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 Pramod K Varshney

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Average citations per article13.00
Citation Count1,417
Publication count109
Publication years1979-2017
Available for download5
Average downloads per article1,645.20
Downloads (cumulative)8,226
Downloads (12 Months)228
Downloads (6 Weeks)25
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109 results found Export Results: bibtexendnoteacmrefcsv

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1
July 2017 IEEE Transactions on Information Forensics and Security: Volume 12 Issue 7, July 2017
Publisher: IEEE Press
Bibliometrics:
Citation Count: 0

In this paper, we revisit the received signal strength (RSS)-based target localization technique presented in Vempaty et al. , where a simple threshold quantizer was employed to quantize the RSS values prior to sending them to the fusion center. It was shown that the probability of misclassification of the distributed ...

2 published by ACM
April 2017 SocialSens'17: Proceedings of the 2nd International Workshop on Social Sensing
Publisher: ACM
Bibliometrics:
Citation Count: 0
Downloads (6 Weeks): 7,   Downloads (12 Months): 33,   Downloads (Overall): 33

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We explore the design of an effective crowdsourcing system for an M-ary classification task. Crowd workers complete simple binary microtasks whose results are aggregated to give the final classification decision. We consider the scenario where the workers have a reject option so that they are allowed to skip microtasks when ...
Keywords: distributed inference, Classification, reject option, confidence reporting, crowdsourcing, information fusion

3
February 2017 IEEE Transactions on Signal Processing: Volume 65 Issue 4, February 2017
Publisher: IEEE Press
Bibliometrics:
Citation Count: 1

Consider designing an effective crowdsourcing system for $M$ -ary classification where crowd workers complete simple binary microtasks, which are aggregated to give the final result. We consider the novel scenario where workers have a reject option, so they may skip microtasks they are unable or unwilling to do. For ...

4
December 2016 IEEE Transactions on Wireless Communications: Volume 15 Issue 12, December 2016
Publisher: IEEE Press
Bibliometrics:
Citation Count: 0

In this paper, we address the constrained resource allocation problems arising in the context of spectrum sharing in cognitive radio networks utilizing a multi-dimensional formulation. Given the activity of the primary users (PUs), we consider multiple objectives and constraints, viz., sum rate, fairness, number of active secondary users (SUs), power ...

5
December 2016 IEEE Transactions on Signal Processing: Volume 64 Issue 24, December 2016
Publisher: IEEE Press
Bibliometrics:
Citation Count: 0

In this paper, we aim to design the optimal sensor collaboration strategy for the estimation of time-varying parameters, where collaboration refers to the act of sharing measurements with neighboring sensors prior to transmission to a fusion center. We begin by addressing the sensor collaboration problem for the estimation of uncorrelated ...

6
May 2016 IEEE Transactions on Signal Processing: Volume 64 Issue 10, May 2016
Publisher: IEEE Press
Bibliometrics:
Citation Count: 0

In this paper, we investigate the design of distributed detection networks in the presence of an eavesdropper (Eve). We consider the problem of designing binary sensor quantizers that maximize the Kullback-Leibler (KL) divergence at the fusion center (FC), when subject to a tolerable constraint on the KL divergence at Eve. ...

7
April 2016 IEEE Transactions on Signal Processing: Volume 64 Issue 7, April 2016
Publisher: IEEE Press
Bibliometrics:
Citation Count: 0

We consider the problem of collaborative inference in a sensor network with heterogeneous and statistically dependent sensor observations. Each sensor aims to maximize its inference performance by forming a coalition with other sensors and sharing information within the coalition. In this paper, the formation of non-overlapping coalitions with statistically dependent ...

8
June 2014 IEEE Transactions on Signal Processing: Volume 62 Issue 12, June 2014
Publisher: IEEE Press
Bibliometrics:
Citation Count: 1

We consider the problem of finding optimal time-periodic sensor schedules for estimating the state of discrete-time dynamical systems. We assume that multiple sensors have been deployed and that the sensors are subject to resource constraints, which limits the number of times each can be activated over one period of the ...

9
June 2014 IEEE Transactions on Signal Processing: Volume 62 Issue 12, June 2014
Publisher: IEEE Press
Bibliometrics:
Citation Count: 1

In this paper, we consider the problem of distributed detection in tree topologies in the presence of Byzantines. The expression for minimum attacking power required by the Byzantines to blind the fusion center (FC) is obtained. More specifically, we show that when more than a certain fraction of individual node ...

10
May 2014 IEEE Transactions on Signal Processing: Volume 62 Issue 10, May 2014
Publisher: IEEE Press
Bibliometrics:
Citation Count: 0

The problem of distributed inference with M-ary quantized data at the sensors is investigated in the presence of Byzantine attacks. We assume that the Byzantine nodes attack the inference network by modifying the symbol corresponding to the quantized data to one of the other symbols in the quantization alphabet-set and ...

11
May 2014 IEEE Transactions on Signal Processing: Volume 62 Issue 10, May 2014
Publisher: IEEE Press
Bibliometrics:
Citation Count: 1

In this paper, a new framework for sequential Bayesian estimation in sensor networks is proposed, which consists of two processes: censoring of measurements at local sensors and fusion of both received measurements and missing ones at the fusion center (FC). In our scheme, each local sensor maintains a Kalman filter ...

12
March 2014 Digital Signal Processing: Volume 26, March, 2014
Publisher: Academic Press, Inc.
Bibliometrics:
Citation Count: 1

An M-ary communication system is considered in which the transmitter and the receiver are connected via multiple additive (possibly non-Gaussian) noise channels, any one of which can be utilized for the transmission of a given symbol. Contrary to deterministic signaling (i.e., employing a fixed constellation), a stochastic signaling approach is ...
Keywords: Detection, M-ary communications, Channel switching, Error probability, Non-Gaussian, Stochastic signaling

13
January 2014 IEEE Transactions on Information Theory: Volume 60 Issue 1, January 2014
Publisher: IEEE Press
Bibliometrics:
Citation Count: 2

In this paper, we consider the task of target localization using quantized data in wireless sensor networks. We propose a computationally efficient localization scheme by modeling it as an iterative classification problem. We design coding theory based iterative approaches for target localization where at every iteration, the fusion center (FC) ...

14
January 2014 IEEE Transactions on Signal Processing: Volume 62 Issue 2, January 2014
Publisher: IEEE Press
Bibliometrics:
Citation Count: 2

In this paper, sensor selection problems for target tracking in large sensor networks with linear equality or inequality constraints are considered. First, we derive an equivalent Kalman filter for sensor selection, i.e., generalized information filter. Then, under a regularity condition, we prove that the multistage look-ahead policy that minimizes either ...

15
January 2014 Automatica (Journal of IFAC): Volume 50 Issue 1, January, 2014
Publisher: Pergamon Press, Inc.
Bibliometrics:
Citation Count: 1

In this paper, we consider the distributed maximum likelihood estimation (MLE) with dependent quantized data under the assumption that the structure of the joint probability density function (pdf) is known, but it contains unknown deterministic parameters. The parameters may include different vector parameters corresponding to marginal pdfs and parameters that ...
Keywords: Wireless sensor networks, Distributed estimation, Fisher information matrix, Maximum likelihood estimation

16
June 2013 IEEE Transactions on Information Theory: Volume 59 Issue 6, June 2013
Publisher: IEEE Press
Bibliometrics:
Citation Count: 0

A power-constrained sensor network that consists of multiple sensor nodes and a fusion center (FC) is considered, where the goal is to estimate a random parameter of interest. In contrast to the distributed framework, the sensor nodes may be partially connected, where individual nodes can update their observations by (linearly) ...

17
June 2013 IEEE Transactions on Signal Processing: Volume 61 Issue 11, June 2013
Publisher: IEEE Press
Bibliometrics:
Citation Count: 0

This paper considers a collaborative human decision making framework in which local decisions made at the individual agents are combined at a moderator to make the final decision. More specifically, we consider a binary hypothesis testing problem in which a group of $n$ people makes individual decisions on which hypothesis ...

18
March 2013 IEEE Transactions on Signal Processing: Volume 61 Issue 6, March 2013
Publisher: IEEE Press
Bibliometrics:
Citation Count: 9

Wireless Sensor Networks (WSNs) are vulnerable to Byzantine attacks in which malicious sensors send falsified information to the Fusion Center (FC) with the goal of degrading inference performance. In this paper, we consider Byzantine attacks for the location estimation task in WSNs using binary quantized data. Posterior Cramér-Rao Lower Bound ...

19
October 2012 IEEE Transactions on Signal Processing: Volume 60 Issue 10, October 2012
Publisher: IEEE Press
Bibliometrics:
Citation Count: 0

In this paper, we study the target tracking problem in wireless sensor networks (WSNs) using quantized sensor measurements where the total number of bits that can be transmitted from sensors to the fusion center is limited. At each time step of tracking, a total of $R$ available bits need to ...

20
October 2012 IEEE Transactions on Signal Processing: Volume 60 Issue 10, October 2012
Publisher: IEEE Press
Bibliometrics:
Citation Count: 1

We seek to characterize the estimation performance of a sensor network where the individual sensors exhibit the phenomenon of drift, i.e., a gradual change of the bias. Though estimation in the presence of random errors has been extensively studied in the literature, the loss of estimation performance due to systematic ...



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