943 resultados para VARIABLE NEIGHBORHOOD RANDOM FIELDS


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We study the tradeoff between the average error probability and the average queueing delay of messages which randomly arrive to the transmitter of a point-to-point discrete memoryless channel that uses variable rate fixed codeword length random coding. Bounds to the exponential decay rate of the average error probability with average queueing delay in the regime of large average delay are obtained. Upper and lower bounds to the optimal average delay for a given average error probability constraint are presented. We then formulate a constrained Markov decision problem for characterizing the rate of transmission as a function of queue size given an average error probability constraint. Using a Lagrange multiplier the constrained Markov decision problem is then converted to a problem of minimizing the average cost for a Markov decision problem. A simple heuristic policy is proposed which approximately achieves the optimal average cost.

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Recently, Ebrahimi and Fragouli proposed an algorithm to construct scalar network codes using small fields (and vector network codes of small lengths) satisfying multicast constraints in a given single-source, acyclic network. The contribution of this paper is two fold. Primarily, we extend the scalar network coding algorithm of Ebrahimi and Fragouli (henceforth referred to as the EF algorithm) to block network-error correction. Existing construction algorithms of block network-error correcting codes require a rather large field size, which grows with the size of the network and the number of sinks, and thereby can be prohibitive in large networks. We give an algorithm which, starting from a given network-error correcting code, can obtain another network code using a small field, with the same error correcting capability as the original code. Our secondary contribution is to improve the EF Algorithm itself. The major step in the EF algorithm is to find a least degree irreducible polynomial which is coprime to another large degree polynomial. We suggest an alternate method to compute this coprime polynomial, which is faster than the brute force method in the work of Ebrahimi and Fragouli.

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Low-complexity near-optimal detection of signals in MIMO systems with large number (tens) of antennas is getting increased attention. In this paper, first, we propose a variant of Markov chain Monte Carlo (MCMC) algorithm which i) alleviates the stalling problem encountered in conventional MCMC algorithm at high SNRs, and ii) achieves near-optimal performance for large number of antennas (e.g., 16×16, 32×32, 64×64 MIMO) with 4-QAM. We call this proposed algorithm as randomized MCMC (R-MCMC) algorithm. Second, we propose an other algorithm based on a random selection approach to choose candidate vectors to be tested in a local neighborhood search. This algorithm, which we call as randomized search (RS) algorithm, also achieves near-optimal performance for large number of antennas with 4-QAM. The complexities of the proposed R-MCMC and RS algorithms are quadratic/sub-quadratic in number of transmit antennas, which are attractive for detection in large-MIMO systems. We also propose message passing aided R-MCMC and RS algorithms, which are shown to perform well for higher-order QAM.

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The gross characteristics of spatio-temporal current evolution in the return stroke phase of a cloud-to-ground lightning are rather well defined. However, they by themselves do not ensure the salient features for the resulting remote Electro- Magnetic Fields (EMFs). In spite of significant efforts in the engineering models wherein, the spatio-temporal current distribution all along the channel is specified by the design, all the salient features of remote EMFs could not be achieved. Only the current evolution that ensures the basic characteristics along with its ability to reproduce all the salient features of remote EMFs ranging from 50 m – 200 km from the lightning channel, can be considered as a realistic return stroke channel current. In view of this, the present work intends to investigate on the required fine features of the return stroke current evolution that yields all the desired features. To ensure that the current evolution is not arbitrary but obeys the involved basic physical processes, a recently developed physical model will be employed for the analysis.

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Effective conservation and management of natural resources requires up-to-date information of the land cover (LC) types and their dynamics. The LC dynamics are being captured using multi-resolution remote sensing (RS) data with appropriate classification strategies. RS data with important environmental layers (either remotely acquired or derived from ground measurements) would however be more effective in addressing LC dynamics and associated changes. These ancillary layers provide additional information for delineating LC classes' decision boundaries compared to the conventional classification techniques. This communication ascertains the possibility of improved classification accuracy of RS data with ancillary and derived geographical layers such as vegetation index, temperature, digital elevation model (DEM), aspect, slope and texture. This has been implemented in three terrains of varying topography. The study would help in the selection of appropriate ancillary data depending on the terrain for better classified information.

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A network of ship-mounted real-time Automatic Weather Stations integrated with Indian geosynchronous satellites Indian National Satellites (INSATs)] 3A and 3C, named Indian National Centre for Ocean Information Services Real-Time Automatic Weather Stations (I-RAWS), is established. The purpose of I-RAWS is to measure the surface meteorological-ocean parameters and transmit the data in real time in order to validate and refine the forcing parameters (obtained from different meteorological agencies) of the Indian Ocean Forecasting System (INDOFOS). Preliminary validation and intercomparison of analyzed products obtained from the National Centre for Medium Range Weather Forecasting and the European Centre for Medium-Range Weather Forecasts using the data collected from I-RAWS were carried out. This I-RAWS was mounted on board oceanographic research vessel Sagar Nidhi during a cruise across three oceanic regimes, namely, the tropical Indian Ocean, the extratropical Indian Ocean, and the Southern Ocean. The results obtained from such a validation and intercomparison, and its implications with special reference to the usage of atmospheric model data for forcing ocean model, are discussed in detail. It is noticed that the performance of analysis products from both atmospheric models is similar and good; however, European Centre for Medium-Range Weather Forecasts air temperature over the extratropical Indian Ocean and wind speed in the Southern Ocean are marginally better.

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In this paper we present a hardware-software hybrid technique for modular multiplication over large binary fields. The technique involves application of Karatsuba-Ofman algorithm for polynomial multiplication and a novel technique for reduction. The proposed reduction technique is based on the popular repeated multiplication technique and Barrett reduction. We propose a new design of a parallel polynomial multiplier that serves as a hardware accelerator for large field multiplications. We show that the proposed reduction technique, accelerated using the modified polynomial multiplier, achieves significantly higher performance compared to a purely software technique and other hybrid techniques. We also show that the hybrid accelerated approach to modular field multiplication is significantly faster than the Montgomery algorithm based integrated multiplication approach.

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We studied the development of surface instabilities leading to the generation of multielectron bubbles (MEBs) in superfluid helium upon the application of a pulsed electric field. We found the statistical distribution of the charge of individual instabilities to be strongly dependent on the duration of the electric field pulse. The rate and probability of generation of these instabilities in relation to the temporal characteristics of the applied field was also investigated.

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Mobile ad-hoc network is a wireless ad-hoc network with dynamic network topology. The Dynamicity, due to the random node movement, and scarcity of resources lead to a challenge in monitoring the nodes in a MANET. Monitoring the lack of resources (bandwidth, buffer, and energy), misbehavior, and mobility at node level remains, a challenge. In a MANET the proposed protocol uses both static as well as mobile agents, where the mobile agents migrate to different clusters of the zones respectively, collect the node status information periodically, and provide a high level information to the static agent (which resides at the central node) by analyzing the raw information at the nodes. This, in turn, reduces the network traffic and conserves the workload of the central node, where a static agent is available with high level information and in coordination with other modules. The protocol has been tested in different size MANETs with variable number of nodes and applications. The results shown in the simulation indicates the effectiveness of the protocol.

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In the Indian Ocean, mid-depth oxygen minimum zones (OMZs) occur in the Arabian Sea and the Bay of Bengal. The lower part of the Arabian-Sea OMZ (ASOMZ; below 400 m) intensifies northward across the basin; in contrast, its upper part (above 400 m) is located in the central/eastern basin, well east of the most productive regions along the western boundary. The Bay-of-Bengal OMZ (BBOMZ), although strong, is weaker than the ASOMZ. To investigate the processes that maintain the Indian-Ocean OMZs, we obtain a suite of solutions to a coupled biological/physical model. Its physical component is a variable-density, 6 1/2-layer model, in which each layer corresponds to a distinct dynamical regime or water-mass type. Its biological component has six compartments: nutrients, phytoplankton, zooplankton, two size classes of detritus, and oxygen. Because the model grid is non-eddy resolving (0.5 degrees), the biological model also includes a parameterization of enhanced mixing based on the eddy kinetic energy derived from satellite observations. To explore further the impact of local processes on OMZs, we also obtain analytic solutions to a one-dimensional, simplified version of the biological model. Our control run is able to simulate basic features of the oxygen, nutrient, and phytoplankton fields throughout the Indian Ocean. The model OMZs result from a balance, or lack thereof, between a sink of oxygen by remineralization and subsurface oxygen sources due primarily to northward spreading of oxygenated water from the Southern Hemisphere, with a contribution from Persian-Gulf water in the northern Arabian Sea. The northward intensification of the lower ASOMZ results mostly from horizontal mixing since advection is weak in its depth range. The eastward shift of the upper ASOMZ is due primarily to enhanced advection and vertical eddy mixing in the western Arabian Sea, which spread oxygenated waters both horizontally and vertically. Advection carries small detritus from the western boundary into the central/eastern Arabian Sea, where it provides an additional source of remineralization that drives the ASOMZ to suboxic levels. The model BBOMZ is weaker than the ASOMZ because the Bay lacks a remote source of detritus from the western boundary. Although detritus has a prominent annual cycle, the model OMZs do not because there is not enough time for significant remineralization to occur.

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The random eigenvalue problem arises in frequency and mode shape determination for a linear system with uncertainties in structural properties. Among several methods of characterizing this random eigenvalue problem, one computationally fast method that gives good accuracy is a weak formulation using polynomial chaos expansion (PCE). In this method, the eigenvalues and eigenvectors are expanded in PCE, and the residual is minimized by a Galerkin projection. The goals of the current work are (i) to implement this PCE-characterized random eigenvalue problem in the dynamic response calculation under random loading and (ii) to explore the computational advantages and challenges. In the proposed method, the response quantities are also expressed in PCE followed by a Galerkin projection. A numerical comparison with a perturbation method and the Monte Carlo simulation shows that when the loading has a random amplitude but deterministic frequency content, the proposed method gives more accurate results than a first-order perturbation method and a comparable accuracy as the Monte Carlo simulation in a lower computational time. However, as the frequency content of the loading becomes random, or for general random process loadings, the method loses its accuracy and computational efficiency. Issues in implementation, limitations, and further challenges are also addressed.

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We present in this paper, approximate analytical expressions for the intensity of light scattered by a rough surface, whose elevation. xi(x,y) in the z-direction is a zero mean stationary Gaussian random variable. With (x,y) and (x',y') being two points on the surface, we have h. = 0 with a correlation, = sigma(2)g(r), where r = (x - x')(2) + ( y - y')(2)](1/2) is the distance between these two points. We consider g(r) = exp-r/l)(beta)] with 1 <= beta <= 2, showing that g(0) = 1 and g(r) -> 0 for r >> l. The intensity expression is sought to be expressed as f(v(xy)) = {1 + (c/2y)v(x)(2) + v(y)(2)]}(-y), where v(x) and v(y) are the wave vectors of scattering, as defined by the Beckmann notation. In the paper, we present expressions for c and y, in terms of sigma, l, and beta. The closed form expressions are verified to be true, for the cases beta = 1 and beta = 2, for which exact expressions are known. For other cases, i.e., beta not equal 1, 2 we present approximate expressions for the scattered intensity, in the range, v(xy) = (v(x)(2) + v(y)(2))(1/2) <= 6.0 and show that the relation for f(v(xy)), given above, expresses the scattered intensity quite accurately, thus providing a simple computational methods in situations of practical importance.

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Recent experiments on fermions in synthetic gauge fields result in systems with a spin-orbit coupling along one spatial axis, a detuning field, and a Zeeman field. We show theoretically that the presence of all three results in interesting and unusual phenomena in a system of interacting fermions (interactions described by a scattering length). For two fermions, bound states appear only over a certain range of the center-of-mass momenta. The deepest bound state appears at a nonzero center-of-mass momentum. For center-of-mass momenta without a bound state, the gauge field induces a resonance-like feature in the scattering continuum resulting in a large scattering phase shift. In the case of many particles, we demonstrate that the system, in a parameter range, shows flow-enhanced pairing, i.e., a Fulde-Farrell-Larkin-Ovchnnikov superfluid state made of robust pairs with a finite center-of-mass momentum. Yet another regime of parameters offers the opportunity to study strongly interacting normal states of spin-orbit-coupled fermionic systems utilizing the resonance-like feature induced by the synthetic gauge field.