Jai Narayan Tripathi

Bio: Jai Narayan Tripathi is an academic researcher from Indian Institute of Technology, Jodhpur. The author has contributed to research in topics: Jitter & Power integrity. The author has an hindex of 9, co-authored 65 publications receiving 247 citations. Previous affiliations of Jai Narayan Tripathi include STMicroelectronics & Indian Institutes of Technology.

Uncertainty Quantification of RF Circuits Using Stochastic Collocation Techniques

Abstract: This paper presents a study on the Polynomial Chaos based approach for uncertainty quantification. It discusses employing different polynomial chaos based techniques for uncertainty quantification of RF circuits. Here, the performance of different Stochastic Collocation techniques such as the pseudo-spectral projection, linear regression, and interpolation technique, is investigated using two illustrative circuit examples. The first example deals with the uncertainty quantification of phase noise in a 2.4 GHz CMOS LC tank oscillator, while in the second one, gain of a 2.4 GHz low-noise amplifier is analyzed in the presence of uncertainty. The applied techniques are investigated and compared with the traditional Monte Carlo simulations approach. The advantages and disadvantages of each of the presented techniques are discussed, which are validated using the illustrations. The results of our study provide guidance for choosing the appropriate technique for modeling and quantifying uncertainty for similar circuits.

Analysis of power supply noise in AMS circuits including the effects of interconnects using estimation by inspection method

Abstract: This paper presents the analysis of on-chip analog and mixed signal (AMS) circuits in the presence of supply noise, on- and off-chip interconnect effects. The estimation-by-inspection method is extended to analyze the performance metrics of the AMS circuits. For the purpose of validation, two different examples are considered, designed in UMC 130 nm and Lfoundry 180 nm technology-nodes. The mean percentage error (MPE) between electronic design automation (EDA) simulations and analytical results using the proposed method is less than 10% for various performance metrics of an AMS system. A speed-up factor of 9 has been achieved using the proposed method as compared to the EDA simulations.

An Automated Framework for Variability Analysis using Simulated Annealing

Abstract: In the design process of integrated circuits, design and process variability plays an important role in the performance of the circuits. In this paper, an automated framework for Variability Analysis of CMOS circuits is proposed using simulated annealing algorithm. A practical study of variability analysis of phase noise in a 2.4 GHz CMOS oscillator is illustrated using this framework. The performance for the proposed framework for Variability Analysis application is validated by comparing it with the conventional Monte Carlo simulations. A significant gain in terms of computational time is reported.

Zero power 4.95Gbps HDMI transmitter

Abstract: The HDMI open drain transmitter is designed to harvest power from the receiver, through the termination impedances during signaling. There is no local power supply needed at the transmitter side, neither any power is taken from the receiver apart from whatever power comes out of it during standard signaling. The zero power HDMI Transmitter capable of datarate 4.95Gbps, i.e. 1.65Gbps per Channel is designed in 65nm technology.

A case study of BGA package for high speed channel with non-ideal ground induced resonance conditions

Abstract: Proper transmission of high speed signal requires sufficiently high bandwidth of the medium. The reference planes play a vital role in achieving distortion-free signal propagation. In this paper a BGA package design exhibiting resonance conditions in insertion loss is analyzed. Analysis led to ground path issues caused by return current density congestions. Improvement in ground return path layout led to elimination of resonance conditions. Re-designed package is meeting the intended design target for HDMI 2.0 standards.

The Design and Analysis of Experiments

Abstract: THE DESIGN AND ANALYSIS OF EXPERIMENTS. By Oscar Kempthorne. New York, John Wiley and Sons, Inc., 1952. 631 pp. $8.50. This book by a teacher of statistics (as well as a consultant for \"experimenters\") is a comprehensive study of the philosophical background for the statistical design of experiment. It is necessary to have some facility with algebraic notation and manipulation to be able to use the volume intelligently. The problems are presented from the theoretical point of view, without such practical examples as would be helpful for those not acquainted with mathematics. The mathematical justification for the techniques is given. As a somewhat advanced treatment of the design and analysis of experiments, this volume will be interesting and helpful for many who approach statistics theoretically as well as practically. With emphasis on the \"why,\" and with description given broadly, the author relates the subject matter to the general theory of statistics and to the general problem of experimental inference. MARGARET J. ROBERTSON

Logical Effort Designing Fast Cmos Circuits

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An Adaptive Particle Swarm Optimization Algorithm Based on Directed Weighted Complex Network

Abstract: The disadvantages of particle swarm optimization (PSO) algorithm are that it is easy to fall into local optimum in high-dimensional space and has a low convergence rate in the iterative process. To deal with these problems, an adaptive particle swarm optimization algorithm based on directed weighted complex network (DWCNPSO) is proposed. Particles can be scattered uniformly over the search space by using the topology of small-world network to initialize the particles position. At the same time, an evolutionary mechanism of the directed dynamic network is employed to make the particles evolve into the scale-free network when the in-degree obeys power-law distribution. In the proposed method, not only the diversity of the algorithm was improved, but also particles’ falling into local optimum was avoided. The simulation results indicate that the proposed algorithm can effectively avoid the premature convergence problem. Compared with other algorithms, the convergence rate is faster.

Analyzing Convergence and Rates of Convergence of Particle Swarm Optimization Algorithms Using Stochastic Approximation Methods

Abstract: Recently, much progress has been made on particle swarm optimization (PSO). A number of works have been devoted to analyzing the convergence of the underlying algorithms. Nevertheless, in most cases, rather simplified hypotheses are used. For example, it often assumes that the swarm has only one particle. In addition, more often than not, the variables and the points of attraction are assumed to remain constant throughout the optimization process. In reality, such assumptions are often violated. Moreover, there are no rigorous rates of convergence results available to date for the particle swarm, to the best of our knowledge. In this paper, we consider a general form of PSO algorithms, and analyze asymptotic properties of the algorithms using stochastic approximation methods. We introduce four coefficients and rewrite the PSO procedure as a stochastic approximation type iterative algorithm. Then we analyze its convergence using weak convergence method. It is proved that a suitably scaled sequence of swarms converge to the solution of an ordinary differential equation. We also establish certain stability results. Moreover, convergence rates are ascertained by using weak convergence method. A centered and scaled sequence of the estimation errors is shown to have a diffusion limit.