ppxscal/embedding_network huggingface dataset:
Rich immersive sports experience: a hybrid multimedia system for content consumption
Authors: John Fawcett, Brian Beyer, Dan Hum, Aaron Ault, Jim Krogmeier, Cuneyt Taskiran
Venue: Proceedings of the 6th IEEE Conference on Consumer Communications and Networking Conference (2009)

Recent widespread use of multimedia-enabled devices has prompted the industry to look at systems which can provide a distributed, synchronized content consumption experience. Motorola has partnered with Purdue University's eStadium project to create the Rich Immersive Sports Experience (RISE) project. RISE is an attempt to design and develop such a system geared toward use in suites in Purdue's Ross-Ade football stadium. The core of the system is Motorola's Media Bundle technology that represents content and timing information for the TV screens and smart phones used in the system. This paper discusses the design process for the RISE system, how Media Bundles are used, and our solutions to issues of synchronization, speed, reliability, and scalability.
Information transfer by energy-efficient neurons
Authors: Toby Berger, William B. Levy
Venue: Proceedings of the 2009 IEEE international conference on Symposium on Information Theory - Volume 3 (2009)

We introduce and analyze a biologically motivated mathematical model of a neuron in primary cortex that we call neuron j, or just j- Our goal is to ascertain how j maximizes the ratio of the information it conveys to the energy it expends.
Capacity of a class of symmetric SIMO Gaussian interference channels within O(1)
Authors: Tiangao Gou, Syed A. Jafar
Venue: Proceedings of the 2009 IEEE international conference on Symposium on Information Theory - Volume 3 (2009)

The N+1 user, 1 × N single input multiple output (SIMO) Gaussian interference channel where each transmitter has a single antenna and each receiver has N antennas is studied. The symmetric capacity within O(1) is characterized for the symmetric case where all direct links have the same signal-to-noise ratio (SNR) and all undesired links have the same interference-to-noise ratio (INR). The gap to the exact capacity IS a constant which iS independent of SNR and INR. On the achievability side, an interesting conclusion is that the generalized degrees of freedom (GDOF) regime where treating interference as noise is found to be optimal in the 2 user interference channel, does not appear in the N + 1 user, 1 × N SIMO case. On the converse side, new multi-user outer bounds emerge out of this work that do not follow directly from the 2 user case. We also provide an outer bound on the capacity region of the 3 user SIMO Gaussian interference channel with 2 antennas at each receiver. This outer bound directly leads to the capacity region of this channel if the channel vectors satisfy certain conditions.
Binary erasure multiple descriptions: worst-case distortion
Authors: Ebad Ahmed, Aaron B. Wagne
Venue: Proceedings of the 2009 IEEE international conference on Symposium on Information Theory - Volume 1 (2009)

We consider a binary erasure version of the n- channel multiple descriptions problem with no excess rate and no distortion for every k out of n descriptions, i.e., any subset of k messages has a total rate of one and allows for perfect reconstruction of the source. Using a worst-case distortion criterion, we present an explicit coding scheme based on Reed-Solomon codes and, for any n and k, characterize its achievable distortion region when m < k messages are received at the decoder. We prove that this scheme is Pareto optimal in the achievable distortions for all n and k for any number of received messages at the decoder, and is optimal for all n and k when a single message is received. We also provide optimality results for a certain range of values of n and k.
On fidelity per unit cost
Authors: Marius Kleiner, Bixio Rimoldi
Venue: Proceedings of the 2009 IEEE international conference on Symposium on Information Theory - Volume 3 (2009)

We consider source coding with a fidelity criterion, channel coding with a channel input constraint, and the combined problem of reproducing a source across a noisy channel. All three cases face a similar tradeoff between resource and performance, and the operating point with the highest performance per resource is of particular interest. In the case of channel coding, channel input cost is traded for rate, and the optimal tradeoff corresponds to the capacity per unit cost. We define equivalent notions for the other two cases and show how they relate. For each case we give necessary and sufficient conditions for the optimal tradeoff to be achieved.
Channel ranking based joint symbols detection for MQRD-PCM/MIMO-OFDM
Authors: Chang-Jun Ahn
Venue: Proceedings of the 6th IEEE Conference on Consumer Communications and Networking Conference (2009)

MIMO-OFDM is considered a key technology in emerging high-data rate systems. With MIMO techniques, the transmission quality deteriorates due to co-channel interference (CCI). Several signal detection schemes have been proposed to mitigate this problem. However, it is impractical to use the conventional methods without reducing theirs computational complexity. Previously, we have proposed a parallel detection algorithm using multiple QR decompositions with permuted channel matrix (MQRD-PCM) for MIMO-OFDM to reduce the system complexity. This method achieves a good BER performance with low system complexity. However, since MQRD-PCM is a kind of parallel detection method, the wrong detection probability is increased due to the bad channel SINR of the transmitted signals. As a result, the average BER performance is influenced by the wrong detection probability of the bad channel SINR. To overcome this problem, in this paper, we propose the channel ranking based joint symbols detection for MQRD-PCM/MIMO-OFDM.
Structural annotation of EM images by graph cut
Authors: Hang Chang, Manfred Auer, Bahram Parvin
Venue: Proceedings of the Sixth IEEE international conference on Symposium on Biomedical Imaging: From Nano to Macro (2009)

Biological images have the potential to reveal complex signatures that may not be amenable to morphological modeling in terms of shape, location, texture, and color. An effective analytical method is to characterize the composition of a specimen based on user-defined patterns of texture and contrast formation. However, such a simple requirement demands an improved model for stability and robustness. Here, an interactive computational model is introduced for learning patterns of interest by example. The learned patterns bound an active contour model in which the traditional gradient descent optimization is replaced by the more efficient optimization of the graph cut methods. First, the energy function is defined according to the curve evolution. Next, a graph is constructed with weighted edges on the energy function and is optimized with the graph cut algorithm. As a result, the method combines the advantages of the level set method and graph cut algorithm, i.e., "topological" invariance and computational efficiency. The technique is extended to the multiphase segmentation problem; the method is validated on synthetic images and then applied to specimens imaged by transmission electron microscopy(TEM).
A new FFT concept for efficient VLSI implementation: part ii - parallel pipelined processing
Authors: Marwan A. Jaber, Daniel Massicotte
Venue: Proceedings of the 16th international conference on Digital Signal Processing (2009)

The success of computational science to accurately describe and model the real world has helped to fuel the ever increasing demand for cheap computing power. This paper presents a solution to the FFT's parallel multiprocessing problem, and involves novel concepts wherein the realization of parallel pipelines and multistage parallel pipelines are possible. The problem resides in defining the mathematical model of the so-called combination phase, in which the concept of representing the Discrete Fourier Transform (DFT) in terms of its partial DFTs should be well structured to obtain the right mathematical model. The resulting implementation in which r parallel processors operate simultaneously within a single instruction reduces the number of communications phases and the no-operation states (NOP) to their minimum values. The two papers, Part I and II, Butterfly Processing Element and Parallel Pipelined Processing, provide a new FFT concept for efficient VLSI implementation.
A new achievable rate for the Gaussian parallel relay channel
Authors: Seyed Saeed Changiz Rezaei, Shahab Oveis Gharan, Amir K. Khandani
Venue: Proceedings of the 2009 IEEE international conference on Symposium on Information Theory - Volume 1 (2009)

Schein and Gallager introduced the Gaussian parallel relay channel in 2000. They proposed the Amplify-and-Forward (AF) and the Decode-and-Forward (DF) strategies for this channel. For a long time, the best known achievable rate for this channel was based on the AF and DF with time sharing (AF-DF). Recently, a Rematch-and-Forward (RF) scheme for the scenario in which different amounts of bandwidth can be assigned to the first and second hops were proposed. In this paper, we propose a Combined Amplify-and-Decode Forward (CADF) scheme for the Gaussian parallel relay channel. We prove that the CADF scheme always gives a better achievable rate compared to the RF scheme, when there is a bandwidth mismatch between the first hop and the second hop. Furthermore, for the equal bandwidth case (Schein's setup), we show that the time sharing between the CADF and the DF schemes (CADF-DF) leads to a better achievable rate compared to the time sharing between the RF and the DF schemes (RF-DF) as well as the AF-DF.
Nonparametric spectral analysis with missing data via the EM algorithm
Authors: Yanwei Wang, Petre Stoica, Jian Li, Thomas L. Marzetta
Venue: Digital Signal Processing (2005)

We consider nonparametric complex spectral estimation of data sequences with missing samples occurring in arbitrary patterns. The existing spectral estimation algorithms designed for uniformly sampled complete-data sequences perform poorly when applied to data sequences with missing samples if the missing samples are simply set to zero. Several nonparametric algorithms have recently been developed to deal with the missing-data problem. They include, for example, GAPES for gapped data and PG-APES, PG-CAPON for periodically gapped data. However, they are not really suitable for the general missing-data problem where the missing data samples occur in arbitrary patterns. In this paper, we deal with a general missing-data spectral estimation problem for which we develop two nonparametric missing-data amplitude and phase estimation (MAPES) algorithms, both of which make use of the expectation maximization (EM) algorithm. Numerical results are provided to demonstrate the effectiveness of the proposed algorithms.
Bit rate maximization loading algorithm with mean BER-constraint for linear precoded OFDM
Authors: Fahad Syed Muhammad, Antoine Stephan, Jean-Yves Baudais, Jean-François Hélard
Venue: Proceedings of the 16th international conference on Telecommunications (2009)

The bit loading algorithms are proposed for orthogonal frequency division multiplexing (OFDM) and linear precoded OFDM under power spectral density and mean bit error rate (BER) constraints. These algorithms maximize the bit rate of the system while respecting a mean BER. The advantages of both linear procoded OFDM and classical OFDM are analyzed under different scenarios. It is shown that the proposed allocations perform better than the allocations under peak error rate constraint, while respecting a power spectral density constraint. The performance of the proposed algorithms is also better than the previously proposed algorithm under mean BER constraint. Moreover, it is observed that the algorithms for linear precoded OFDM under mean BER constraint have significantly lower computational complexity.
Algebraic network coding: a new perspective
Authors: K. R. Dinesh Kumar, Andrew Thangaraj
Venue: Proceedings of the 2009 IEEE international conference on Symposium on Information Theory - Volume 1 (2009)

Algebraic criteria for existence of scalar linear network codes to satisfy a set of connection requirements has been discussed extensively by Koetter and Médard, Solving for a network code is now known to be equivalent to solving a system of polynomial equations obtained by assigning variables to edges in the line graph of the network and computing a suitable transfer function. An alternative formulation for arriving at an equivalent system of polynomial equations is given in this paper based on the decomposition of the original network into trees, which we call "information flow trees". The basic idea is to exploit the graph structure and assign variables suitably. Interestingly, the information flow tree approach results in only linear and degree-2 equations that can be simplified considerably in directed acyclic networks as shown in prior work. In this article, we provide an alternative derivation of the information flow tree approach that results in two further extensions to networks with cycles. The first extension is to flow acyclic solutions on any directed cyclic network. The second extension is to cyclic networks where all strongly connected components are simple cycles. Here the degree of the equations we are left to solve is limited to 4.
Stochastic channel prioritization for spectrum sensing in cooperative cognitive radio
Authors: Xiaoyu Wang, Alexander Wong, Pin-Han Ho
Venue: Proceedings of the 6th IEEE Conference on Consumer Communications and Networking Conference (2009)

In this paper, a novel cooperative stochastic channel prioritization algorithm is presented for the purpose of improving spectrum sensing efficiency in cooperative cognitive radio systems. The proposed algorithm achieves the goal by prioritizing the channels for fine sensing based on both local statistics obtained by the cognitive radio as well as long-term spatiotemporal statistics obtained from other cognitive radios. Channel priority is determined in a stochastic manner by performing statistical fusion on the local statistics and statistics from neighboring cognitive radios to obtain a biasing density from which stochastic sampling can be used to identify the likelihood of channel availability. Therefore, the individual cognitive radios collaborate to improve the likelihood of each cognitive radio in obtaining available channels. Simulation results show that the proposed cooperative stochastic channel prioritization algorithm can be used to reduce both sensing overhead and percentage of missed opportunities when implemented in a complimentary manner with existing cooperative cognitive radio systems.
Reliable transfer of variable-length coded correlated date: an low complexity iterative joint source-channel decoding approach
Authors: Yang Yang, Weidong Yi, Yongrui Chen
Venue: Proceedings of the 6th IEEE Conference on Consumer Communications and Networking Conference (2009)

We propose a trellis-based soft-input-soft-output (SISO) a posteriori probability (APP) decoding technique for variable-length coded correlated sources. This technique allows not only the (ML) sequence estimation but also the computation of bit-based reliability values. The notable feature of the proposed technique is that its calculation complexity and memory space requirement are both low. Moreover, we bring the technique of scaling extrinsic information to the field of iterative joint source-channel decoding (ISCD), and obtain fixed scaling factors (SFs) based on the extrinsic information transfer (EXIT) charts analysis. This technique obviously improves the ISCD performance with increasing neglectable complexity. Simulation results show that the proposed ISCD scheme provides a significant improvement on error protection capability for the variable-length coded correlated sources.
Bayesian wavelet denoising and evolutionary calibration
Authors: Adelino R. Ferreira da Silva
Venue: Digital Signal Processing (2004)

Wavelet shrinkage estimation has become an attractive and efficient method for signal denoising and compression. Despite the ample variety of methods which have been used in the wavelet denoising context, it has proven elusive to construct threshold estimators with good adaptive properties. Recently, empirical Bayes selection criteria have been proposed to derive adaptive shrinkage estimators. We consider the application of empirical Bayes variable selection criteria to each level of the wavelet transform to obtain adaptive threshold estimates. A set of level-dependent hyperparameters has to be estimated to derive nonlinear data-dependent thresholding rules. We propose the use of an evolutionary algorithm to calibrate the multilevel parameters, in order to automate parameter selection and enhance adaptivity of the threshold estimators. Comparative simulations on a set of standard model functions show good performance. Applications to data drawn from various fields of application are used to explore the practical performance of the proposed approach.
Utility-based end-to-end flow control for services with time-varying rate requirements
Authors: Byung-Gook Kim, Jang-Won Lee
Venue: Proceedings of the 6th IEEE Conference on Consumer Communications and Networking Conference (2009)

In this paper, we study a utility based flow control problem for a communication network. In most previous works on utility based flow control, the utility function of each user, which represents its satisfaction to the allocated data rate, is assumed to be fixed. This implies that the degree of the rate requirement of each user is assumed to be fixed over the entire duration of its session. However, in the communication network, many services are variable rate services, i.e., the degree of their rate requirement varies over time. Hence, in this paper, we allow the degree of the rate requirement of each user to change over time and model it by using a stochastic utility function that varies stochastically according to the variation of the degree of its rate requirement. We formulate a stochastic optimization problem with stochastic utility functions that aims at maximizing the average network utility while satisfying the constraint on the link capacity. By solving the stochastic optimization problem, we develop a distributed flow control algorithm that converges to the optimal rate allocation.
An integrated 0.35µm CMOS technology inductor for wideband LNA application
Authors: M. Ben Amor, M. Loulou, S. Quintanel, D. Pasquet
Venue: Proceedings of the 16th international conference on Telecommunications (2009)

This paper presents the design of an integrated inductor with AMS CMOS 0.35µm technology. This inductor is designed to ensure the wide band LNA circuit implementation on silicon. This inductor is designed with a coplanar transmission line. This line type achieves an inductance value of 0.38nH on the whole operating frequency band from 2 to 6GHz.
Deformed statistics formulation of the information bottleneck method
Authors: R. C. Venkatesan, A. Plastina
Venue: Proceedings of the 2009 IEEE international conference on Symposium on Information Theory - Volume 2 (2009)

The theoretical basis for a candidate variational principle for the information bottleneck (IB) method is formulated within the ambit of the generalized nonadditive statistics of Tsallis. Given a nonadditivity parameter q, the role of the additive duality of nonadditive statistics (q* = 2 - q) in relating Tsallis entropies for ranges of the nonadditivity parameter q < 1 and q > 1 is described. Defining X, X, and Y to be the source alphabet, the compressed reproduction alphabet, and, the relevance variable respectively, it is demonstrated that minimization of a generalized IB (gIB) Lagrangian defined in terms of the nonadditivity parameter q* self-consistently yields the nonadditive effective distortion measure to be the q-deformed generalized Kullback-Leibler divergence: DK-Lq[p(Y|X)||p(Y|X)]. This result is achieved without enforcing any a-priori assumptions. Next, it is proven that the q*-deformed nonadditive free energy of the system is non-negative and convex. Finally, the update equations for the gIB method are derived. These results generalize critical features of the IB method to the case of Tsallis statistics.
Approximating the rate-distortion region of the distributed source coding for three jointly Gaussian tree-structured sources
Authors: Mohammad Ali Maddah-Ali, David N. C. Tse
Venue: Proceedings of the 2009 IEEE international conference on Symposium on Information Theory - Volume 3 (2009)

The rate-distortion region for the distributed source coding of the three jointly-Gaussian tree-structured sources with the quadratic distortion measure, is characterized within a constant gap. As a simplified counterpart of the Gaussian problem, we first investigate the rate region of a three binary-expanded sources where each pair of the sources have a certain number of the most-significant bits in common, and the central decoder needs to reconstruct each source with a target resolution. Motivated by the result of binary-expansion model, we prove that the achievable region of the quantize-and-binning scheme and the outer-bound of the cooperative scheme has a bounded gap of 2:4771 bits.
Enabling service aggregation for providers of consumer services and applications
Authors: Stanley Moyer, Peter Kriens
Venue: Proceedings of the 6th IEEE Conference on Consumer Communications and Networking Conference (2009)

The OSGi™ service platform is universal middleware for Java-based platforms that provides capabilities for enabling service providers to deploy consumer applications and services via various business models. This paper describes motivation and requirements for a service aggregation business model and describes how OSGi technology supports it.
An efficient bit-loading algorithm with peak BER constraint for the band-extended PLC
Authors: Ali Maiga, Jean-Yves Baudais, Jean-François Hélard
Venue: Proceedings of the 16th international conference on Telecommunications (2009)

Powerline communications (PLC) have become a viable local area network (LAN) solution for in-home networks. In order to achieve high bit rate over powerline, the current technology bandwidth is increased up to 100 MHz within the European project OMEGA. In this paper, an efficient bit-loading algorithm with peak BER constraint is proposed. This algorithm tries to maximize the overall data rate based on linear precoded discrete multitone (LP-DMT), which enables reliable high bit rate transmission. A fast computational algorithm with mean BER constraint is also proposed. Simulations are run over PLC channels and it is shown that peak BER constraint algorithm combined with linear precoding component gives better performance than mean BER constraint algorithm.
A new capacity upper bound for "relay-with-delay" channel
Authors: Amir Salimi, Mahtab Mirmohseni, Mohammad-Reza Aref
Venue: Proceedings of the 2009 IEEE international conference on Symposium on Information Theory - Volume 1 (2009)

In this paper we prove a new capacity upper bound for a class of relay channels known as Relay-With-Delay channels. The proposed bound is general and holds for any arbitrary amount of delay. We have shown that the previously introduced bounds can be considered as special cases of our proposed upper bound. The new introduced bound is, in some cases, tighter than the previously established bounds. It is also notable that the proposed bound coincides with the previously known capacity of "Relay-With-Delay" channels.