172 resultados para Quasi-periodic sequences


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A three-level inverter produces six active vectors, each of normalized magnitudes 1, 0.866, and 0.5, besides a zero vector. The vectors of relative length 0.5 are termed pivot vectors.The three nearest voltage vectors are usually used to synthesize the reference vector. In most continuous pulsewidth-modulation(PWM) schemes, the switching sequence begins from a pivot vector and ends with the same pivot vector. Thus, the pivot vector is applied twice in a subcycle or half-carrier cycle. This paper proposes and investigates alternative switching sequences, which use the pivot vector only once but employ one of the other two vectors twice within the subcycle. The total harmonic distortion(THD) in the fundamental line current pertaining to these novel sequences is studied theoretically as well as experimentally over the whole range of modulation. Compared with centered space vector PWM, two of the proposed sequences lead to reduced THD at high modulation indices at a given average switching frequency.

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This paper deals with surface profilometry, where we try to detect a periodic structure, hidden in randomness using the matched filter method of analysing the intensity of light, scattered from the surface. From the direct problem of light scattering from a composite rough surface of the above type, we find that the detectability of the periodic structure can be hindered by the randomness, being dependent on the correlation function of the random part. In our earlier works, we had concentrated mainly on the Cauchy-type correlation function for the rough part. In the present work, we show that this technique can determine the periodic structure of different kinds of correlation functions of the roughness, including Cauchy, Gaussian etc. We study the detection by the matched filter method as the nature of the correlation function is varied.

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Superscalar processors currently have the potential to fetch multiple basic blocks per cycle by employing one of several recently proposed instruction fetch mechanisms. However, this increased fetch bandwidth cannot be exploited unless pipeline stages further downstream correspondingly improve. In particular,register renaming a large number of instructions per cycle is diDcult. A large instruction window, needed to receive multiple basic blocks per cycle, will slow down dependence resolution and instruction issue. This paper addresses these and related issues by proposing (i) partitioning of the instruction window into multiple blocks, each holding a dynamic code sequence; (ii) logical partitioning of the registerjle into a global file and several local jles, the latter holding registers local to a dynamic code sequence; (iii) the dynamic recording and reuse of register renaming information for registers local to a dynamic code sequence. Performance studies show these mechanisms improve performance over traditional superscalar processors by factors ranging from 1.5 to a little over 3 for the SPEC Integer programs. Next, it is observed that several of the loops in the benchmarks display vector-like behavior during execution, even if the static loop bodies are likely complex for compile-time vectorization. A dynamic loop vectorization mechanism that builds on top of the above mechanisms is briefly outlined. The mechanism vectorizes up to 60% of the dynamic instructions for some programs, albeit the average number of iterations per loop is quite small.

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We show that a fluid under strong spatially periodic confinement displays a glass transition within mode-coupling theory at a much lower density than the corresponding bulk system. We use fluctuating hydrodynamics, with confinement imposed through a periodic potential whose wavelength plays an important role in our treatment. To make the calculation tractable we implement a detailed calculation in one dimension. Although we do not expect simple 1d fluids to show a glass transition, our results are indicative of the behavior expected in higher dimensions. In a certain region of parameter space we observe a three-step relaxation reported recently in computer simulations [S. H. Krishnan, Ph.D. thesis, Indian Institute of Science (2005); Kim et al., Eur. Phys. J. Special Topics 189, 135 (2010)] and a glass-glass transition. We compare our results to those of Krakoviack [Phys. Rev. E 75, 031503 (2007)] and Lang et al. [Phys. Rev. Lett. 105, 125701 (2010)].

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Ultrasonic C-Scan is used very often to detect flaws and defects in the composite components resulted during fabrication and damages resulting from service conditions. Evaluation and characterization of defects and damages of composites require experience and good understanding of the material as they are distinctly different in composition and behavior as compared to conventional metallic materials. The failure mechanisms in composite materials are quite complex. They involve the interaction of matrix cracking, fiber matrix interface debonding, fiber pullout, fiber fracture and delamination. Generally all of them occur making the stress and failure analysis very complex. Under low-velocity impact loading delamination is observed to be a major failure mode. In composite materials the ultrasonic waves suffer high acoustic attenuation and scattering effect, thus making data interpretation difficult. However these difficulties can be overcome to a greater extent by proper selection of probe, probe parameter settings like pulse width, pulse amplitude, pulse repetition rate, delay, blanking, gain etc., and data processing which includes image processing done on the image obtained by the C-Scan.

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The effect of scaling (1 μm to 0.09 μm) on the non-quasi-static (NQS) behaviour of the MOSFET has been studied using process and device simulation. It is shown that under fixed gate (Vgs) and drain (Vds) bias voltages, the NQS transition frequency (fNQS) scales as 1/Leff rather than 1/L2eff due to the velocity saturation effect. However, under the practical scaling guidelines, considering the scaling of supply voltage as well, fNQS shows a turn around effect at the sub 100 nm regime. The relation between unity gain frequency (ft) and fNQS is also evaluated and it is shown that ft and fNQS have similar trends with scaling.

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In this paper we consider the process of discovering frequent episodes in event sequences. The most computationally intensive part of this process is that of counting the frequencies of a set of candidate episodes. We present two new frequency counting algorithms for speeding up this part. These, referred to as non-overlapping and non-inteleaved frequency counts, are based on directly counting suitable subsets of the occurrences of an episode. Hence they are different from the frequency counts of Mannila et al [1], where they count the number of windows in which the episode occurs. Our new frequency counts offer a speed-up factor of 7 or more on real and synthetic datasets. We also show how the new frequency counts can be used when the events in episodes have time-durations as well.

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Discovering patterns in temporal data is an important task in Data Mining. A successful method for this was proposed by Mannila et al. [1] in 1997. In their framework, mining for temporal patterns in a database of sequences of events is done by discovering the so called frequent episodes. These episodes characterize interesting collections of events occurring relatively close to each other in some partial order. However, in this framework(and in many others for finding patterns in event sequences), the ordering of events in an event sequence is the only allowed temporal information. But there are many applications where the events are not instantaneous; they have time durations. Interesting episodesthat we want to discover may need to contain information regarding event durations etc. In this paper we extend Mannila et al.’s framework to tackle such issues. In our generalized formulation, episodes are defined so that much more temporal information about events can be incorporated into the structure of an episode. This significantly enhances the expressive capability of the rules that can be discovered in the frequent episode framework. We also present algorithms for discovering such generalized frequent episodes.

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We study the quenching dynamics of a many-body system in one dimension described by a Hamiltonian that has spatial periodicity. Specifically, we consider a spin-1/2 chain with equal xx and yy couplings and subject to a periodically varying magnetic field in the (z) over cap direction or, equivalently, a tight-binding model of spinless fermions with a periodic local chemical potential, having period 2q, where q is a positive integer. For a linear quench of the strength of the magnetic field (or chemical potential) at a rate 1/tau across a quantum critical point, we find that the density of defects thereby produced scales as 1/tau(q/(q+1)), deviating from the 1/root tau scaling that is ubiquitous in a range of systems. We analyze this behavior by mapping the low-energy physics of the system to a set of fermionic two-level systems labeled by the lattice momentum k undergoing a nonlinear quench as well as by performing numerical simulations. We also show that if the magnetic field is a superposition of different periods, the power law depends only on the smallest period for very large values of tau, although it may exhibit a crossover at intermediate values of tau. Finally, for the case where a zz coupling is also present in the spin chain, or equivalently, where interactions are present in the fermionic system, we argue that the power associated with the scaling law depends on a combination of q and the interaction strength.

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In this work, the effects of loading rate, material rate sensitivity and constraint level on quasi-static crack tip fields in a FCC single crystal are studied. Finite element simulations are performed within a mode I, plane strain modified boundary layer framework by prescribing the two term (K-T) elastic crack tip field as remote boundary conditions. The material is assumed to obey a rate-dependent crystal plasticity theory. The orientation of the single crystal is chosen so that the crack surface coincides with the crystallographic (010) plane and the crack front lies along 101] direction. Solutions corresponding to different stress intensity rates K., T-stress values and strain rate exponents m are obtained. The results show that the stress levels ahead of the crack tip increase with K. which is accompanied by gradual shrinking of the plastic zone size. However, the nature of the shear band patterns around the crack tip is not affected by the loading rate. Further, it is found that while positive T-stress enhances the opening and hydrostatic stress levels ahead of crack tip, they are considerably reduced with imposition of negative T-stress. Also, negative T-stress promotes formation of shear bands in the forward sector ahead of the crack tip and suppresses them behind the tip.

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Over the past two decades, many ingenious efforts have been made in protein remote homology detection. Because homologous proteins often diversify extensively in sequence, it is challenging to demonstrate such relatedness through entirely sequence-driven searches. Here, we describe a computational method for the generation of `protein-like' sequences that serves to bridge gaps in protein sequence space. Sequence profile information, as embodied in a position-specific scoring matrix of multiply aligned sequences of bona fide family members, serves as the starting point in this algorithm. The observed amino acid propensity and the selection of a random number dictate the selection of a residue for each position in the sequence. In a systematic manner, and by applying a `roulette-wheel' selection approach at each position, we generate parent family-like sequences and thus facilitate an enlargement of sequence space around the family. When generated for a large number of families, we demonstrate that they expand the utility of natural intermediately related sequences in linking distant proteins. In 91% of the assessed examples, inclusion of designed sequences improved fold coverage by 5-10% over searches made in their absence. Furthermore, with several examples from proteins adopting folds such as TIM, globin, lipocalin and others, we demonstrate that the success of including designed sequences in a database positively sensitized methods such as PSI-BLAST and Cascade PSI-BLAST and is a promising opportunity for enormously improved remote homology recognition using sequence information alone.

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Learning your αβγ's: The diversity of hydrogen-bonding patterns in backbone-expanded hybrid helices is shown by crystal-structure determination of several oligomeric peptides (see scheme; C=gray; H=white; O=red; N=blue). C 12 helices were observed in the αγ peptide series for n=2-8. In comparison, the αα peptide and αβ peptide sequences show C 10 and mixed C 14/C 15 helices, respectively. Copyright © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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Receive antenna selection (AS) has been shown to maintain the diversity benefits of multiple antennas while potentially reducing hardware costs. However, the promised diversity gains of receive AS depend on the assumptions of perfect channel knowledge at the receiver and slowly time-varying fading. By explicitly accounting for practical constraints imposed by the next-generation wireless standards such as training, packetization and antenna switching time, we propose a single receive AS method for time-varying fading channels. The method exploits the low training overhead and accuracy possible from the use of discrete prolate spheroidal (DPS) sequences based reduced rank subspace projection techniques. It only requires knowledge of the Doppler bandwidth, and does not require detailed correlation knowledge. Closed-form expressions for the channel prediction and estimation error as well as symbol error probability (SEP) of M-ary phase-shift keying (MPSK) for symbol-by-symbol receive AS are also derived. It is shown that the proposed AS scheme, after accounting for the practical limitations mentioned above, outperforms the ideal conventional single-input single-output (SISO) system with perfect CSI and no AS at the receiver and AS with conventional estimation based on complex exponential basis functions.

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Genome sequences contain a number of patterns that have biomedical significance. Repetitive sequences of various kinds are a primary component of most of the genomic sequence patterns. We extended the suffix-array based Biological Language Modeling Toolkit to compute n-gram frequencies as well as n-gram language-model based perplexity in windows over the whole genome sequence to find biologically relevant patterns. We present the suite of tools and their application for analysis on whole human genome sequence.