6,087 research outputs found
Image Encryption Based on Diffusion and Multiple Chaotic Maps
In the recent world, security is a prime important issue, and encryption is
one of the best alternative way to ensure security. More over, there are many
image encryption schemes have been proposed, each one of them has its own
strength and weakness. This paper presents a new algorithm for the image
encryption/decryption scheme. This paper is devoted to provide a secured image
encryption technique using multiple chaotic based circular mapping. In this
paper, first, a pair of sub keys is given by using chaotic logistic maps.
Second, the image is encrypted using logistic map sub key and in its
transformation leads to diffusion process. Third, sub keys are generated by
four different chaotic maps. Based on the initial conditions, each map may
produce various random numbers from various orbits of the maps. Among those
random numbers, a particular number and from a particular orbit are selected as
a key for the encryption algorithm. Based on the key, a binary sequence is
generated to control the encryption algorithm. The input image of 2-D is
transformed into a 1- D array by using two different scanning pattern (raster
and Zigzag) and then divided into various sub blocks. Then the position
permutation and value permutation is applied to each binary matrix based on
multiple chaos maps. Finally the receiver uses the same sub keys to decrypt the
encrypted images. The salient features of the proposed image encryption method
are loss-less, good peak signal-to-noise ratio (PSNR), Symmetric key
encryption, less cross correlation, very large number of secret keys, and
key-dependent pixel value replacement.Comment: 14 pages,9 figures and 5 tables;
http://airccse.org/journal/jnsa11_current.html, 201
Bipartite Entanglement in Continuous-Variable Cluster States
We present a study of the entanglement properties of Gaussian cluster states,
proposed as a universal resource for continuous-variable quantum computing. A
central aim is to compare mathematically-idealized cluster states defined using
quadrature eigenstates, which have infinite squeezing and cannot exist in
nature, with Gaussian approximations which are experimentally accessible.
Adopting widely-used definitions, we first review the key concepts, by
analysing a process of teleportation along a continuous-variable quantum wire
in the language of matrix product states. Next we consider the bipartite
entanglement properties of the wire, providing analytic results. We proceed to
grid cluster states, which are universal for the qubit case. To extend our
analysis of the bipartite entanglement, we adopt the entropic-entanglement
width, a specialized entanglement measure introduced recently by Van den Nest M
et al., Phys. Rev. Lett. 97 150504 (2006), adapting their definition to the
continuous-variable context. Finally we add the effects of photonic loss,
extending our arguments to mixed states. Cumulatively our results point to key
differences in the properties of idealized and Gaussian cluster states. Even
modest loss rates are found to strongly limit the amount of entanglement. We
discuss the implications for the potential of continuous-variable analogues of
measurement-based quantum computation.Comment: 22 page
MDS Array Codes with Optimal Rebuilding
MDS array codes are widely used in storage systems
to protect data against erasures. We address the rebuilding ratio
problem, namely, in the case of erasures, what is the the fraction
of the remaining information that needs to be accessed in order
to rebuild exactly the lost information? It is clear that when the
number of erasures equals the maximum number of erasures
that an MDS code can correct then the rebuilding ratio is 1
(access all the remaining information). However, the interesting
(and more practical) case is when the number of erasures is
smaller than the erasure correcting capability of the code. For
example, consider an MDS code that can correct two erasures:
What is the smallest amount of information that one needs to
access in order to correct a single erasure? Previous work showed
that the rebuilding ratio is bounded between 1/2 and 3/4 , however,
the exact value was left as an open problem. In this paper, we
solve this open problem and prove that for the case of a single
erasure with a 2-erasure correcting code, the rebuilding ratio is
1/2 . In general, we construct a new family of r-erasure correcting
MDS array codes that has optimal rebuilding ratio of 1/r
in the
case of a single erasure. Our array codes have efficient encoding
and decoding algorithms (for the case r = 2 they use a finite field
of size 3) and an optimal update property
Revstack sort, zigzag patterns, descent polynomials of -revstack sortable permutations, and Steingr\'imsson's sorting conjecture
In this paper we examine the sorting operator . Applying
this operator to a permutation is equivalent to passing the permutation
reversed through a stack. We prove theorems that characterise -revstack
sortability in terms of patterns in a permutation that we call
patterns. Using these theorems we characterise those permutations of length
which are sorted by applications of for . We
derive expressions for the descent polynomials of these six classes of
permutations and use this information to prove Steingr\'imsson's sorting
conjecture for those six values of . Symmetry and unimodality of the descent
polynomials for general -revstack sortable permutations is also proven and
three conjectures are given
The Importance of Forgetting: Limiting Memory Improves Recovery of Topological Characteristics from Neural Data
We develop of a line of work initiated by Curto and Itskov towards
understanding the amount of information contained in the spike trains of
hippocampal place cells via topology considerations. Previously, it was
established that simply knowing which groups of place cells fire together in an
animal's hippocampus is sufficient to extract the global topology of the
animal's physical environment. We model a system where collections of place
cells group and ungroup according to short-term plasticity rules. In
particular, we obtain the surprising result that in experiments with spurious
firing, the accuracy of the extracted topological information decreases with
the persistence (beyond a certain regime) of the cell groups. This suggests
that synaptic transience, or forgetting, is a mechanism by which the brain
counteracts the effects of spurious place cell activity
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