412 resultados para QUANTIZATION


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In this thesis, the possibility of extending the Quantization Condition of Dirac for Magnetic Monopoles to noncommutative space-time is investigated. The three publications that this thesis is based on are all in direct link to this investigation. Noncommutative solitons have been found within certain noncommutative field theories, but it is not known whether they possesses only topological charge or also magnetic charge. This is a consequence of that the noncommutative topological charge need not coincide with the noncommutative magnetic charge, although they are equivalent in the commutative context. The aim of this work is to begin to fill this gap of knowledge. The method of investigation is perturbative and leaves open the question of whether a nonperturbative source for the magnetic monopole can be constructed, although some aspects of such a generalization are indicated. The main result is that while the noncommutative Aharonov-Bohm effect can be formulated in a gauge invariant way, the quantization condition of Dirac is not satisfied in the case of a perturbative source for the point-like magnetic monopole.

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In this thesis the current status and some open problems of noncommutative quantum field theory are reviewed. The introduction aims to put these theories in their proper context as a part of the larger program to model the properties of quantized space-time. Throughout the thesis, special focus is put on the role of noncommutative time and how its nonlocal nature presents us with problems. Applications in scalar field theories as well as in gauge field theories are presented. The infinite nonlocality of space-time introduced by the noncommutative coordinate operators leads to interesting structure and new physics. High energy and low energy scales are mixed, causality and unitarity are threatened and in gauge theory the tools for model building are drastically reduced. As a case study in noncommutative gauge theory, the Dirac quantization condition of magnetic monopoles is examined with the conclusion that, at least in perturbation theory, it cannot be fulfilled in noncommutative space.

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We investigate the Nernst effect in a mesoscopic two-dimensional electron system (2DES) at low magnetic fields, before the onset of Landau level quantization. The overall magnitude of the Nernst signal agrees well with semiclassical predictions. We observe reproducible mesoscopic fluctuations in the signal that diminish significantly with an increase in temperature. We also show that the Nernst effect exhibits an anomalous component that is correlated with an oscillatory Hall effect. This behavior may be able to distinguish between different spin-correlated states in the 2DES.

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Large external memory bandwidth requirement leads to increased system power dissipation and cost in video coding application. Majority of the external memory traffic in video encoder is due to reference data accesses. We describe a lossy reference frame compression technique that can be used in video coding with minimal impact on quality while significantly reducing power and bandwidth requirement. The low cost transformless compression technique uses lossy reference for motion estimation to reduce memory traffic, and lossless reference for motion compensation (MC) to avoid drift. Thus, it is compatible with all existing video standards. We calculate the quantization error bound and show that by storing quantization error separately, bandwidth overhead due to MC can be reduced significantly. The technique meets key requirements specific to the video encode application. 24-39% reduction in peak bandwidth and 23-31% reduction in total average power consumption are observed for IBBP sequences.

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The problem of sensor-network-based distributed intrusion detection in the presence of clutter is considered. It is argued that sensing is best regarded as a local phenomenon in that only sensors in the immediate vicinity of an intruder are triggered. In such a setting, lack of knowledge of intruder location gives rise to correlated sensor readings. A signal-space view-point is introduced in which the noise-free sensor readings associated to intruder and clutter appear as surfaces f(s) and f(g) and the problem reduces to one of determining in distributed fashion, whether the current noisy sensor reading is best classified as intruder or clutter. Two approaches to distributed detection are pursued. In the first, a decision surface separating f(s) and f(g) is identified using Neyman-Pearson criteria. Thereafter, the individual sensor nodes interactively exchange bits to determine whether the sensor readings are on one side or the other of the decision surface. Bounds on the number of bits needed to be exchanged are derived, based on communication-complexity (CC) theory. A lower bound derived for the two-party average case CC of general functions is compared against the performance of a greedy algorithm. Extensions to the multi-party case is straightforward and is briefly discussed. The average case CC of the relevant greaterthan (CT) function is characterized within two bits. Under the second approach, each sensor node broadcasts a single bit arising from appropriate two-level quantization of its own sensor reading, keeping in mind the fusion rule to be subsequently applied at a local fusion center. The optimality of a threshold test as a quantization rule is proved under simplifying assumptions. Finally, results from a QualNet simulation of the algorithms are presented that include intruder tracking using a naive polynomial-regression algorithm. 2010 Elsevier B.V. All rights reserved.

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We develop a Gaussian mixture model (GMM) based vector quantization (VQ) method for coding wideband speech line spectrum frequency (LSF) parameters at low complexity. The PDF of LSF source vector is modeled using the Gaussian mixture (GM) density with higher number of uncorrelated Gaussian mixtures and an optimum scalar quantizer (SQ) is designed for each Gaussian mixture. The reduction of quantization complexity is achieved using the relevant subset of available optimum SQs. For an input vector, the subset of quantizers is chosen using nearest neighbor criteria. The developed method is compared with the recent VQ methods and shown to provide high quality rate-distortion (R/D) performance at lower complexity. In addition, the developed method also provides the advantages of bitrate scalability and rate-independent complexity.

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The resolution of the digital signal path has a crucial impact on the design, performance and the power dissipation of the radio receiver data path, downstream from the ADC. The ADC quantization noise has been traditionally included with the Front End receiver noise in calculating the SNR as well as BER for the receiver. Using the IEEE 802.15.4 as an example, we show that this approach leads to an over-design for the ADC and the digital signal path, resulting in larger power. More accurate specifications for the front-end design can be obtained by making SNRreg a function of signal resolutions. We show that lower resolution signals provide adequate performance and quantization noise alone does not produce any bit-error. We find that a tight bandpass filter preceding the ADC can relax the resolution requirement and a 1-bit ADC degrades SNR by only 1.35 dB compared to 8-bit ADC. Signal resolution has a larger impact on the synchronization and a 1-bit ADC costs about 5 dB in SNR to maintain the same level of performance as a 8-bit ADC.

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We propose the design and implementation of hardware architecture for spatial prediction based image compression scheme, which consists of prediction phase and quantization phase. In prediction phase, the hierarchical tree structure obtained from the test image is used to predict every central pixel of an image by its four neighboring pixels. The prediction scheme generates an error image, to which the wavelet/sub-band coding algorithm can be applied to obtain efficient compression. The software model is tested for its performance in terms of entropy, standard deviation. The memory and silicon area constraints play a vital role in the realization of the hardware for hand-held devices. The hardware architecture is constructed for the proposed scheme, which involves the aspects of parallelism in instructions and data. The processor consists of pipelined functional units to obtain the maximum throughput and higher speed of operation. The hardware model is analyzed for performance in terms throughput, speed and power. The results of hardware model indicate that the proposed architecture is suitable for power constrained implementations with higher data rate

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In this paper, we consider robust joint designs of relay precoder and destination receive filters in a nonregenerative multiple-input multiple-output (MIMO) relay network. The network consists of multiple source-destination node pairs assisted by a MIMO-relay node. The channel state information (CSI) available at the relay node is assumed to be imperfect. We consider robust designs for two models of CSI error. The first model is a stochastic error (SE) model, where the probability distribution of the CSI error is Gaussian. This model is applicable when the imperfect CSI is mainly due to errors in channel estimation. For this model, we propose robust minimum sum mean square error (SMSE), MSE-balancing, and relay transmit power minimizing precoder designs. The next model for the CSI error is a norm-bounded error (NBE) model, where the CSI error can be specified by an uncertainty set. This model is applicable when the CSI error is dominated by quantization errors. In this case, we adopt a worst-case design approach. For this model, we propose a robust precoder design that minimizes total relay transmit power under constraints on MSEs at the destination nodes. We show that the proposed robust design problems can be reformulated as convex optimization problems that can be solved efficiently using interior-point methods. We demonstrate the robust performance of the proposed design through simulations.

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We present a simplified theoretical formulation of the Fowler-Nordheim field emission (FNFE) under magnetic quantization and also in quantum wires of optoelectronic materials on the basis of a newly formulated electron dispersion law in the presence of strong electric field within the framework of k.p formalism taking InAs, InSb, GaAs, Hg(1-x)Cd(x)Te and In(1-x)Ga(x) As(y)P(1-y) lattice matched to InP as examples. The FNFE exhibits oscillations with inverse quantizing magnetic field and electron concentration due to SdH effect and increases with increasing electric field. For quantum wires the FNFE increases with increasing film thickness due to the existence van-Hove singularity and the magnitude of the quantum jumps are not of same height indicating the signature of the band structure of the material concerned. The appearance of the humps of the respective curves is due to the redistribution of the electrons among the quantized energy levels when the quantum numbers corresponding to the highest occupied level changes from one fixed value to the others. Although the field current varies in various manners with all the variables in all the limiting cases as evident from all the curves, the rates of variations are totally band-structure dependent. Under certain limiting conditions, all the results as derived in this paper get transformed in to well known Fowler-Nordheim formula. (C) 2011 Elsevier Ltd. All rights reserved.

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In this paper, we address the design of codes which achieve modulation diversity in block fading single-input single-output (SISO) channels with signal quantization at the receiver. With an unquantized receiver, coding based on algebraic rotations is known to achieve maximum modulation coding diversity. On the other hand, with a quantized receiver, algebraic rotations may not guarantee gains in diversity. Through analysis, we propose specific rotations which result in the codewords having equidistant component-wise projections. We show that the proposed coding scheme achieves maximum modulation diversity with a low-complexity minimum distance decoder and perfect channel knowledge. Relaxing the perfect channel knowledge assumption we propose a novel channel training/estimation technique to estimate the channel. We show that our coding/training/estimation scheme and minimum distance decoding achieves an error probability performance similar to that achieved with perfect channel knowledge.

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The photoemission from quantum wires and dots of effective mass superlattices of optoelectronic materials was investigated on the basis of newly formulated electron energy spectra, in the presence of external light waves, which controls the transport properties of ultra-small electronic devices under intense radiation. The effect of magnetic quantization on the photoemission from the aforementioned superlattices, together with quantum well superlattices under magnetic quantization, has also been investigated in this regard. It appears, taking HgTe/Hg1-xCdxTe and InxGa1-xAs/InP effective mass superlattices, that the photoemission from these quantized structures is enhanced with increasing photon energy in quantized steps and shows oscillatory dependences with the increasing carrier concentration. In addition, the photoemission decreases with increasing light intensity and wavelength as well as with increasing thickness exhibiting oscillatory spikes. The strong dependence of the photoemission on the light intensity reflects the direct signature of light waves on the carrier energy spectra. The content of this paper finds six different applications in the fields of low dimensional systems in general.

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This paper presents the design and performance analysis of a detector based on suprathreshold stochastic resonance (SSR) for the detection of deterministic signals in heavy-tailed non-Gaussian noise. The detector consists of a matched filter preceded by an SSR system which acts as a preprocessor. The SSR system is composed of an array of 2-level quantizers with independent and identically distributed (i.i.d) noise added to the input of each quantizer. The standard deviation sigma of quantizer noise is chosen to maximize the detection probability for a given false alarm probability. In the case of a weak signal, the optimum sigma also minimizes the mean-square difference between the output of the quantizer array and the output of the nonlinear transformation of the locally optimum detector. The optimum sigma depends only on the probability density functions (pdfs) of input noise and quantizer noise for weak signals, and also on the signal amplitude and the false alarm probability for non-weak signals. Improvement in detector performance stems primarily from quantization and to a lesser extent from the optimization of quantizer noise. For most input noise pdfs, the performance of the SSR detector is very close to that of the optimum detector. (C) 2012 Elsevier B.V. All rights reserved.

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In recent years a number of white dwarfs have been observed with very high surface magnetic fields. We can expect that the magnetic field in the core of these stars would be much higher (similar to 10(14) G). In this paper, we analytically study the effect of high magnetic field on relativistic cold electron, and hence its effect on the stability and the mass-radius relation of a magnetic white dwarf. In strong magnetic fields, the equation of state of the Fermi gas is modified and Landau quantization comes into play. For relatively very high magnetic fields (with respect to the average energy density of matter) the number of Landau levels is restricted to one or two. We analyze the equation of states for magnetized electron degenerate gas analytically and attempt to understand the conditions in which transitions from the zeroth Landau level to first Landau level occurs. We also find the effect of the strong magnetic field on the star collapsing to a white dwarf, and the mass-radius relation of the resulting star. We obtain an interesting theoretical result that it is possible to have white dwarfs with mass more than the mass set by Chandrasekhar limit.

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We consider a relativistic, degenerate electron gas at zero temperature under the influence of a strong, uniform, static magnetic field, neglecting any form of interactions. Since the density of states for the electrons changes due to the presence of the magnetic field (which gives rise to Landau quantization), the corresponding equation of state also gets modified. In order to investigate the effect of very strong magnetic field, we focus only on systems in which a maximum of either one, two, or three Landau level(s) is/are occupied. This is important since, if a very large number of Landau levels are filled, it implies a very low magnetic field strength which yields back Chandrasekhar's celebrated nonmagnetic results. The maximum number of occupied Landau levels is fixed by the correct choice of two parameters, namely, the magnetic field strength and the maximum Fermi energy of the system. We study the equations of state of these one-level, two-level, and three-level systems and compare them by taking three different maximum Fermi energies. We also find the effect of the strong magnetic field on the mass-radius relation of the underlying star composed of the gas stated above. We obtain an exciting result that it is possible to have an electron-degenerate static star, namely, magnetized white dwarfs, with a mass significantly greater than the Chandrasekhar limit in the range 2.3-2.6M(circle dot), provided it has an appropriate magnetic field strength and central density. In fact, recent observations of peculiar type Ia supernovae-SN 2006gz, SN 2007if, SN 2009dc, SN 2003fg-seem to suggest super-Chandrasekhar-mass white dwarfs with masses up to 2.4-2.8M(circle dot) as their most likely progenitors. Interestingly, our results seem to lie within these observational limits.