Search results for "Stochastic Proce"
showing 10 items of 349 documents
Bazaar economics
2015
Competitive Equilibrium theory has been a widely accepted and extensively used cornerstone in economics for over a century. Here, we suggest a complementary model—motivated by the haggling in a bazaar—that offers a useful, first-principle account of market behavior that better accounts for the observed outcomes in forty market experiments. The Bazaar model uses simple stochastic processes to drive the matching of traders and the determination of price. We show that as agents become more impatient, the system tends toward more Competitive-Equilibrium-like outcomes.
Analysis of the level-crossing rate and average duration of fades of WSSUS channels
2017
Studies of the level-crossing rate (LCR) and the average duration of fades (ADF) are so far only devoted to stochastic processes being a function of one independent variable, which is usually time or in some few cases frequency. In this paper, we study the LCR (ADF) of wide-sense stationary uncorrelated scattering (WSSUS) processes in the time-frequency domain. A closed-form solution will be derived for the so-called time-frequency LCR (ADF) of the absolute value of the time-variant transfer function (TVTF) of WSSUS processes. It is shown that the LCR (ADF) is circularly symmetric in the normalized time-frequency domain. The derived time-frequency LCR contains the time LCR and frequency LCR…
An enhanced memetic differential evolution in filter design for defect detection in paper production.
2008
This article proposes an Enhanced Memetic Differential Evolution (EMDE) for designing digital filters which aim at detecting defects of the paper produced during an industrial process. Defect detection is handled by means of two Gabor filters and their design is performed by the EMDE. The EMDE is a novel adaptive evolutionary algorithm which combines the powerful explorative features of Differential Evolution with the exploitative features of three local search algorithms employing different pivot rules and neighborhood generating functions. These local search algorithms are the Hooke Jeeves Algorithm, a Stochastic Local Search, and Simulated Annealing. The local search algorithms are adap…
M/M/1 queue in two alternating environments and its heavy traffic approximation
2018
We investigate an M/M/1 queue operating in two switching environments, where the switch is governed by a two-state time-homogeneous Markov chain. This model allows to describe a system that is subject to regular operating phases alternating with anomalous working phases or random repairing periods. We first obtain the steady-state distribution of the process in terms of a generalized mixture of two geometric distributions. In the special case when only one kind of switch is allowed, we analyze the transient distribution, and investigate the busy period problem. The analysis is also performed by means of a suitable heavy-traffic approximation which leads to a continuous random process. Its d…
Cluster size distributions in particle systems with asymmetric dynamics
2001
We present exact and asymptotic results for clusters in the one-dimensional totally asymmetric exclusion process (TASEP) with two different dynamics. The expected length of the largest cluster is shown to diverge logarithmically with increasing system size for ordinary TASEP dynamics and as a logarithm divided by a double logarithm for generalized dynamics, where the hopping probability of a particle depends on the size of the cluster it belongs to. The connection with the asymptotic theory of extreme order statistics is discussed in detail. We also consider a related model of interface growth, where the deposited particles are allowed to relax to the local gravitational minimum.
On weakly measurable stochastic processes and absolutely summing operators
2006
A characterization of absolutely summing operators by means of McShane integrable stochastic processes is considered
Prediction of tyrosinase inhibition activity using atom-based bilinear indices.
2007
A set of novel atom-based molecular fingerprints is proposed based on a bilinear map similar to that defined in linear algebra. These molecular descriptors (MDs) are proposed as a new means of molecular parametrization easily calculated from 2D molecular information. The nonstochastic and stochastic molecular indices match molecular structure provided by molecular topology by using the kth nonstochastic and stochastic graph-theoretical electronic-density matrices, M(k) and S(k), respectively. Thus, the kth nonstochastic and stochastic bilinear indices are calculated using M(k) and S(k) as matrix operators of bilinear transformations. Chemical information is coded by using different pair com…
Stochastic seismic analysis of hydrodynamic pressure in dam reservoir systems
2002
Hydrodynamic seismic-induced pressure requires careful consideration in the aseismic design of dams. Effects induced by earthquake excitation may cause many-fold increments of hydrostatic pressure. In this study earthquake excitation has been modelled by means of random process theory obtaining the response statistics of a dam-reservoir dynamical system. The analysis has been conducted assuming a rigid retaining wall of the reservoir and dissipative fluid. Copyright © 2002 John Wiley & Sons, Ltd.
Scaling and data collapse for the mean exit time of asset prices
2005
We study theoretical and empirical aspects of the mean exit time of financial time series. The theoretical modeling is done within the framework of continuous time random walk. We empirically verify that the mean exit time follows a quadratic scaling law and it has associated a pre-factor which is specific to the analyzed stock. We perform a series of statistical tests to determine which kind of correlation are responsible for this specificity. The main contribution is associated with the autocorrelation property of stock returns. We introduce and solve analytically both a two-state and a three-state Markov chain models. The analytical results obtained with the two-state Markov chain model …
Mean Escape Time in a System with Stochastic Volatility
2007
We study the mean escape time in a market model with stochastic volatility. The process followed by the volatility is the Cox Ingersoll and Ross process which is widely used to model stock price fluctuations. The market model can be considered as a generalization of the Heston model, where the geometric Brownian motion is replaced by a random walk in the presence of a cubic nonlinearity. We investigate the statistical properties of the escape time of the returns, from a given interval, as a function of the three parameters of the model. We find that the noise can have a stabilizing effect on the system, as long as the global noise is not too high with respect to the effective potential barr…