26,442 research outputs found
Bayesian power-spectrum inference for Large Scale Structure data
We describe an exact, flexible, and computationally efficient algorithm for a
joint estimation of the large-scale structure and its power-spectrum, building
on a Gibbs sampling framework and present its implementation ARES (Algorithm
for REconstruction and Sampling). ARES is designed to reconstruct the 3D
power-spectrum together with the underlying dark matter density field in a
Bayesian framework, under the reasonable assumption that the long wavelength
Fourier components are Gaussian distributed. As a result ARES does not only
provide a single estimate but samples from the joint posterior of the
power-spectrum and density field conditional on a set of observations. This
enables us to calculate any desired statistical summary, in particular we are
able to provide joint uncertainty estimates. We apply our method to mock
catalogs, with highly structured observational masks and selection functions,
in order to demonstrate its ability to reconstruct the power-spectrum from real
data sets, while fully accounting for any mask induced mode coupling.Comment: 25 pages, 15 figure
Comparison of Langevin and Markov channel noise models for neuronal signal generation
The stochastic opening and closing of voltage-gated ion channels produces
noise in neurons. The effect of this noise on the neuronal performance has been
modelled using either approximate or Langevin model, based on stochastic
differential equations or an exact model, based on a Markov process model of
channel gating. Yet whether the Langevin model accurately reproduces the
channel noise produced by the Markov model remains unclear. Here we present a
comparison between Langevin and Markov models of channel noise in neurons using
single compartment Hodgkin-Huxley models containing either and
, or only voltage-gated ion channels. The performance of the
Langevin and Markov models was quantified over a range of stimulus statistics,
membrane areas and channel numbers. We find that in comparison to the Markov
model, the Langevin model underestimates the noise contributed by voltage-gated
ion channels, overestimating information rates for both spiking and non-spiking
membranes. Even with increasing numbers of channels the difference between the
two models persists. This suggests that the Langevin model may not be suitable
for accurately simulating channel noise in neurons, even in simulations with
large numbers of ion channels
A study of data coding technology developments in the 1980-1985 time frame, volume 2
The source parameters of digitized analog data are discussed. Different data compression schemes are outlined and analysis of their implementation are presented. Finally, bandwidth compression techniques are given for video signals
Implementacija digitalnog generatora obojenog šuma bez množila
Colored noise can be generated by filtering of the white noise. It is a simple task. However, it becomes challenging if high operating speed of the generator is required. The realization of digital filter generally requires one multiplication per coefficient. Therefore, a high operating speed is achieved only with the cost of several generalpurpose multipliers. In this paper, a multiplierless realization of the colored noise generator is proposed. It is based on the filtering of 1-bit random signal by a finite impulse response filter. The design of the generator is described and its implementation is considered. Furthermore, an application is described in which the proposed generator is used in mitigation of undesired effects caused by nonlinearities in an analog to digital converter.Obojeni šum može se generirati filtriranjem bijelog šuma. To je jednostavan postupak. Međutim, on postaje izazovan ako se od generatora traži velika brzina rada. Realizacija digitalnog filtra u pravilu zahtijeva jedno množenje po koeficijentu. Zato se velika brzina rada može postići samo uz cijenu većeg broja množila opće namjene. U ovom radu predložena je realizacija generatora obojenog šuma koja ne sadrži množila. Ona se temelji se na filtraciji 1-bitnog slučajnog signala pomoću filtra s konačnim impulsnim odzivom. Opisano je projektiranje generatora te je razmotrena njegova implementacija. Nadalje, opisana je primjena u kojoj je predloženi generator iskorišten za smanjivanje utjecaja nelinearnosti u analogno digitalnom pretvorniku
Mixing Bandt-Pompe and Lempel-Ziv approaches: another way to analyze the complexity of continuous-states sequences
In this paper, we propose to mix the approach underlying Bandt-Pompe
permutation entropy with Lempel-Ziv complexity, to design what we call
Lempel-Ziv permutation complexity. The principle consists of two steps: (i)
transformation of a continuous-state series that is intrinsically multivariate
or arises from embedding into a sequence of permutation vectors, where the
components are the positions of the components of the initial vector when
re-arranged; (ii) performing the Lempel-Ziv complexity for this series of
`symbols', as part of a discrete finite-size alphabet. On the one hand, the
permutation entropy of Bandt-Pompe aims at the study of the entropy of such a
sequence; i.e., the entropy of patterns in a sequence (e.g., local increases or
decreases). On the other hand, the Lempel-Ziv complexity of a discrete-state
sequence aims at the study of the temporal organization of the symbols (i.e.,
the rate of compressibility of the sequence). Thus, the Lempel-Ziv permutation
complexity aims to take advantage of both of these methods. The potential from
such a combined approach - of a permutation procedure and a complexity analysis
- is evaluated through the illustration of some simulated data and some real
data. In both cases, we compare the individual approaches and the combined
approach.Comment: 30 pages, 4 figure
Computation in Finitary Stochastic and Quantum Processes
We introduce stochastic and quantum finite-state transducers as
computation-theoretic models of classical stochastic and quantum finitary
processes. Formal process languages, representing the distribution over a
process's behaviors, are recognized and generated by suitable specializations.
We characterize and compare deterministic and nondeterministic versions,
summarizing their relative computational power in a hierarchy of finitary
process languages. Quantum finite-state transducers and generators are a first
step toward a computation-theoretic analysis of individual, repeatedly measured
quantum dynamical systems. They are explored via several physical systems,
including an iterated beam splitter, an atom in a magnetic field, and atoms in
an ion trap--a special case of which implements the Deutsch quantum algorithm.
We show that these systems' behaviors, and so their information processing
capacity, depends sensitively on the measurement protocol.Comment: 25 pages, 16 figures, 1 table; http://cse.ucdavis.edu/~cmg; numerous
corrections and update
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