Search results for "Probability Distribution"
showing 10 items of 263 documents
Noise-induced effects in population dynamics
2002
We investigate the role of noise in the nonlinear relaxation of two ecosystems described by generalized Lotka-Volterra equations in the presence of multiplicative noise. Specifically we study two cases: (i) an ecosystem with two interacting species in the presence of periodic driving; (ii) an ecosystem with a great number of interacting species with random interaction matrix. We analyse the interplay between noise and periodic modulation for case (i) and the role of the noise in the transient dynamics of the ecosystem in the presence of an absorbing barrier in case (ii). We find that the presence of noise is responsible for the generation of temporal oscillations and for the appearance of s…
High redshift galaxies in the ALHAMBRA survey
2015
Context. Most observational results on the high redshift restframe UV-bright galaxies are based on samples pinpointed using the so called dropout technique or Ly-alpha selection. However, the availability of multifilter data allows now replacing the dropout selections by direct methods based on photometric redshifts. In this paper we present the methodology to select and study the population of high redshift galaxies in the ALHAMBRA survey data. Aims. Our aim is to develop a less biased methodology than the traditional dropout technique to study the high redshift galaxies in ALHAMBRA and other multifilter data. Thanks to the wide area ALHAMBRA covers, we especially aim at contributing in th…
Transient behavior of a population dynamical model
2005
The transient behavior of an ecosystem with N random interacting species in the presence of a multiplicative noise is analyzed. The multiplicative noise mimics the interaction with the environment. We investigate different asymptotic dynamical regimes and the role of the external noise on the probability distribution of the local field.
Verhulst model with Lévy white noise excitation
2008
The transient dynamics of the Verhulst model perturbed by arbitrary non-Gaussian white noise is investigated. Based on the infinitely divisible distribution of the Levy process we study the nonlinear relaxation of the population density for three cases of white non-Gaussian noise: (i) shot noise, (ii) noise with a probability density of increments expressed in terms of Gamma function, and (iii) Cauchy stable noise. We obtain exact results for the probability distribution of the population density in all cases, and for Cauchy stable noise the exact expression of the nonlinear relaxation time is derived. Moreover starting from an initial delta function distribution, we find a transition induc…
Continuous-Variable Sampling from Photon-Added or Photon-Subtracted Squeezed States
2017
We introduce a new family of quantum circuits in Continuous Variables and we show that, relying on the widely accepted conjecture that the polynomial hierarchy of complexity classes does not collapse, their output probability distribution cannot be efficiently simulated by a classical computer. These circuits are composed of input photon-subtracted (or photon-added) squeezed states, passive linear optics evolution, and eight-port homodyne detection. We address the proof of hardness for the exact probability distribution of these quantum circuits by exploiting mappings onto different architectures of sub-universal quantum computers. We obtain both a worst-case and an average-case hardness re…
Continuous-Variable Instantaneous Quantum Computing is Hard to Sample
2017
Instantaneous quantum computing is a sub-universal quantum complexity class, whose circuits have proven to be hard to simulate classically in the Discrete-Variable (DV) realm. We extend this proof to the Continuous-Variable (CV) domain by using squeezed states and homodyne detection, and by exploring the properties of post-selected circuits. In order to treat post-selection in CVs we consider finitely-resolved homodyne detectors, corresponding to a realistic scheme based on discrete probability distributions of the measurement outcomes. The unavoidable errors stemming from the use of finitely squeezed states are suppressed through a qubit-into-oscillator GKP encoding of quantum information,…
Distributed learning automata-based scheme for classification using novel pursuit scheme
2020
Learning Automata (LA) is a popular decision making mechanism to “determine the optimal action out of a set of allowable actions” (Agache and Oommen, IEEE Trans Syst Man Cybern-Part B Cybern 2002(6): 738–749, 2002). The distinguishing characteristic of automata-based learning is that the search for the optimising parameter vector is conducted in the space of probability distributions defined over the parameter space, rather than in the parameter space itself (Thathachar and Sastry, IEEE Trans Syst Man Cybern-Part B Cybern 32(6): 711–722, 2002). Recently, Goodwin and Yazidi pioneered the use of Ant Colony Optimisation (ACO) for solving classification problems (Goodwin and Yazidi 2016). In th…
Understanding 802.11e contention-based prioritization mechanisms and their coexistence with legacy 802.11 stations
2005
The IEEE 802.11e task group has reached a stable consensus on two basic contention-based priority mechanisms to promote for standardization: usage of different arbitration interframe spaces and usage of different minimum/maximum contention windows. The goal of this article is to provide a thorough understanding of the principles behind their operation. To this purpose, rather than limit our investigation to high-level (e.g. throughput and delay) performance figures, we take a closer look at their detailed operation, also in terms of low-level performance metrics (e.g., the probability of accessing specific channel slots). Our investigation on one hand confirms that AIFS differentiation prov…
A probabilistic rainfall model to estimate the leading-edge lifetime of wind turbine blade coating system
2021
Rain-induced leading-edge erosion of wind turbine blades is associated with high repair and maintenance costs. For efficient operation and maintenance, erosion models are required that provide estimates of blade coating lifetime at a real scale. In this study, a statistical rainfall model is established that describes probabilistic distributions of rain parameters that are critical for site-specific leading-edge erosion assessment. A new droplet size distribution (DSD) is determined based on two years’ onshore rainfall data of an inland site in the Netherlands and the obtained DSD is compared with those from the literature. Joint probability distribution functions of rain intensities and dr…
Coherence Checking and Propagation of Lower Probability Bounds
2003
In this paper we use imprecise probabilities, based on a concept of generalized coherence (g-coherence), for the management of uncertain knowledge and vague information. We face the problem of reducing the computational difficulties in g-coherence checking and propagation of lower conditional probability bounds. We examine a procedure, based on linear systems with a reduced number of unknowns, for the checking of g-coherence. We propose an iterative algorithm to determine the reduced linear systems. Based on the same ideas, we give an algorithm for the propagation of lower probability bounds. We also give some theoretical results that allow, by suitably modifying our algorithms, the g-coher…