An approximate analysis of non-linear non-conservative systems subjected to step function excitation

This paper deals with the approximate analysis of the step response of non-linear nonconservative systems by the application of ultraspherical polynomials. From the differential equations for amplitude and phase, set up by the method of variation of parameters, the approximate solutions are obtained by a generalized averaging technique based on ultraspherical polynomial expansions. The Krylov-Bogoliubov results are given by a particular set of these polynomials. The method has been applied to study the step response of a cubic spring mass system in presence of viscous, material, quadratic, and mixed types of damping. The approximate results are compared with the digital and analogue computer solutions and a close agreement has been found between the analytical and the exact results.

Natural modes of a coupled non-linear system

The natural modes of a non-linear system with two degrees of freedom are investigated. The system, which may contain either hard or soft springs, is shown to possess three modes of vibration one of which does not have any counterpart in the linear theory. The stability analysis indicates the existence of seven different modal stability patterns depending on the values of two parameters of non-linearity.

Pressure dependence of chlorine nuclear quadrupole resonance in sodium chlorate

The pressure dependence of the chlorine NQR frequency in NaClo3 has been investigated up to 20 k bar hydrostatic pressure. A distinct break in slope in the pressure dependence of the resonance frequency is observed near 11 k bar. This is attributed to a phase transition reported earlier by Bridgman in this pressure region.

Asymptotic behaviour and boundedness of linear systems with time varying coefficients

Motivated by developments in spacecraft dynamics, the asymptotic behaviour and boundedness of solution of a special class of time varying systems in which each term appears as the sum of a constant and a time varying part, are analysed in this paper. It is not possible to apply standard textbook results to such systems, which are originally in second order. Some of the existing results are reformulated. Four theorems which explore the relations between the asymptotic behaviour/boundedness of the constant coefficient system, obtained by equating the time varying terms to zero, to the corresponding behaviour of the time varying system, are developed. The results show the behaviour of the two systems to be intimately related, provided the solutions of the constant coefficient system approach zero are bounded for large values of time, and the time varying terms are suitably restrained. Two problems are tackled using these theorems.

Performance analysis of a suprathreshold, stochastic resonance based nonlinear detector

In this paper we introduce a nonlinear detector based on the phenomenon of suprathreshold stochastic resonance (SSR). We first present a model (an array of 1-bit quantizers) that demonstrates the SSR phenomenon. We then use this as a pre-processor to the conventional matched filter. We employ the Neyman-Pearson(NP) detection strategy and compare the performances of the matched filter, the SSR-based detector and the optimal detector. Although the proposed detector is non-optimal, for non-Gaussian noises with heavy tails (leptokurtic) it shows better performance than the matched filter. In situations where the noise is known to be leptokurtic without the availability of the exact knowledge of its distribution, the proposed detector turns out to be a better choice than the matched filter.

Approximate linear time ML decoding on tail-biting trellises in two rounds

A linear time approximate maximum likelihood decoding algorithm on tail-biting trellises is presented, that requires exactly two rounds on the trellis. This is an adaptation of an algorithm proposed earlier with the advantage that it reduces the time complexity from O(m log m) to O(m) where m is the number of nodes in the tail-biting trellis. A necessary condition for the output of the algorithm to differ from the output of the ideal ML decoder is deduced and simulation results on an AWGN channel using tail-biting trellises for two rate 1/2 convolutional codes with memory 4 and 6 respectively, are reported.

A generalized Linear Programming based approach to optimal divisible load scheduling

In this paper we propose a general Linear Programming (LP) based formulation and solution methodology for obtaining optimal solution to the load distribution problem in divisible load scheduling. We exploit the power of the versatile LP formulation to propose algorithms that yield exact solutions to several very general load distribution problems for which either no solutions or only heuristic solutions were available. We consider both star (single-level tree) networks and linear daisy chain networks, having processors equipped with front-ends, that form the generic models for several important network topologies. We consider arbitrary processing node availability or release times and general models for communication delays and computation time that account for constant overheads such as start up times in communication and computation. The optimality of the LP based algorithms is proved rigorously.

A suprathreshold stochastic resonance based pre-processor for direction-of-arrival estimation

In this paper we propose a nonlinear preprocessor for enhancing the performance of processors used for direction-of-arrival (DOA) estimation in heavy-tailed non-Gaussian noise. The preprocessor based on the phenomenon of suprathreshold stochastic resonance (SSR), provides SNR gain. The preprocessed data is used for DOA estimation by the MUSIC algorithm. Simulation results are presented to show that the SSR preprocessor provides a significant improvement in the performance of MUSIC in heavy-tailed noise at low SNR.

Classification of magnetic resonance brain images using wavelets as input to support vector machine and neural network

In this paper. we propose a novel method using wavelets as input to neural network self-organizing maps and support vector machine for classification of magnetic resonance (MR) images of the human brain. The proposed method classifies MR brain images as either normal or abnormal. We have tested the proposed approach using a dataset of 52 MR brain images. Good classification percentage of more than 94% was achieved using the neural network self-organizing maps (SOM) and 98% front support vector machine. We observed that the classification rate is high for a Support vector machine classifier compared to self-organizing map-based approach.

Scalable non-linear Support Vector Machine using hierarchical clustering

This paper discusses a method for scaling SVM with Gaussian kernel function to handle large data sets by using a selective sampling strategy for the training set. It employs a scalable hierarchical clustering algorithm to construct cluster indexing structures of the training data in the kernel induced feature space. These are then used for selective sampling of the training data for SVM to impart scalability to the training process. Empirical studies made on real world data sets show that the proposed strategy performs well on large data sets.

Behaviour of autonomous mobile agents using linear cyclic pursuit laws

In this paper, the behaviour of a group of autonomous mobile agents under cyclic pursuit is studied. Cyclic pursuit is a simple distributed control law, in which the agent i pursues agent i + 1 modulo n.. The equations of motion are linear, with no kinematic constraints on motion. Behaviourally, the agents are identical, but may have different controller gains. We generalize existing results in the literature and show that by selecting these gains, the behavior of the agents can be controlled. They can be made to converge at a point or be directed to move in a straight line. The invariance of the point of convergence with the sequence of pursuit is also shown.

Construction and use of linear regression models for processor performance analysis

Processor architects have a challenging task of evaluating a large design space consisting of several interacting parameters and optimizations. In order to assist architects in making crucial design decisions, we build linear regression models that relate Processor performance to micro-architecture parameters, using simulation based experiments. We obtain good approximate models using an iterative process in which Akaike's information criteria is used to extract a good linear model from a small set of simulations, and limited further simulation is guided by the model using D-optimal experimental designs. The iterative process is repeated until desired error bounds are achieved. We used this procedure to establish the relationship of the CPI performance response to 26 key micro-architectural parameters using a detailed cycle-by-cycle superscalar processor simulator The resulting models provide a significance ordering on all micro-architectural parameters and their interactions, and explain the performance variations of micro-architectural techniques.

Rare earth exchanged (Ce3+, La3+ and RE3+) H-Y zeolites as solid acid catalysts for the synthesis of linear alkyl benzenes

Rare earth exchanged H–Y zeolites were prepared by simple ion exchange methods at 353 K and have been characterized using different physicochemical techniques. A strong peak around 58 ppm in the 27Al{1H} MAS NMR spectra of these zeolites suggests a tetrahedral coordination for the framework aluminium. Small peak at or near 0 ppm is due to hexa-coordinated extra-framework aluminium and a shoulder peak near 30 ppm is a penta-coordinated aluminium species; [Al(OH)4]−. The vapor-phase benzene alkylation with 1-decene and 1-dodecene was investigated with these catalytic systems. Under the reaction conditions of 448 K, benzene/olefin molar ratio of 20 and time on stream 3 h, the most efficient catalyst was CeH–Y which showed more than 70% of olefin conversion with 48.5% 2-phenyldecane and 46.8%, 2-phenyldodecane selectivities with 1-decene and 1-dodecene respectively.

Analysis of solar radiation pressure induced coupled liberations of a gravity stabilized axisymmetric satellite

This paper presents an analysis of solar radiation pressure induced coupled librations of gravity stabilized cylindrical spacecraft with a special reference to geostationary communication satellites. The Lagrangian approach is used to obtain the corresponding equations of motion. The solar induced torques are assumed to be free of librational angles and are represented by their Fourier expansion. The response and periodic solutions are obtained through linear and nonlinear analyses, using the method of harmonic balance in the latter case. The stability conditions are obtained using Routh-Hurwitz criteria. To establish the ranges of validity the analytic response is compared with the numerical solution. Finally, values of the system parameters are suggested to make the satellite behave as desired. Among these is a possible approach to subdue the solar induced roll resonance. It is felt that the approximate analysis presented here should significantly reduce the computational efforts involved in the design and stability analysis of the systems.

Direct Synthesis of Terminally ``Clickable'' Linear and Hyperbranched Polyesters

1,3-Dipolar cycloaddition of an organic azide and an acetylenic unit,often referred to as the ``click reaction'', has become an important ligation tool both in the context of materials chemistry and biology. Thus, development of simple approaches to directly generate polymers that bear either an azide or an alkyne unit has gained considerable importance. We describe here a straightforward approach to directly prepare linear and hyperbranched polyesters that carry terminal propargyl groups. To achieve the former, we designed an AB-type monomer that carries a hydroxyl group and a propargyl ester, which upon self-condensation under standard transesterification conditions yielded a polyester that carries a single propargyl group at one of its chain-ends. Similarly, an AB(2) type monomer that carries one hydroxyl group and two propargyl ester groups, when polymerized under the same conditions yielded a hyperbranched polymer with numerous clickable'' propargyl groups at its molecular periphery. These propargyl groups can be readily clicked with different organic azides, such as benzyl azide, omega-azido heptaethyleneglycol monomethylether or 9-azidomethyl anthracene. When an anthracene chromophore is clicked, the molecular weight of the linear polyester could be readily estimated using both UV-visible and fluorescence spectroscopic measurements. Furthermore, the reactive propargyl end group could also provide an opportunity to prepare block copolymers in the case of linear polyesters and to generate nanodimensional scaffolds to anchor variety of functional units, in the case of the hyperbranched polymer. (C) 2010 Wiley Periodicals, Inc. J Polym Sci Part A: Polym Chem 48: 3200-3208, 2010.