Solution of Linear Programming Problems using a Neural Network with Non-Linear Feedback

This paper presents a recurrent neural circuit for solving linear programming problems. The objective is to minimize a linear cost function subject to linear constraints. The proposed circuit employs non-linear feedback, in the form of unipolar comparators, to introduce transcendental terms in the energy function ensuring fast convergence to the solution. The proof of validity of the energy function is also provided. The hardware complexity of the proposed circuit compares favorably with other proposed circuits for the same task. PSPICE simulation results are presented for a chosen optimization problem and are found to agree with the algebraic solution. Hardware test results for a 2–variable problem further serve to strengthen the proposed theory

High-Dimensional Stochastic Design Optimization by Adaptive-Sparse Polynomial Dimensional Decomposition

This paper presents a novel adaptive-sparse polynomial dimensional decomposition (PDD) method for stochastic design optimization of complex systems. The method entails an adaptive-sparse PDD approximation of a high-dimensional stochastic response for statistical moment and reliability analyses; a novel integration of the adaptive-sparse PDD approximation and score functions for estimating the first-order design sensitivities of the statistical moments and failure probability; and standard gradient-based optimization algorithms. New analytical formulae are presented for the design sensitivities that are simultaneously determined along with the moments or the failure probability. Numerical results stemming from mathematical functions indicate that the new method provides more computationally efficient design solutions than the existing methods. Finally, stochastic shape optimization of a jet engine bracket with 79 variables was performed, demonstrating the power of the new method to tackle practical engineering problems.Comment: 18 pages, 2 figures, to appear in Sparse Grids and Applications--Stuttgart 2014, Lecture Notes in Computational Science and Engineering 109, edited by J. Garcke and D. Pfl\"{u}ger, Springer International Publishing, 201

A study of the Haor areas of Sylhet-Mymensing districts with ERTS imageries (winter crop estimation)

There are no author-identified significant results in this report

Distribution system simulator

In a series of tests performed under the Department of Energy auspices, power line carrier propagation was observed to be anomalous under certain circumstances. To investigate the cause, a distribution system simulator was constructed. The simulator was a physical simulator that accurately represented the distribution system from below power frequency to above 50 kHz. Effects such as phase-to-phase coupling and skin effect were modeled. Construction details of the simulator, and experimental results from its use are presented

Structural, Vibrational and Thermodynamic Properties of AgnCu34-n Nanoparticles

We report results of a systematic study of structural, vibrational and thermodynamical properties of 34-atom bimetallic nanoparticles from the AgnCu34-n family using model interaction potentials as derived from the embedded atom method and in the harmonic approximation of lattice dynamics. Systematic trends in the bond length and dynamical properties can be explained largely on arguments based on local coordination and elemental environment. Thus increase in the number of silver atoms in a given neighborhood introduces a monotonic increase in bond length while increase of the copper content does the reverse. Moreover, based on bond lengths of the lowest coordinated (6 and 8) copper atoms with their nearest neighbors (Cu atoms), we find that the nanoparticles divide into two groups with average bond length either close to (~ 2.58 A) or smaller (~ 2.48 A) than that in bulk copper, accompanied by characteristic features in their vibrational density of states. For the entire set of nanoparticles, vibrational modes are found above the bulk bands of copper/silver. Furthermore, a blue shift in the high frequency end with increasing number of copper atoms in the nanoparticles is traced to a shrinkage of bond lengths from bulk values. The vibrational densities of states at the low frequency end of the spectrum scale linearly with frequency as for single element nanoparticles, however, the effect is more pronounced for these nanoalloys. The Debye temperature was found to be about one third of that of the bulk for pure copper and silver nanoparticles with a non-linear increase with increasing number of copper atoms in the nanoalloys.Comment: 37 pages, 12 figure