Absolutely expedient algorithms for learning Nash equilibria

This paper considers a multi-person discrete game with random payoffs. The distribution of the random payoff is unknown to the players and further none of the players know the strategies or the actual moves of other players. A class of absolutely expedient learning algorithms for the game based on a decentralised team of Learning Automata is presented. These algorithms correspond, in some sense, to rational behaviour on the part of the players. All stable stationary points of the algorithm are shown to be Nash equilibria for the game. It is also shown that under some additional constraints on the game, the team will always converge to a Nash equilibrium.

Stochastic Approximation Algorithms for Constrained Optimization via Simulation

We develop four algorithms for simulation-based optimization under multiple inequality constraints. Both the cost and the constraint functions are considered to be long-run averages of certain state-dependent single-stage functions. We pose the problem in the simulation optimization framework by using the Lagrange multiplier method. Two of our algorithms estimate only the gradient of the Lagrangian, while the other two estimate both the gradient and the Hessian of it. In the process, we also develop various new estimators for the gradient and Hessian. All our algorithms use two simulations each. Two of these algorithms are based on the smoothed functional (SF) technique, while the other two are based on the simultaneous perturbation stochastic approximation (SPSA) method. We prove the convergence of our algorithms and show numerical experiments on a setting involving an open Jackson network. The Newton-based SF algorithm is seen to show the best overall performance.

Characterization of the zinc-metalloprotein nature of rat spermatidal protein TP2

Spermatidal transition protein, TP2, was purified from rat testes by Hg-affinity chromatography. The present study reports the details of the zinc-metalloprotein nature of TP2 by employing the Zn-65-blotting technique. Chemical modification of cysteine by iodoacetic acid, and histidine by diethylpyrocarbonate, resulted in a near complete inhibition of Zn-65-binding to TP2. The (65)Zinc-binding was localized to the V8 protease-derived N-terminal two-third polypeptide fragment. Circular dichroism spectroscopy studies of TP2 (zinc pre-incubated) and its V8 protease-derived polypeptide fragments revealed that the N-terminal fragment has a Type I-beta-turn spectrum, while the C-terminal fragment has a small but significant alpha-helical structure. EDTA altered the circular dichroism spectrum of TP2 and the N-terminal fragment (zinc binding domain) but not that of the C-terminal fragment.

Cooperative Spectrum Sensing Algorithms For OFDM Systems with Frequency Selective Channels

This paper considers the problem of spectrum sensing in cognitive radio networks when the primary user employs Orthogonal Frequency Division Multiplexing (OFDM). We specifically consider the scenario when the channel between the primary and a secondary user is frequency selective. We develop cooperative sequential detection algorithms based on energy detectors. We modify the detectors to mitigate the effects of some common model uncertainties such as timing and frequency offset, IQ-imbalance and uncertainty in noise and transmit power. The performance of the proposed algorithms are studied via simulations. We show that the performance of the energy detector is not affected by the frequency selective channel. We also provide a theoretical analysis for some of our algorithms.

Fe-Cr/Al2O3 metal-ceramic composites: Nature and size of the metal particles formed during hydrogen reduction

Fe-Cr/Al2O3 metal-ceramic composites prepared by hydrogen reduction at different temperatures and for different periods have been investigated by a combined use of Mossbauer spectroscopy, x-ray diffraction, transmission electron microscopy, and energy-dispersive x-ray spectroscopy in order to obtain information on the nature of the metallic species formed. Total reduction of Fe3+ does not occur by increasing the reduction time at 1320 K from 1 to 30 h, and the amount of superparamagnetic metallic species is essentially constant (about 10%). Temperatures higher than 1470 K are needed to achieve nearly total reduction of substitutional Fe3+. Interestingly, iron favors the reduction of chromium. The composition of the Fe-Cr particles is strongly dependent on their size, the Cr content being higher in particles smaller than 10 nm.

Flat connections, geometric invariants and the symplectic nature of the fundamental group of surfaces

In this paper we associate a new geometric invariant to the space of fiat connections on a G (= SU(2))-bundle on a compact Riemann surface M and relate it tcr the symplectic structure on the space Hom(pi(1)(M), G)/G consisting of representations of the fundamental group pi(1)(M) Of M into G module the conjugate action of G on representations.

Managing interprocessor delays in distributed recursive algorithms

For a class of distributed recursive algorithms, it is shown that a stochastic approximation-like tapering stepsize routine suppresses the effects of interprocessor delays.

Multiple UAV Coalitions for a Search and Prosecute Mission

Unmanned aerial vehicles (UAVs) have the potential to carry resources in support of search and prosecute operations. Often to completely prosecute a target, UAVs may have to simultaneously attack the target with various resources with different capacities. However, the UAVs are capable of carrying only limited resources in small quantities, hence, a group of UAVs (coalition) needs to be assigned that satisfies the target resource requirement. The assigned coalition must be such that it minimizes the target prosecution delay and the size of the coalition. The problem of forming coalitions is computationally intensive due to the combinatorial nature of the problem, but for real-time applications computationally cheap solutions are required. In this paper, we propose decentralized sub-optimal (polynomial time) and decentralized optimal coalition formation algorithms that generate coalitions for a single target with low computational complexity. We compare the performance of the proposed algorithms to that of a global optimal solution for which we need to solve a centralized combinatorial optimization problem. This problem is computationally intensive because the solution has to (a) provide a coalition for each target, (b) design a sequence in which targets need to be prosecuted, and (c) take into account reduction of UAV resources with usage. To solve this problem we use the Particle Swarm Optimization (PSO) technique. Through simulations, we study the performance of the proposed algorithms in terms of mission performance, complexity of the algorithms and the time taken to form the coalition. The simulation results show that the solution provided by the proposed algorithms is close to the global optimal solution and requires far less computational resources.

An Efficient Simulated Annealing With a Valid Solution Mechanism For TDMA Brodcast Scheduling problem

This paper presents an efficient Simulated Annealing with valid solution mechanism for finding an optimum conflict-free transmission schedule for a broadcast radio network. This is known as a Broadcast Scheduling Problem (BSP) and shown as an NP-complete problem, in earlier studies. Because of this NP-complete nature, earlier studies used genetic algorithms, mean field annealing, neural networks, factor graph and sum product algorithm, and sequential vertex coloring algorithm to obtain the solution. In our study, a valid solution mechanism is included in simulated annealing. Because of this inclusion, we are able to achieve better results even for networks with 100 nodes and 300 links. The results obtained using our methodology is compared with all the other earlier solution methods.

Dynamic stiffness matrix of a general cable element

A computational scheme for determining the dynamic stiffness coefficients of a linear, inclined, translating and viscously/hysteretically damped cable element is outlined. Also taken into account is the coupling between inplane transverse and longitudinal forms of cable vibration. The scheme is based on conversion of the governing set of quasistatic boundary value problems into a larger equivalent set of initial value problems, which are subsequently numerically integrated in a spatial domain using marching algorithms. Numerical results which bring out the nature of the dynamic stiffness coefficients are presented. A specific example of random vibration analysis of a long span cable subjected to earthquake support motions modeled as vector gaussian random processes is also discussed. The approach presented is versatile and capable of handling many complicating effects in cable dynamics in a unified manner.

Line clipping revisited: Two efficient algorithms based on simple geometric observations

Two new line clipping algorithms, the opposite-corner algorithm and the perpendicular-distance algorithm, that are based on simple geometric observations are presented. These algorithms do not require computation of outcodes nor do they depend on the parametric representations of the lines. It is shown that the opposite-corner algorithm perform consistently better than an algorithm due to Nicholl, Lee, and Nicholl which is claimed to be better than the classic algorithm due to Cohen-Sutherland and the more recent Liang-Barsky algorithm. The pseudo-code of the opposite-corner algorithm is provided in the Appendix.

Influence of glycosidic linkage on the nature of carbohydrate binding in beta-prism I fold lectins: An X-ray and molecular dynamics investigation on banana lectin-carbohydrate complexes

The three crystal structures reported here provide details of the interactions of mannose and the mannosyl-alpha-1,3-mannose component of a pentamannose with banana lectin and evidence for the binding of glucosyl-alpha-1,2-glucose to the lectin. The known structures involving the lectin include a complex with glucosyl-beta-1,3-glucose. Modeling studies on the three disaccharide complexes with the reducing end and the nonreducing end at the primary binding site are also provided here. The results of the Xray and modeling studies show that the disaccharides with an alpha-1,3 linkage prefer to have the nonreducing end at the primary binding site, whereas the reducing end is preferred at the site when the linkage is beta-1,3 in mannose/glucose-specific beta-prism I fold lectins. In the corresponding galactose-specific lectins, however, alpha-1,3-linked disaccharides cannot bind the lectin with the nonreducing end at the primary binding site on account of steric clashes with an aromatic residue that occurs only when the lectin is galactose-specific. Molecular dynamics simulations based on the known structures involving banana lectin enrich the information on lectin-carbohydrate interactions obtained from crystal structures. They demonstrate that conformational selection as well as induced fit operate when carbohydrates bind to banana lectin.

S-nets: A Petri net based model for performance evaluation of real-time scheduling algorithms

A new class of nets, called S-nets, is introduced for the performance analysis of scheduling algorithms used in real-time systems Deterministic timed Petri nets do not adequately model the scheduling of resources encountered in real-time systems, and need to be augmented with resource places and signal places, and a scheduler block, to facilitate the modeling of scheduling algorithms. The tokens are colored, and the transition firing rules are suitably modified. Further, the concept of transition folding is used, to get intuitively simple models of multiframe real-time systems. Two generic performance measures, called �load index� and �balance index,� which characterize the resource utilization and the uniformity of workload distribution, respectively, are defined. The utility of S-nets for evaluating heuristic-based scheduling schemes is illustrated by considering three heuristics for real-time scheduling. S-nets are useful in tuning the hardware configuration and the underlying scheduling policy, so that the system utilization is maximized, and the workload distribution among the computing resources is balanced.

Structure-potential relationship and nature of disorder in liquids and glassy solids

A method based on the minimal-spanning tree is extended to a collection of points in three dimensions. Two parameters, the average edge length and its standard deviation characterize the disorder. The structural phase diagram for a monatomic system of particles and the characteristic values for the uniform random distribution of points have been obtained. The method is applied to hard spheres and Lennard-Jones systems. These systems occupy distinct regions in the structural phase diagram. The structure of the Lennard-Jones system approaches that of the defective close-packed arrangements at low temperatures whereas in the liquid regime, it deviates from the close-packed configuration.

Some Algorithms for Eigensubspace Estimation

An important tool in signal processing is the use of eigenvalue and singular value decompositions for extracting information from time-series/sensor array data. These tools are used in the so-called subspace methods that underlie solutions to the harmonic retrieval problem in time series and the directions-of-arrival (DOA) estimation problem in array processing. The subspace methods require the knowledge of eigenvectors of the underlying covariance matrix to estimate the parameters of interest. Eigenstructure estimation in signal processing has two important classes: (i) estimating the eigenstructure of the given covariance matrix and (ii) updating the eigenstructure estimates given the current estimate and new data. In this paper, we survey some algorithms for both these classes useful for harmonic retrieval and DOA estimation problems. We begin by surveying key results in the literature and then describe, in some detail, energy function minimization approaches that underlie a class of feedback neural networks. Our approaches estimate some or all of the eigenvectors corresponding to the repeated minimum eigenvalue and also multiple orthogonal eigenvectors corresponding to the ordered eigenvalues of the covariance matrix. Our presentation includes some supporting analysis and simulation results. We may point out here that eigensubspace estimation is a vast area and all aspects of this cannot be fully covered in a single paper. (C) 1995 Academic Press, Inc.