959 resultados para White noise


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This silent swarm of stylized crickets is downloading data from Internet and catalogue searches being undertaken by the public at the State Library Queensland. These searches are being displayed on the screen on their backs. Each cricket downloads the searches and communicates this information with other crickets. Commonly found searches spread like a meme through the swarm. In this work memes replace the crickets’ song, washing like a wave through the swarm and changing on the whim of Internet users. When one cricket begins calling others, the swarm may respond to produce emergent patterns of text. When traffic is slow or of now interest to the crickets, they display onomatopoeia. The work is inspired by R. Murray Schafer’s research into acoustic ecologies. In the 1960’s Schafer proposed that many species develop calls that fit niches within their acoustic environment. An increasing background of white noise dominates the acoustic environment of urban human habitats, leaving few acoustic niches for other species to communicate. The popularity of headphones and portable music may be seen as an evolution of our acoustic ecology driven by our desire to hear expressive, meaningful sound, above the din of our cities. Similarly, the crickets in this work are hypothetical creatures that have evolved to survive in a noisy human environment. This speculative species replaces auditory calls with onomatopoeia and information memes, communicating with the swarm via radio frequency chirps instead of sound. Whilst these crickets cannot make sound, each individual has been programmed respond to sound generated by the audience, by making onomatopoeia calls in text. Try talking to a cricket, blowing on its tail, or making other sounds to trigger a call.

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This paper considers VECMs for variables exhibiting cointegration and common features in the transitory components. While the presence of cointegration between the permanent components of series reduces the rank of the long-run multiplier matrix, a common feature among the transitory components leads to a rank reduction in the matrix summarizing short-run dynamics. The common feature also implies that there exists linear combinations of the first-differenced variables in a cointegrated VAR that are white noise and traditional tests focus on testing for this characteristic. An alternative, however, is to test the rank of the short-run dynamics matrix directly. Consequently, we use the literature on testing the rank of a matrix to produce some alternative test statistics. We also show that these are identical to one of the traditional tests. The performance of the different methods is illustrated in a Monte Carlo analysis which is then used to re-examine an existing empirical study. Finally, this approach is applied to provide a check for the presence of common dynamics in DSGE models.

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We propose a new active noise control (ANC) technique. The technique has a feedback structure to have a simple configuration in practical implementation. In this approach, the secondary path is modelled online to ensure convergence of the system as the secondary paths are practically time varying or non-linear. The proposed method consists of two steps: a noise controller which is based on a modified FxLMS algorithm, and a new variable step size (VSS) LMS algorithm which is used to adapt the modelling filter with the secondary path. The proposed algorithm stops injection of the white noise at the optimum point and reactivate the injection during the operation, if needed, to maintain performance of the system. Eliminating continuous injection of the white noise increases the performance of the proposed method significantly and makes it more desirable for practical ANC systems. The computer simulations are presented to show the effectiveness of the proposed method.

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Operational modal analysis (OMA) is prevalent in modal identifi cation of civil structures. It asks for response measurements of the underlying structure under ambient loads. A valid OMA method requires the excitation be white noise in time and space. Although there are numerous applications of OMA in the literature, few have investigated the statistical distribution of a measurement and the infl uence of such randomness to modal identifi cation. This research has attempted modifi ed kurtosis to evaluate the statistical distribution of raw measurement data. In addition, a windowing strategy employing this index has been proposed to select quality datasets. In order to demonstrate how the data selection strategy works, the ambient vibration measurements of a laboratory bridge model and a real cable-stayed bridge have been respectively considered. The analysis incorporated with frequency domain decomposition (FDD) as the target OMA approach for modal identifi cation. The modal identifi cation results using the data segments with different randomness have been compared. The discrepancy in FDD spectra of the results indicates that, in order to fulfi l the assumption of an OMA method, special care shall be taken in processing a long vibration measurement data. The proposed data selection strategy is easy-to-apply and verifi ed effective in modal analysis.

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Oscillatory entrainment to the speech signal is important for language processing, but has not yet been studied in developmental disorders of language. Developmental dyslexia, a difficulty in acquiring efficient reading skills linked to difficulties with phonology (the sound structure of language), has been associated with behavioural entrainment deficits. It has been proposed that the phonological ‘deficit’ that characterises dyslexia across languages is related to impaired auditory entrainment to speech at lower frequencies via neuroelectric oscillations (<10 Hz, ‘temporal sampling theory’). Impaired entrainment to temporal modulations at lower frequencies would affect the recovery of the prosodic and syllabic structure of speech. Here we investigated event-related oscillatory EEG activity and contingent negative variation (CNV) to auditory rhythmic tone streams delivered at frequencies within the delta band (2 Hz, 1.5 Hz), relevant to sampling stressed syllables in speech. Given prior behavioural entrainment findings at these rates, we predicted functionally atypical entrainment of delta oscillations in dyslexia. Participants performed a rhythmic expectancy task, detecting occasional white noise targets interspersed with tones occurring regularly at rates of 2 Hz or 1.5 Hz. Both groups showed significant entrainment of delta oscillations to the rhythmic stimulus stream, however the strength of inter-trial delta phase coherence (ITC, ‘phase locking’) and the CNV were both significantly weaker in dyslexics, suggestive of weaker entrainment and less preparatory brain activity. Both ITC strength and CNV amplitude were significantly related to individual differences in language processing and reading. Additionally, the instantaneous phase of prestimulus delta oscillation predicted behavioural responding (response time) for control participants only.

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Extant models of decision making in social neurobiological systems have typically explained task dynamics as characterized by transitions between two attractors. In this paper, we model a three-attractor task exemplified in a team sport context. The model showed that an attacker–defender dyadic system can be described by the angle x between a vector connecting the participants and the try line. This variable was proposed as an order parameter of the system and could be dynamically expressed by integrating a potential function. Empirical evidence has revealed that this kind of system has three stable attractors, with a potential function of the form V(x)=−k1x+k2ax2/2−bx4/4+x6/6, where k1 and k2 are two control parameters. Random fluctuations were also observed in system behavior, modeled as white noise εt, leading to the motion equation dx/dt = −dV/dx+Q0.5εt, where Q is the noise variance. The model successfully mirrored the behavioral dynamics of agents in a social neurobiological system, exemplified by interactions of players in a team sport.

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The anharmonic oscillator under combined sinusoidal and white noise excitation is studied using the Gaussian closure approximation. The mean response and the steady-state variance of the system is obtained by the WKBJ approximation and also by the Fokker Planck equation. The multiple steadystate solutions are obtained and their stability analysis is presented. Numerical results are obtained for a particular set of system parameters. The theoretical results are compared with a digital simulation study to bring out the usefulness of the present approximate theory.

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It is now well known that in extreme quantum limit, dominated by the elastic impurity scattering and the concomitant quantum interference, the zero-temperature d.c. resistance of a strictly one-dimensional disordered system is non-additive and non-self-averaging. While these statistical fluctuations may persist in the case of a physically thin wire, they are implicitly and questionably ignored in higher dimensions. In this work, we have re-examined this question. Following an invariant imbedding formulation, we first derive a stochastic differential equation for the complex amplitude reflection coefficient and hence obtain a Fokker-Planck equation for the full probability distribution of resistance for a one-dimensional continuum with a Gaussian white-noise random potential. We then employ the Migdal-Kadanoff type bond moving procedure and derive the d-dimensional generalization of the above probability distribution, or rather the associated cumulant function –‘the free energy’. For d=3, our analysis shows that the dispersion dominates the mobilitly edge phenomena in that (i) a one-parameter B-function depending on the mean conductance only does not exist, (ii) an approximate treatment gives a diffusion-correction involving the second cumulant. It is, however, not clear whether the fluctuations can render the transition at the mobility edge ‘first-order’. We also report some analytical results for the case of the one dimensional system in the presence of a finite electric fiekl. We find a cross-over from the exponential to the power-low length dependence of resistance as the field increases from zero. Also, the distribution of resistance saturates asymptotically to a poissonian form. Most of our analytical results are supported by the recent numerical simulation work reported by some authors.

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The coalescence of nearly rigid liquid droplets in a turbulent flow field is viewed as the drainage of a thin film of liquid under the action of a stochastic force representing the effect of turbulence. The force squeezing the drop pair is modelled as a correlated random function of time. The drops are assumed to coalesce once the film thickness becomes smaller than a critical thickness while they are regarded as separated if their distance of separation is larger than a prescribed distance. A semi-analytical solution is derived to determine the coalescence efficiency. The veracity of the solution procedure is established via a Monte-Carlo solution scheme. The model predicts a reversing trend of the dependence of the coalescence efficiency on the drop radii, the film liquid viscosity and the turbulence energy dissipation per unit mass, as the relative fluctuation increases. However, the dependence on physical parameters is weak (especially at high relative fluctuation) so that for the smallest droplets (which are nearly rigid) the coalescence efficiency may be treated as an empirical constant. The predictions of this model are compared with those of a white-noise force model. The results of this paper and those in Muralidhar and Ramkrishna (1986, Ind. Engng Chem. Fundam. 25, 554-56) suggest that dynamic drop deformation is the key factor that influences the coalescence efficiency.

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For a dynamically disordered continuum it is found that the exact quantum mechanical mean square displacement 〈x2(t)〉∼t3, for t→∞. A Gaussian white-noise spectrum is assumed for the random potential. The result differs qualitatively from the diffusive behavior well known for the one-band lattice Hamiltonian, and is understandable in terms of the momentum cutoff inherent in the lattice, simulating a "momentum bath."

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A method is presented for obtaining, approximately, the response covariance and probability distribution of a non-linear oscillator under a Gaussian excitation. The method has similarities with the hierarchy closure and the equivalent linearization approaches, but is different. A Gaussianization technique is used to arrive at the output autocorrelation and the input-output cross-correlation. This along with an energy equivalence criterion is used to estimate the response distribution function. The method is applicable in both the transient and steady state response analysis under either stationary or non-stationary excitations. Good comparison has been observed between the predicted and the exact steady state probability distribution of a Duffing oscillator under a white noise input.

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First, the non-linear response of a gyrostabilized platform to a small constant input torque is analyzed in respect to the effect of the time delay (inherent or deliberately introduced) in the correction torque supplied by the servomotor, which itself may be non-linear to a certain extent. The equation of motion of the platform system is a third order nonlinear non-homogeneous differential equation. An approximate analytical method of solution of this equation is utilized. The value of the delay at which the platform response becomes unstable has been calculated by using this approximate analytical method. The procedure is illustrated by means of a numerical example. Second, the non-linear response of the platform to a random input has been obtained. The effects of several types of non-linearity on reducing the level of the mean square response have been investigated, by applying the technique of equivalent linearization and solving the resulting integral equations by using laguerre or Gaussian integration techniques. The mean square responses to white noise and band limited white noise, for various values of the non-linear parameter and for different types of non-linearity function, have been obtained. For positive values of the non-linear parameter the levels of the non-linear mean square responses to both white noise and band-limited white noise are low as compared to the linear mean square response. For negative values of the non-linear parameter the level of the non-linear mean square response at first increases slowly with increasing values of the non-linear parameter and then suddenly jumps to a high level, at a certain value of the non-linearity parameter.

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The goal of this study is the multi-mode structural vibration control in the composite fin-tip of an aircraft. Structural model of the composite fin-tip with surface bonded piezoelectric actuators is developed using the finite element method. The finite element model is updated experimentally to reflect the natural frequencies and mode shapes accurately. A model order reduction technique is employed for reducing the finite element structural matrices before developing the controller. Particle swarm based evolutionary optimization technique is used for optimal placement of piezoelectric patch actuators and accelerometer sensors to suppress vibration. H{infty} based active vibration controllers are designed directly in the discrete domain and implemented using dSpace® (DS-1005) electronic signal processing boards. Significant vibration suppression in the multiple bending modes of interest is experimentally demonstrated for sinusoidal and band limited white noise forcing functions.

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Sequence design problems are considered in this paper. The problem of sum power minimization in a spread spectrum system can be reduced to the problem of sum capacity maximization, and vice versa. A solution to one of the problems yields a solution to the other. Subsequently, conceptually simple sequence design algorithms known to hold for the white-noise case are extended to the colored noise case. The algorithms yield an upper bound of 2N - L on the number of sequences where N is the processing gain and L the number of non-interfering subsets of users. If some users (at most N - 1) are allowed to signal along a limited number of multiple dimensions, then N orthogonal sequences suffice.