759,307 research outputs found
Strong edge features for image coding
A two-component model is proposed for perceptual image coding. For the first component of the model, the watershed operator is used to detect strong edge features. Then, an efficient morphological interpolation algorithm reconstructs the smooth areas of the image from the extracted edge information, also known as sketch data. The residual component, containing fine textures, is separately coded by a subband coding scheme. The morphological operators involved in the coding of the primary component perform very efficiently compared to conventional techniques like the LGO operator, used for the edge extraction, or the diffusion filters, iteratively applied for the interpolation of smooth areas in previously reported sketch-based coding schemes.Peer ReviewedPostprint (published version
Strong Converse to the Quantum Channel Coding Theorem
A lower bound on the probability of decoding error of quantum communication
channel is presented. The strong converse to the quantum channel coding theorem
is shown immediately from the lower bound. It is the same as Arimoto's method
exept for the difficulty due to non-commutativity.Comment: LaTeX, 11 pages, submitted to IEEE Trans. Inform. Theor
On the Capacity of Symmetric Gaussian Interference Channels with Feedback
In this paper, we propose a new coding scheme for symmetric Gaussian
interference channels with feedback based on the ideas of time-varying coding
schemes. The proposed scheme improves the Suh-Tse and Kramer inner bounds of
the channel capacity for the cases of weak and not very strong interference.
This improvement is more significant when the signal-to-noise ratio (SNR) is
not very high. It is shown theoretically and numerically that our coding scheme
can outperform the Kramer code. In addition, the generalized degrees-of-freedom
of our proposed coding scheme is equal to the Suh-Tse scheme in the strong
interference case. The numerical results show that our coding scheme can attain
better performance than the Suh-Tse coding scheme for all channel parameters.
Furthermore, the simplicity of the encoding/decoding algorithms is another
strong point of our proposed coding scheme compared with the Suh-Tse coding
scheme. More importantly, our results show that an optimal coding scheme for
the symmetric Gaussian interference channels with feedback can be achieved by
using only marginal posterior distributions under a better cooperation strategy
between transmitters.Comment: To appear in Proc. of IEEE International Symposium on Information
Theory (ISIT), Hong Kong, June 14-19, 201
Coding Schemes for Achieving Strong Secrecy at Negligible Cost
We study the problem of achieving strong secrecy over wiretap channels at
negligible cost, in the sense of maintaining the overall communication rate of
the same channel without secrecy constraints. Specifically, we propose and
analyze two source-channel coding architectures, in which secrecy is achieved
by multiplexing public and confidential messages. In both cases, our main
contribution is to show that secrecy can be achieved without compromising
communication rate and by requiring only randomness of asymptotically vanishing
rate. Our first source-channel coding architecture relies on a modified wiretap
channel code, in which randomization is performed using the output of a source
code. In contrast, our second architecture relies on a standard wiretap code
combined with a modified source code termed uniform compression code, in which
a small shared secret seed is used to enhance the uniformity of the source code
output. We carry out a detailed analysis of uniform compression codes and
characterize the optimal size of the shared seed.Comment: 15 pages, two-column, 5 figures, accepted to IEEE Transactions on
Information Theor
A strong converse for classical channel coding using entangled inputs
A fully general strong converse for channel coding states that when the rate
of sending classical information exceeds the capacity of a quantum channel, the
probability of correctly decoding goes to zero exponentially in the number of
channel uses, even when we allow code states which are entangled across several
uses of the channel. Such a statement was previously only known for classical
channels and the quantum identity channel. By relating the problem to the
additivity of minimum output entropies, we show that a strong converse holds
for a large class of channels, including all unital qubit channels, the
d-dimensional depolarizing channel and the Werner-Holevo channel. This further
justifies the interpretation of the classical capacity as a sharp threshold for
information-transmission.Comment: 9 pages, revte
Empirical and Strong Coordination via Soft Covering with Polar Codes
We design polar codes for empirical coordination and strong coordination in
two-node networks. Our constructions hinge on the fact that polar codes enable
explicit low-complexity schemes for soft covering. We leverage this property to
propose explicit and low-complexity coding schemes that achieve the capacity
regions of both empirical coordination and strong coordination for sequences of
actions taking value in an alphabet of prime cardinality. Our results improve
previously known polar coding schemes, which (i) were restricted to uniform
distributions and to actions obtained via binary symmetric channels for strong
coordination, (ii) required a non-negligible amount of common randomness for
empirical coordination, and (iii) assumed that the simulation of discrete
memoryless channels could be perfectly implemented. As a by-product of our
results, we obtain a polar coding scheme that achieves channel resolvability
for an arbitrary discrete memoryless channel whose input alphabet has prime
cardinality.Comment: 14 pages, two-column, 5 figures, accepted to IEEE Transactions on
Information Theor
Connectivity reflects coding: A model of voltage-based spike-timing-dependent-plasticity with homeostasis
Electrophysiological connectivity patterns in cortex often show a few strong connections in a sea of weak connections. In some brain areas a large fraction of strong connections are bidirectional, in others they are mainly unidirectional. In order to explain these connectivity patterns, we use a model of Spike-Timing-Dependent Plasticity where synaptic changes depend on presynaptic spike arrival and the postsynaptic membrane potential. The model describes several nonlinear effects in STDP experiments, as well as the voltage dependence of plasticity under voltage clamp and classical paradigms of LTP/LTD induction. We show that in a simulated recurrent network of spiking neurons our plasticity rule leads not only to receptive field development, but also to connectivity patterns that reflect the neural code: for temporal coding paradigms strong connections are predominantly unidirectional, whereas they are bidirectional under rate coding. Thus variable connectivity patterns in the brain could reflect different coding principles across brain areas
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The threnoscope: a musical work for live coding performance
This paper introduces a new direction in the field of artistic live coding where musical works are presented as pieces in the form of a live coding system. The system itself and the code affordances become equivalent to score system in an open musical work for strong improvisation
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