S. S. Iyengar

Florida International University

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Vir V. Phoha

Syracuse University

Kianoosh G. Boroojeni

Florida International University

Nageswara S. V. Rao

Oak Ridge National Laboratory

M. Hadi Amini

Florida International University

K. R. Venugopal

Bangalore University

L.M. Patnaik

KIIT University

Rajkumar Buyya

University of Melbourne

Niki Pissinou

Florida International University

S Raghavendra

Manipal Academy of Higher Education

L.M. Patnaik

National Institute of Advanced Studies

Cooperative Institutions

Louisiana State University

Florida International University

Bangalore University

Visvesvaraya Technological University

University of Miami

Chinese Academy of Sciences

Chinese Academy of Medical Sciences & Peking Union Medical College

Louisiana State University Agricultural Center

Indian Institute of Science Bangalore

Shanghai Jiao Tong University

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Defuzzification method for a faster and more accurate control

Salil K. Sanyal S. S. Iyengar Amartya Roy N.N. Karnik N. M. Mengale

Fuzzy control is achieved by formulating a rule-base which is based on experience gathered by human operators. Those systems which cannot be modeled mathematically benefit most from a fuzzy control strategy since the imprecise data can he captured using linguistic variables in the rule-base. Fuzzy logic has certain disadvantages. The number of computations required for arriving at a certain output response for given inputs is very large and thus the system response is sluggish. Therefore to adapt fuzzy systems to real-time applications one needs to use faster algorithms and/or parallel processing. Also the process of defuzzification required to produce a single output value may lead to errors which can undo the advantages of fine control normally achievable using fuzzy logic. Special analytical techniques ensure that the complications of the defuzzification process are simplified; the method used retains the desirable features of fuzzy control. This paper aims to present a comparison between the conventional fuzzy controller and a fuzzy logic controller based on the techniques mentioned above.< >

Defuzzification

Fuzzy associative matrix

Base (topology)

Fuzzy rule

Fuzzy electronics

10.1109/tencon.1993.320496

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Citations (1)

Distributed algorithms for locating centers and medians in communication networks

Mohan Sharma Jianhua Chen S. S. Iyengar

Article Free Access Share on Distributed algorithms for locating centers and medians in communication networks Authors: Mohan Sharma IBM Corporation, 11400 Burnet Road, Zip 9640, Austin, TX IBM Corporation, 11400 Burnet Road, Zip 9640, Austin, TXView Profile , Jianhua Chen Department of Computer Science, Louisiana State University, Baton Rouge, LA Department of Computer Science, Louisiana State University, Baton Rouge, LAView Profile , Sitharama Iyengar Department of Computer Science, Louisiana State University, Baton Rouge, LA Department of Computer Science, Louisiana State University, Baton Rouge, LAView Profile Authors Info & Claims SAC '92: Proceedings of the 1992 ACM/SIGAPP symposium on Applied computing: technological challenges of the 1990'sMarch 1992 Pages 808–817https://doi.org/10.1145/130069.130093Online:01 March 1992Publication History 1citation216DownloadsMetricsTotal Citations1Total Downloads216Last 12 Months1Last 6 weeks1 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteeReaderPDF

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IBM

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10.1145/130069.130093

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Distributed decision fusion under unknown distributions

Optical Engineering (1996)

Nageswara S. V. Rao S. S. Iyengar

The problem of distributed decision fusion is studied in the case when the probability distributions of the individual detectors are not available. The detector system is available so that a training sample can be generated by sensing objects with known parameters or classification. Earlier solutions to this problem required some knowledge of the error distributions of the detectors, for example, either in a parametric form or in a closed analytical form. Here we present three methods that, given a sufficiently large training sample, yield an approximation to the optimal fusion rule with an arbitrary level of confidence. These methods are based on (i) empirical estimation, (ii) approximate decision rule, and (iii) nearest-neighbor rule. We show that a nearest-neighbor rule provides a computationally viable solution, which approximates a neural network-based one while ensuring fast computation. {copyright} {ital 1996 Society of Photo{minus}Optical Instrumentation Engineers.}

Optical engineering

10.1117/1.600635

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Citations (16)

Scalable Infrastructure for Distributed Sensor Networks

Springer eBooks (2005)

Krishnendu Chakrabarty S. S. Iyengar

10.1007/1-84628-213-6

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Citations (38)

Query Recommendation based on Query Relevance Graph.

Transactions on machine learning and data mining (2016)

D. Sejal K. G. Shailesh V. Tejaswi D.K. Anvekar K. R. Venugopal

Relevance

RDF query language

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Robot navigation in unknown terrains of convex polygonal obstacles using learned visibility graphs

National Conference on Artificial Intelligence (1986)

B. John Oommen S. S. Iyengar Nageswara S. V. Rao R.L. Kashyap

The problem of navigating an autonomous mobile robot through an unexplored terrain of obstacles is the focus of this paper. The case when the obstacles are 'known' has been extensively studied in literature. The process of robot navigation in completely unexplored terrains involves both learning the information about the obstacle terrain and path planning. We present an algorithm to navigate a point robot in an unexplored terrain that is arbitrarily populated with disjoint convex polygonal obstacles in the plane. The navigation process is constituted by a number of traversals; each traversal is from an arbitrary source point to an arbitrary destination point. Initially, the terrain is explored using a sensor and the paths of traversal made may be sub-optimal. The visibility graph that models the obstacle terrain is incrementally constructed by integrating the information about the paths traversed so far. At any stage of learning, the partially learnt terrain model is represented as a learned visibility graph, and it is updated after each traversal. The proposed algorithm is proven to yield a convergent solution to each path of traversal. It is also shown that the learned visibility graph converges to the visibility graph with probability one, when the source and destination points are chosen randomly. Ultimately, the availability of the complete visibility graph enables the robot to plan globally optimal paths, and also obviates the further usage of sensors.

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Mobile User Data Privacy

Springer eBooks (2016)

Kianoosh G. Boroojeni M. Hadi Amini S. S. Iyengar

10.1007/978-3-319-45050-6_7

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Automatic correlation and calibration of noisy sensor readings using elite genetic algorithms

Artificial Intelligence (1996)

Richard R. Brooks S. S. Iyengar J. Chen

10.1016/0004-3702(96)00012-4

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Citations (49)

<title>Morphological edge detection for oceanographic images</title>

Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE (1994)

Shantha Krishnamurthy S. S. Iyengar Ronald J. Holyer Matthew Lybanon

Mesoscale oceanographic features are important aspects of ocean circulation. The high volume of satellite-derived oceanographic data coupled with the high level of human skill associated with the detection of oceanographic features in the data has necessitated automating the interpretation process. Morphological edge detectors produce better results than the conventional template- and differentiation-based edge detectors. A grayscale morphological edge-detection algorithms is developed for automatic delineation of mesoscale structure in digital satellite IR images of the ocean. We compare performances of three morphological edge detectors in sea surface temperature fields. We provide experimental results on images from the North Atlantic under various image settings.

10.1117/12.169465

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Design concept and motion planning of a single-moduled autonomous pipeline exploration robot

Jong-Hoon Kim Gokarna Sharma S. S. Iyengar

In this paper, we present the design concept and motion planning of a single-moduled fully autonomous mobile pipeline exploration robot that can be used for the inspection of Φ130~150mm pipelines. In this robot, the four straight wall-press caterpillar wheels are fixed 90 degrees apart in its circumstance and each wheel is operated by two DC motors integrated in it. The speed of each wheel is controlled independently to provide steering capability to go through 45 degree elbows, 90 degree elbows, T-branches, and Y-branches. The robot system has been developed and experimented in different pipeline layouts for the validation of its design concept and motion planning mechanism.

10.1109/iecon.2010.5675462

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Citations (9)