Performance comparisons between greedy and lagrange algorithms in adaptive MIMO MC-CDMA systems

This paper describes two algorithms for adaptive power and bit allocations in a multiple input multiple output multiple-carrier code division multiple access (MIMO MC-CDMA) system. The first is the greedy algorithm, which has already been presented in the literature. The other one, which is proposed by the authors, is based on the use of the Lagrange multiplier method. The performances of the two algorithms are compared via Monte Carlo simulations. At present stage, the simulations are restricted to a single user MIMO MC-CDMA system, which is equivalent to a MIMO OFDM system. It is assumed that the system operates in a frequency selective fading environment. The transmitter has a partial knowledge of the channel whose properties are measured at the receiver. The use of the two algorithms results in similar system performances. The advantage of the Lagrange algorithm is that is much faster than the greedy algorithm. ©2005 IEEE

A hybrid probabilistic criterion for market-based transmission expansion planning

Market-based transmission expansion planning gives information to investors on where is the most cost efficient place to invest and brings benefits to those who invest in this grid. However, both market issue and power system adequacy problems are system planers’ concern. In this paper, a hybrid probabilistic criterion of Expected Economical Loss (EEL) is proposed as an index to evaluate the systems’ overall expected economical losses during system operation in a competitive market. It stands on both investors’ and planner’s point of view and will further improves the traditional reliability cost. By applying EEL, it is possible for system planners to obtain a clear idea regarding the transmission network’s bottleneck and the amount of losses arises from this weak point. Sequentially, it enables planners to assess the worth of providing reliable services. Also, the EEL will contain valuable information for moneymen to undertake their investment. This index could truly reflect the random behaviors of power systems and uncertainties from electricity market. The performance of the EEL index is enhanced by applying Normalized Coefficient of Probability (NCP), so it can be utilized in large real power systems. A numerical example is carried out on IEEE Reliability Test System (RTS), which will show how the EEL can predict the current system bottleneck under future operational conditions and how to use EEL as one of planning objectives to determine future optimal plans. A well-known simulation method, Monte Carlo simulation, is employed to achieve the probabilistic characteristic of electricity market and Genetic Algorithms (GAs) is used as a multi-objective optimization tool.

Algorithms for sequence analysis via mutagenesis

Despite many successes of conventional DNA sequencing methods, some DNAs remain difficult or impossible to sequence. Unsequenceable regions occur in the genomes of many biologically important organisms, including the human genome. Such regions range in length from tens to millions of bases, and may contain valuable information such as the sequences of important genes. The authors have recently developed a technique that renders a wide range of problematic DNAs amenable to sequencing. The technique is known as sequence analysis via mutagenesis (SAM). This paper presents a number of algorithms for analysing and interpreting data generated by this technique.

Comparison of BR and QR Eigenvalue Algorithms for Power System Small Signal Stability Analysis

The BR algorithm is a novel and efficient method to find all eigenvalues of upper Hessenberg matrices and has never been applied to eigenanalysis for power system small signal stability. This paper analyzes differences between the BR and the QR algorithms with performance comparison in terms of CPU time based on stopping criteria and storage requirement. The BR algorithm utilizes accelerating strategies to improve its performance when computing eigenvalues of narrowly banded, nearly tridiagonal upper Hessenberg matrices. These strategies significantly reduce the computation time at a reasonable level of precision. Compared with the QR algorithm, the BR algorithm requires fewer iteration steps and less storage space without depriving of appropriate precision in solving eigenvalue problems of large-scale power systems. Numerical examples demonstrate the efficiency of the BR algorithm in pursuing eigenanalysis tasks of 39-, 68-, 115-, 300-, and 600-bus systems. Experiment results suggest that the BR algorithm is a more efficient algorithm for large-scale power system small signal stability eigenanalysis.

A study of the stability of subcycling algorithms in structural dynamics

Algorithms for explicit integration of structural dynamics problems with multiple time steps (subcycling) are investigated. Only one such algorithm, due to Smolinski and Sleith has proved to be stable in a classical sense. A simplified version of this algorithm that retains its stability is presented. However, as with the original version, it can be shown to sacrifice accuracy to achieve stability. Another algorithm in use is shown to be only statistically stable, in that a probability of stability can be assigned if appropriate time step limits are observed. This probability improves rapidly with the number of degrees of freedom in a finite element model. The stability problems are shown to be a property of the central difference method itself, which is modified to give the subcycling algorithm. A related problem is shown to arise when a constraint equation in time is introduced into a time-continuous space-time finite element model. (C) 1998 Elsevier Science S.A.

Anomalous fluorescence spectra in an extremely weak, broadband squeezed vacuum under monochromatic and bichromatic excitation

We show that a two-level atom interacting with an extremely weak squeezed vacuum can display resonance fluorescence spectra that are qualitatively different to those that can be obtained using fields with a classical analogue. We consider first the free space situation with monochromatic excitation, and then discuss a bichromatically driven two-level atom in a cavity as a practical scenario for experimentally detecting the anomalous features predicted. We show that in the bad cavity limit, the anomalous spectral features appear for a weak squeezed vacuum and large frequency differences of the bichromatic field, conditions which are easily accessible in laboratories. The advantage of bichromatic, as opposed to monochromatic, excitation is that there is no coherent scattering at line centre which could obscure the observations. A scaling law is derived, N similar to Omega(4) which relates the squeezed photon number to the Rabi frequency at which the anomalous features appear. (C) 1998 Elsevier Science B.V.

Resonance fluorescence spectrum in a weak squeezed field with an arbitrary bandwidth

We analyze the linewidth narrowing in the fluorescence spectrum of a two-level atom driven by a squeezed vacuum field of a finite bandwidth. It is found that the fluorescence spectrum in a low-intensity squeezed field can exhibit a (omega - omega(0))(-6) frequency dependence in the wings. We show that this fast fall-off behavior is intimately related to the properties of a narrow-bandwidth squeezed field and does not extend into the region of broadband excitation. We apply the Linear response model and find that the narrowing results from a convolution of the atom response with the spectrum of the incident field. On the experimental side, we emphasize that the linewidth narrowing is not sensitive to the solid angle of the squeezed modes coupled to the atom. We also compare the fluorescence spectrum with the quadrature-noise spectrum and find that the fluorescence spectrum for an off-resonance excitation does not reveal the noise spectrum. We show that this difference arises from the competing three-photon scattering processes. [S1050-2947(98)04308-X].

Extended GCD and Hermite normal form algorithms via lattice basis reduction

Extended gcd calculation has a long history and plays an important role in computational number theory and linear algebra. Recent results have shown that finding optimal multipliers in extended gcd calculations is difficult. We present an algorithm which uses lattice basis reduction to produce small integer multipliers x(1), ..., x(m) for the equation s = gcd (s(1), ..., s(m)) = x(1)s(1) + ... + x(m)s(m), where s1, ... , s(m) are given integers. The method generalises to produce small unimodular transformation matrices for computing the Hermite normal form of an integer matrix.

Spectral linewidth narrowing by a weak squeezed field of an arbitrary bandwidth

We study the spectral and noise properties of the fluorescence field emitted from a two-level atom driven by a beam of squeezed light. For a weak driving field we derive simple analytical formulae for the fluorescence and quadrature-noise spectra which are valid for an arbitrary bandwidth of the squeezed field. We analyse the spectra in the regime where the squeezing bandwidth is smaller or comparable to the atomic linewidth, the area where non-Markovian effects are important. We emphasize that there is a noticable difference between the fluorescence spectra for the thermal and squeezed field excitations. In both cases the spectrum can be narrower than any bandwidth involved in the process. However, as we point out for the squeezed driving field the linewidth narrowing, being much larger than in the thermal-field case, can be attributed to the squeezing of the fluctuations in the driving held. We also calculate the quadrature-noise spectrum of the emitted fluorescence, and find that for a detuned squeezed field the fluorescence spectrum does not reveal the quadrature-noise spectrum. In contrast to the fluorescence spectrum having two peaks, the quadrature-noise spectrum exhibits three peaks. We explain this difference as arising from the competiting three-photon scattering processes. (C) 1998 Elsevier Science B.V. All rights reserved.

Effects of data characteristics on the results of reserve selection algorithms

We tested the effects of four data characteristics on the results of reserve selection algorithms. The data characteristics were nestedness of features (land types in this case), rarity of features, size variation of sites (potential reserves) and size of data sets (numbers of sites and features). We manipulated data sets to produce three levels, with replication, of each of these data characteristics while holding the other three characteristics constant. We then used an optimizing algorithm and three heuristic algorithms to select sites to solve several reservation problems. We measured efficiency as the number or total area of selected sites, indicating the relative cost of a reserve system. Higher nestedness increased the efficiency of all algorithms (reduced the total cost of new reserves). Higher rarity reduced the efficiency of all algorithms (increased the total cost of new reserves). More variation in site size increased the efficiency of all algorithms expressed in terms of total area of selected sites. We measured the suboptimality of heuristic algorithms as the percentage increase of their results over optimal (minimum possible) results. Suboptimality is a measure of the reliability of heuristics as indicative costing analyses. Higher rarity reduced the suboptimality of heuristics (increased their reliability) and there is some evidence that more size variation did the same for the total area of selected sites. We discuss the implications of these results for the use of reserve selection algorithms as indicative and real-world planning tools.

Weak-force detection with superposed coherent states

We investigate the utility of nonclassical states of simple harmonic oscillators, particularly a superposition of coherent states, for sensitive force detection. We find that like squeezed states, a superposition of coherent states allows displacement measurements at the Heisenberg limit. Entangling many superpositions of coherent states offers a significant advantage over a single-mode superposition state with the same mean photon number.

Genetic algorithms for design of liquid retaining structure

In this paper, genetic algorithm (GA) is applied to the optimum design of reinforced concrete liquid retaining structures, which comprise three discrete design variables, including slab thickness, reinforcement diameter and reinforcement spacing. GA, being a search technique based on the mechanics of natural genetics, couples a Darwinian survival-of-the-fittest principle with a random yet structured information exchange amongst a population of artificial chromosomes. As a first step, a penalty-based strategy is entailed to transform the constrained design problem into an unconstrained problem, which is appropriate for GA application. A numerical example is then used to demonstrate strength and capability of the GA in this domain problem. It is shown that, only after the exploration of a minute portion of the search space, near-optimal solutions are obtained at an extremely converging speed. The method can be extended to application of even more complex optimization problems in other domains.

Robust algorithms for solving stochastic partial differential equations

A robust semi-implicit central partial difference algorithm for the numerical solution of coupled stochastic parabolic partial differential equations (PDEs) is described. This can be used for calculating correlation functions of systems of interacting stochastic fields. Such field equations can arise in the description of Hamiltonian and open systems in the physics of nonlinear processes, and may include multiplicative noise sources. The algorithm can be used for studying the properties of nonlinear quantum or classical field theories. The general approach is outlined and applied to a specific example, namely the quantum statistical fluctuations of ultra-short optical pulses in chi((2)) parametric waveguides. This example uses a non-diagonal coherent state representation, and correctly predicts the sub-shot noise level spectral fluctuations observed in homodyne detection measurements. It is expected that the methods used wilt be applicable for higher-order correlation functions and other physical problems as well. A stochastic differencing technique for reducing sampling errors is also introduced. This involves solving nonlinear stochastic parabolic PDEs in combination with a reference process, which uses the Wigner representation in the example presented here. A computer implementation on MIMD parallel architectures is discussed. (C) 1997 Academic Press.