A charge sharing–based switching scheme for SAR ADCs

This paper presents an energy-efficient switching scheme for successive approximation register (SAR) analogue-to-digital converter (ADC). The proposed scheme employs charge recycling method to keep the capacitor arrays free of transitional energy between bit generations except reset phase. In comparison with the conventional switching scheme, the proposed one achieves 100% transitional energy saving without considering reset phase. In addition, configuration of a 10-bit SAR ADC shows that the proposed switching scheme reduces the capacitor area by 25% compared with the conventional switching scheme.     

A control-theoretic approach to distributed discrete-valued decision-making in networks of sensing agents

We address the problem of global sensor fusion for the purpose of distributed decision-making, from a control-theoretic perspective. In particular, we introduce a quasi-linear stochastic distributed protocol, using which a network of sensing agents can reach agreement in order to take a collective action. Using control-theoretic methods, we design the parameters of our protocol - which include weights in the local update rules used by the agents and a finite stopping time - to achieve agreement in a fair and rapid manner. We show analytically that the developed protocol achieves fair agreement with certainty in the noise-free case and achieves fair agreement with high probability even in the presence of communication noise and assuming very little information storage capability for the agents. Our development is illustrated throughout with a canonical example motivated by autonomous vehicle control.     

Adaptive stabilization of a class of nonlinear systems using high-gain feedback

This note presents a high-gain feedback stabilizing control algorithm in which the high-gain parameter is adapted on-line. The algorithm is developed for a class of nonlinear systems which can be viewed as the nonlinear counterpart of uniform rank systems. The system can be unknown except for a number of vital pieces of information. For single-input single-output linear systems such information is usually required in the traditional adaptive control literature.     

A Detection-Theoretic Model of Echo Inhibition.

A detection-theoretic analysis of the auditory localization of dual-impulse stimuli is described, and a model for the processing of spatial cues in the echo pulse is developed. Although for over 50 years "echo suppression" has been the topic of intense theoretical and empirical study within the hearing sciences, only a rudimentary understanding of its mechanisms has emerged. In this article, psychometric functions and results from matching studies are used in developing a model that specifies the perceived position of the echo pulse as a normal deviate, with an expectation that is a logistic function of the echo delay and a variance that depends on interaural time difference. Loss of information in the echo event is quantified as a decline in the efficiency with which the binaural system receives information from the lag impulse. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Ignite-GPU: a GPU-enabled in-memory computing architecture on clusters

The Journal of Supercomputing - During recent years, big data explosion and the increase in main memory capacity, on the one hand, and the need for faster data processing, on the other hand, have...     

Designing linear distributed algorithms with memory for fast convergence

Motivated by both distributed computation and decentralized control applications, we studied the distributed linear iterative algorithms with memory. Specifically, we showed that the system of linear equations G x = b can be solved through a distributed linear iteration for arbitrary invertible G using only a single memory element at each processor. Further, we demonstrated that the memoried distributed algorithm can be designed to achieve much faster convergence than a memoryless distributed algorithm. Two small simulation examples were included to illustrate the results. Copyright © 2011 John Wiley & Sons, Ltd.     

An integrated fuzzy regression-data envelopment analysis algorithm for optimum oil consumption estimation with ambiguous data

This study introduces an integrated fuzzy regression (FR) data envelopment analysis (DEA) algorithm for oil consumption estimation and optimization with uncertain and ambiguous data. This is quite important as oil consumption estimations deals with several uncertainties due to social, economic factors. Furthermore, DEA is integrated with FR because there is no clear cut as to which FR approach is superior for oil consumption estimation. The standard indicators used in this paper are population, cost of crude oil, gross domestic production (GDP) and annual oil production. Fifteen popular and most cited FR models are considered in the algorithm. Each FR model has different approach and advantages. The input data is divided into train and test data. The FR models have been tuned for all their parameters according to the train data, and the best coefficients are identified. Center of Average Method for defuzzification output process is applied. For determining the rate of error of FR models estimations, the rate of defuzzified output of each model is compared with its actual rate consumption in test data. The efficiency of 15 FR models is examined by the output-oriented Data Envelopment Analysis (DEA) model without inputs by considering three types of relative error: RMSE, MAE and MAPE. The applicability and superiority of the proposed algorithm is shown for monthly oil consumption of Canada, United States, Japan and Australia from 1990 to 2005.     

Squaring down of general MIMO systems to invertible uniform rank systems via pre- and/or post-compensators

Pre- and/or post-compensators are designed to square down a general MIMO system to a uniform rank system, the structure of which is almost similar to a SISO system. The method of squaring down either does not change the finite zero structure of the given MIMO system or simply adds additional finite zeros in the left half s-plane. The significance of such a squaring down lies in the simplicity of the structure of a uniform rank system lending itself for easy analysis and control design.     

Synchronization in heterogeneous networks of discrete‐time introspective right‐invertible agents

This paper studies output synchronization problem, formation problem, and regulated synchronization problem for a heterogenous network of discrete‐time introspective right‐invertible agents. We first propose a decentralized control scheme to solve the output synchronization problem for a set of communication topologies. Moreover, if the synchronization trajectories are assumed to be bounded, a universal controller can be constructed for all communication topologies, which contain a directed spanning tree. The design can be applied to solve the formation problem with arbitrary formation vectors. In the regulated synchronization problem, we assume only the root receives information from exosystem. We then design a decentralized controller to solve the problem for a set of communication topologies. Copyright © 2013 John Wiley & Sons, Ltd.