(SoE) School of Engineering

<p>Shiv Nadar University is a comprehensive, multidisciplinary, research-focused, and student-centric University offering a full range of academic programs at the undergraduate, postgraduate and doctoral level. With state-of-the-art infrastructure, the University comprises of academic wings, sophisticated labs, international standard sports facilities, amphitheaters, auditorium, conference rooms and smart classrooms. The University&rsquo;s goal is to become internationally recognized for the quality of its research and creative endeavors and their applicability to improving quality of life, generating new insights and expanding the boundaries of human knowledge creativity. Committed to excellence in teaching, research and service, the University aims to serve the higher education needs of India and the world beyond.</p>

Shiv Nadar University

Proton-exchanged (PE) regions in LiNbO3 create an invisible inhomogeneity that can be used as surface acoustic wave (SAW) reflectors similar to metallized overlays, implanted layers, or grooves. We report the detection of coherently reflected SAW, from a dispersive array of proton-exchanged dot rows, by utilizing a sensitive interferometric heterodyne laser probe.© 1995 American Institute of Physics.

Electrical Engineering

World University root node

Fulltext

Applied Physics Letters

Surface acoustic wave reflections from a proton exchanged dispersive dot array

In this letter we demonstrate that a photothermal microscopy experiment can be used to determine the electronic diffusivity (or carrier mobility) in the same way it is now widely used to measure locally thermal diffusivity of various nonsemiconductor materials. The main difficulty lies in the fact that in order to separate thermal and carrier diffusion, the experiment must be performed for a relatively large distance between the pump and probe beams. Photothermal signals are therefore rather weak and great experimental care must be taken. We present and discuss experimental results on Si. © 1996 American Institute of Physics.

Electronic diffusivity measurement in silicon by photothermal microscopy

We show that any parallel algorithm in the fixed degree algebraic decision tree model that answers membership queries in W⊆ Rn using p processors, requires Ω (|W|/nlog(p/n)) rounds where |W| is the number of connected components of W. We further prove a similar result for the average case complexity. We give applications of this result to various fundamental problems in computational geometry like convex-hull construction and trapezoidal decomposition and also present algorithms with matching upper bounds. © 1994, Springer Verlag. All rights reserved.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Lower bounds for parallel algebraic decision trees, complexity of convex hulls and related problems

This paper presents a neural network based control scheme for robot tracking applications. Gaussian networks are used to model both the forward and the inverse dynamics of a robot arm. The feedforward torque is actuated by the output of inverse dynamic mapping while the feedback control law is derived using the linear perturbation model of the identified forward dynamics along the desired trajectory. The gradient based learning algorithm is used and the effectiveness of the proposed scheme is highlighted through simulation studies. © 1994.

Robotics and Autonomous Systems

Trajectory tracking of robot manipulator using Gaussian networks

The effect of row withdrawal in surface acoustic wave reflective dot array dispersive delay lines has been investigated, and the simulated multifrequency, constant fractional chirp bandwidth operation of such a device has been experimentally validated. Utilizing appropriate input/output interdigital transducers, the approach enables higher frequency and increased time‐bandwidth product operation of reflective array devices, with relaxed mask‐making and lithography constraints. © 1994 John Wiley & Sons, Inc. Copyright © 1994 Wiley Periodicals, Inc., A Wiley Company

Microwave and Optical Technology Letters

Characteristics of row withdrawn surface acoustic wave reflective dot dispersive delay lines

An automated system for the pyroelectric imaging of polar substrates has been developed. The principle of operation, details of the optical and mechanical subsystems, and a description of the system hardware, interface, and software for data acquisition and display are given. The automation has made possible routine scans of high resolution and/or large areas of pyroelectric materials, such as LiNbO3 and ZnO. Features of the system are highlighted by means of a first ever reported pyroelectric imaging of proton-exchanged LiNbO3, which is an important material for optical waveguides. © 1994 IEEE

IEEE Transactions on Instrumentation and Measurement

An Automated Nondestructive Characterization System for Pyroelectric Materials

We present an O((m + n)√n log n) time algorithm to select the k th smallest item from an m × n totally monotone matrix for any k ≤ ran. This is the first subquadratic algorithm for selecting an item from a totally monotone matrix. Our method also yields an algorithm for generalized row selection in monotone matrices of the same time complexity. Given a set S = {p1, …, pn} of n points in convex position and a vector k = {k1, …, kn}, we also present an O(n4/3 logO(1) n) algorithm to compute the kith nearest neighbor of pi for every i ≤ n; c is an appropriate constant. This algorithm is considerably faster than the one based on a row-selection algorithm for monotone matrices. If the points of S are arbitrary, then the kith h nearest neighbor of pi, for all i ≤ n, can be computed in time O(n7/5 logc n), which also improves upon the previously best-known result. © 1994, Springer Verlag. All rights reserved.

Selection in monotone matrices and computing kth nearest neighbors

A unified study of adaptive control and neural network based control schemes for the trajectory tracking problem of robot manipulators is presented. Efficacy of parametrized adaptive algorithms in compensating the structured uncertainties in robot dynamics is verified through extensive simulation. The ability of neural networks to provide a robust adaptive framework in the presence of both structured and unstructured uncertainties is investigated. A case study is carried out in support of a parametrized adaptive scheme using neural networks. Simulation results clearly indicate that the neural network based adaptive controller achieves better tracking in the presence of parametric uncertainties as well as unmodelled effects compared to the simple direct adaptive scheme. © 1994 Taylor & Francis Group, LLC.

International Journal of Systems Science

Adaptive manipulator trajectory control using neural networks

For the trajectory-tracking problem of robot manipulators various decentralized control schemes are investigated in this paper. These control schemes result in poor tracking performance in case of large payload variations. A compensation scheme using an error-data knowledge base is developed to improve the performance robustness. © 1993.

On robustness of decentralized control for robot manipulators

For representing the input-output behaviour of a robot manipulator by a linear time-invariant model, four direct linearization schemes are: (i) state linearization, (ii) linearization based on an identification method, (iii) linearization based on neglecting velocity-dependent and gravity terms and (iv) linearization based on neglecting the velocity-dependent term only (rate linearization). In order to make an appropriate choice of linear model for the development of real-time control, these schemes are extensively studied in this paper. It is shown that the rate linearization method leads to a satisfactory tradeoff between computation, accuracy, and stability. In the case of high velocity motions, a combination of state linearization and rate linearization is proposed. © 1993 Kluwer Academic Publishers.