay and Sensor Faults

Mathematics ◽  
2021 ◽  
Vol 9 (18) ◽  
pp. 2203
Author(s):  
Houssem Jerbi ◽  
Mourad Kchaou ◽  
Attia Boudjemline ◽  
Mohamed Amin Regaieg ◽  
Sondes Ben Aoun ◽  
...  
Keyword(s):  
Sufficient Conditions ◽  
Lyapunov Theory ◽  
Descriptor Systems ◽  
Time Varying ◽  
Sensor Failure ◽  
Simple Method ◽  
Time Varying Delay ◽  
Performance Requirements ◽  
Cone Complementarity Linearization ◽  
Varying Delay

In this paper, the problem of reliable control design with mixed H∞ /passive performance is discussed for a class of Takagi–Sugeno TS fuzzy descriptor systems with time-varying delay, sensor failure, and randomly occurred non-linearity. Based on the Lyapunov theory, firstly, a less conservative admissible criterion is established by combining the delay decomposition and reciprocally convex approaches. Then, the attention is focused on the design of a reliable static output feedback (SOF) controller with mixed H∞ /passive performance requirements. The key merit of the paper is to propose a simple method to design such a controller since the system output is subject to probabilistic missing data and noise. Using the output vector as a state component, an augmented model is introduced, and sufficient conditions are derived to achieve the desired performance of the closed-loop system. In addition, the cone complementarity linearization (CCL) algorithm is provided to calculate the controller gains. At last, three numerical examples, including computer-simulated truck-trailer and ball and beam systems are given to show the efficacy of our proposed approach, compared with existing ones in the literature.

A simple way for producing holographic filters suitable for image improvement

1978 ◽  
Vol 36 (1) ◽  
pp. 226-227
Author(s):  
K.-H. Herrmann ◽  
E. Reuber ◽  
P. Schiske
Keyword(s):  
Transfer Functions ◽  
Diffraction Order ◽  
Lateral Position ◽  
Simple Method ◽  
Spatial Frequencies ◽  
Resolution Electron ◽  
Wiener Filters ◽  
Image Improvement ◽  
Optical Reconstruction ◽  
Set Up

Aposteriori deblurring of high resolution electron micrographs of weak phase objects can be performed by holographic filters [1,2] which are arranged in the Fourier domain of a light-optical reconstruction set-up. According to the diffraction efficiency and the lateral position of the grating structure, the filters permit adjustment of the amplitudes and phases of the spatial frequencies in the image which is obtained in the first diffraction order.In the case of bright field imaging with axial illumination, the Contrast Transfer Functions (CTF) are oscillating, but real. For different imageforming conditions and several signal-to-noise ratios an extensive set of Wiener-filters should be available. A simple method of producing such filters by only photographic and mechanical means will be described here.A transparent master grating with 6.25 lines/mm and 160 mm diameter was produced by a high precision computer plotter. It is photographed through a rotating mask, plotted by a standard plotter.

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