Learning Optimal Discriminant Functions through a Cooperative Game of Automata

The problem of learning correct decision rules to minimize the probability of misclassification is a long-standing problem of supervised learning in pattern recognition. The problem of learning such optimal discriminant functions is considered for the class of problems where the statistical properties of the pattern classes are completely unknown. The problem is posed as a game with common payoff played by a team of mutually cooperating learning automata. This essentially results in a probabilistic search through the space of classifiers. The approach is inherently capable of learning discriminant functions that are nonlinear in their parameters also. A learning algorithm is presented for the team and convergence is established. It is proved that the team can obtain the optimal classifier to an arbitrary approximation. Simulation results with a few examples are presented where the team learns the optimal classifier.

On evolutionarily stable compositions of populations of interacting genotypes.

Consider an organism in which the genetic fitness of an individual depends to a large extent on its social interactions. Assuming the genotypes to differ only in the choice of strategies they adopt in social interactions, and equating the variation in genetic fitness to the mean payoff to an individual averaged over all possible encounters, we develop a dynamical model for the evolution of genotypic frequencies in such a population. Such a system is characterised by frequency dependent selection, and depending on the initial composition, the population evolves towards one of several possible compositions. We term as evolutionarily stable compositions (ESC) any such composition towards which a population can evolve and which is stable against small fluctuations in the frequencies of existing genotypes as well as to invasions by any other postulated genotype. We state the necessary and sufficient conditions for the identification of all possible ESC's for any number of interacting genotypes. Our results conform to those derived earlier in connection with the concept of evolutionarily stable strategies only in the case of two interacting genotypes; when more than two genotypes interact the conditions under which various ESC's exist become far richer. We consider interactions with mixed strategists and show that in a conflict with pure strategists the optimal mixed strategist will be the only one to ultimately survive. We illustrate our approach by considering the specific case of a primitively social wasp.

Vapour composition and activities in Mg-Zn liquid alloy at 923 K

Vapour species effusing from a magnesia Knudsen cell containing Mg-Zn alloy at 923 K were condensed on a water cooled copper plate. The equilibrium composition of the vapour phase over the alloy was determined from chemical analysis of the condensate. The activity coefficients of both components in the alloy have been derived from the data using a modified Gibbs-Duhem relation. The ratio of saturation vapour pressures of pure Zn and Mg obtained from the analysis of alloy data agree well with values from the literature, providing an internal check on the accuracy of data obtained in this study. Both components of the alloy exhibit negative deviations from Raoult's law. The concentration-concentration structure factor of Bhatia and Thomton at zero wave vector, evaluated from the measurements, indicate the presence of MgZn2 type complex in the liquid state. The associated regular solution model has been used for the thermodynamic description of liquid Mg-Zn alloys.

An Optimal g-Guidance Scheme for Satellite Launch Vehicles

A closed-loop steering logic based on an optimal (2-guidance is developed here. The guidance system drives the satellite launch vehicle along a two- or three- dimensional trajectory for placing the payload into a specified circular orbit. The modified g-guidance algorithm makes use of the optimal required velocity vector, which minimizes the total impulse needed for an equivalent two-impluse transfer from the present state to the final orbit. The required velocity vector is defined as velocity of the vehicle on the hypothetical transfer orbit immediately after the application of the first impulse. For this optimal transfer orbit, a simple and elegant expression for the Q-matrix is derived. A working principle for the guidance algorithm in terms of the major and minor cycles, and also for the generation of the steering command, is outlined.

Lipids of nervous tissue: composition and metabolism

As indicated in the Introduction, the many significant developments in the recent past in our knowledge of the lipids of the nervous system have been collated in this article. That there is a sustained interest in this field is evident from the rather long bibliography which is itself selective. Obviously, it is not possible to summarize a review in which the chemistry, distribution and metabolism of a great variety of lipids have been discussed. However, from the progress of research, some general conclusions may be drawn. The period of discovery of new lipids in the nervous system appears to be over. All the major lipid components have been discovered and a great deal is now known about their structure and metabolism. Analytical data on the lipid composition of the CNS are available for a number of species and such data on the major areas of the brain are also at hand but information on the various subregions is meagre. Such investigations may yet provide clues to the role of lipids in brain function. Compared to CNS, information on PNS is less adequate. Further research on PNS would be worthwhile as it is amenable for experimental manipulation and complex mechanisms such as myelination can be investigated in this tissue. There are reports correlating lipid constituents with the increased complexity in the organization of the nervous system during evolution. This line of investigation may prove useful. The basic aim of research on the lipids of the nervous tissue is to unravel their functional significance.

A composition dependent thermal behavior of GexSe35-xTe65 glasses

Alternating differential scanning calorimetric (ADSC) studies have been performed to understand the thermal behavior of bulk GexSe35-xTe65 glasses (17 <= x <= 25); it is found that the glasses with x <= 20 exhibit two crystallization exotherms (T-c1 & T-c2). On the other hand, those with x >= 20.5, show a single crystallization reaction upon heating. The exothermic reaction at T-c1 has been found to correspond to the partial crystallization of the glass into hexagonal Te and the reaction at T-c2 is associated with the additional crystallization of rhombohedral Ge-Te phase. The glass transition temperature of GexSe35-xTe65 glasses is found to show a linear but not-steep increase, indicating a progressive, but a gradual increase in network connectivity with Ge addition. It is also found that T-c1 of GexSe35-xTe65 glasses with x <= 20, increases progressively with Ge content and eventually merges with T-c2 at x approximate to 20.5 (< r > = 2.41); this behavior has been understood on the basis of the reduction in Te-Te bonds of lower energy and increase in Ge-Te bonds of higher energy, with increasing Ge content. Apart from the interesting composition dependent crystallization, an anomalous melting behavior is also exhibited by the GexSe35-xTe65 glasses.

An Online Implementable Differential Evolution Tuned Optimal Guidance Law

This paper proposes a novel application of differential evolution to solve a difficult dynamic optimisation or optimal control problem. The miss distance in a missile-target engagement is minimised using differential evolution. The difficulty of solving it by existing conventional techniques in optimal control theory is caused by the nonlinearity of the dynamic constraint equation, inequality constraint on the control input and inequality constraint on another parameter that enters problem indirectly. The optimal control problem of finding the minimum miss distance has an analytical solution subject to several simplifying assumptions. In the approach proposed in this paper, the initial population is generated around the seed value given by this analytical solution. Thereafter, the algorithm progresses to an acceptable final solution within a few generations, satisfying the constraints at every iteration. Since this solution or the control input has to be obtained in real time to be of any use in practice, the feasibility of online implementation is also illustrated.

The Influence of Bilayer Composition on the Gel to Liquid Crystalline Transition

We report molecular dynamics simulations of bilayers using a united atom model with explicit solvent molecules. The bilayer consists of the single tail cationic surfactant behenyl trimethyl ammonium chloride (BTMAC) with stearyl alcohol (SA) as the cosurfactant. We study the gel to liquid crystalline transitions in the bilayer by varying the amount of water at fixed BTMAC to SA ratio as well as by varying the BTMAC to SA ratio at fixed water content. The bilayer is found to exist in the tilted, Lβ′ phase at low temperatures, and for the compositions investigated in this study, the Lβ′ to Lα melting transition occurred in the temperature range 330−338 K. For the highest BTMAC to SA composition (2:3 molar ratio), a diffuse headgroup−water interface is observed at lower temperatures, and an increase in the d-spacing occurs prior to the melting transition. This pretransition swelling is accompanied by a sharpening in the water density variation across the headgroup region of the bilayer. Signatures of this swelling effect which can be observed in the alkane density distributions, area per headgroup, and membrane thickness are attributed to the hydrophobic effect. At a fixed bilayer composition, the transition temperature (>338 K) from the Lβ′ to Lα transition obtained for the high water content bilayer (80 wt %) is similar to that obtained with low water content (54.3 wt %), confirming that the melting transition at these water contents is dominated by chain melting.

Optimal dynamic inversion-based semi-active control of benchmark bridge using MR dampers

A new two-stage state feedback control design approach has been developed to monitor the voltage supplied to magnetorheological (MR) dampers for semi-active vibration control of the benchmark highway bridge. The first stage contains a primary controller, which provides the force required to obtain a desired closed-loop response of the system. In the second stage, an optimal dynamic inversion (ODI) approach has been developed to obtain the amount of voltage to be supplied to each of the MR dampers such that it provides the required force prescribed by the primary controller. ODI is formulated by optimization with dynamic inversion, such that an optimal voltage is supplied to each damper in a set. The proposed control design has been simulated for both phase-I and phase-II study of the recently developed benchmark highway bridge problem. The efficiency of the proposed controller is analyzed in terms of the performance indices defined in the benchmark problem definition. Simulation results demonstrate that the proposed approach generally reduces peak response quantities over those obtained from the sample semi-active controller, although some response quantities have been seen to be increasing. Overall, the proposed control approach is quite competitive as compared with the sample semi-active control approach.

Optimal simultaneous maximum a posterioriestimation of states, noise statistics and parameters I. Algorithm

The simultaneous state and parameter estimation problem for a linear discrete-time system with unknown noise statistics is treated as a large-scale optimization problem. The a posterioriprobability density function is maximized directly with respect to the states and parameters subject to the constraint of the system dynamics. The resulting optimization problem is too large for any of the standard non-linear programming techniques and hence an hierarchical optimization approach is proposed. It turns out that the states can be computed at the first levelfor given noise and system parameters. These, in turn, are to be modified at the second level.The states are to be computed from a large system of linear equations and two solution methods are considered for solving these equations, limiting the horizon to a suitable length. The resulting algorithm is a filter-smoother, suitable for off-line as well as on-line state estimation for given noise and system parameters. The second level problem is split up into two, one for modifying the noise statistics and the other for modifying the system parameters. An adaptive relaxation technique is proposed for modifying the noise statistics and a modified Gauss-Newton technique is used to adjust the system parameters.

Optimal simultaneous maximum a posterioriestimation of states, noise statistics and parameters II. Numerical performance

A very general and numerically quite robust algorithm has been proposed by Sastry and Gauvrit (1980) for system identification. The present paper takes it up and examines its performance on a real test example. The example considered is the lateral dynamics of an aircraft. This is used as a vehicle for demonstrating the performance of various aspects of the algorithm in several possible modes.

Optimal Interconnections in the Design of Microprocessors and Digital Systems

This paper recasts the multiple data path assignment problem solved by Torng and Wilhelm by the dynamic programming method [1] into a minimal covering problem following a switching theoretic approach. The concept of bus compatibility for the data transfers is used to obtain the various ways of interconnecting the circuit modules with the minimum number of buses that allow concurrent data transfers. These have been called the feasible solutions of the problem. The minimal cost solutions are obtained by assigning weights to the bus-compatible sets present in the feasible solutions. Minimization of the cost of the solution by increasing the number of buses is also discussed.

Optimal Interconnections in the Design of Microprocessors and Digital Systems

This paper recasts the multiple data path assignment problem solved by Torng and Wilhelm by the dynamic programming method [1] into a minimal covering problem following a switching theoretic approach. The concept of bus compatibility for the data transfers is used to obtain the various ways of interconnecting the circuit modules with the minimum number of buses that allow concurrent data transfers. These have been called the feasible solutions of the problem. The minimal cost solutions are obtained by assigning weights to the bus-compatible sets present in the feasible solutions. Minimization of the cost of the solution by increasing the number of buses is also discussed.

Optimal irrigation planning in river basin development: The case of the Upper Cauvery river basin

The study deals with the irrigation planning of the Cauvery river basin in peninsular India which is extensively developed in the downstream reaches and has a high potential for development in the upper reaches. A four-reservoir system is modelled on a monthly basis by using a mathematical programming (LP) formulation to find optimum cropping patterns, subject to land, water and downstream release constraints, and applied to the Cauvery basin. Two objectives, maximizing net economic benefits and maximizing irrigated cropped area, considered in the model are analysed in the context of multiobjective planning and the trade-offs discussed.