R. Lugannani

1.0k total citations · 1 hit paper
16 papers, 736 citations indexed

About

R. Lugannani is a scholar working on Artificial Intelligence, Statistics and Probability and Computer Vision and Pattern Recognition. According to data from OpenAlex, R. Lugannani has authored 16 papers receiving a total of 736 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Artificial Intelligence, 4 papers in Statistics and Probability and 3 papers in Computer Vision and Pattern Recognition. Recurrent topics in R. Lugannani's work include Bayesian Methods and Mixture Models (3 papers), Probability and Risk Models (3 papers) and Image and Signal Denoising Methods (2 papers). R. Lugannani is often cited by papers focused on Bayesian Methods and Mixture Models (3 papers), Probability and Risk Models (3 papers) and Image and Signal Denoising Methods (2 papers). R. Lugannani collaborates with scholars based in United States. R. Lugannani's co-authors include Stephen A. Rice, John B. Thomas, S. O. Rice and On-Ching Yue and has published in prestigious journals such as Journal of Computational Physics, IEEE Transactions on Information Theory and Journal of the Franklin Institute.

In The Last Decade

R. Lugannani

16 papers receiving 652 citations

Hit Papers

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What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Saddle point approximation for the distribution of the sum of independent random variables

1980 536 citations R. Lugannani, Stephen A. Rice Advances in Applied Probability profile →

Peers

Countries citing papers authored by R. Lugannani

Since Specialization

Citations

This map shows the geographic impact of R. Lugannani's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by R. Lugannani with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites R. Lugannani more than expected).

Fields of papers citing papers by R. Lugannani

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by R. Lugannani. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by R. Lugannani. The network helps show where R. Lugannani may publish in the future.

Co-authorship network of co-authors of R. Lugannani

This figure shows the co-authorship network connecting the top 25 collaborators of R. Lugannani. A scholar is included among the top collaborators of R. Lugannani based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with R. Lugannani. R. Lugannani is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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16 of 16 papers shown

#	Work	Indexed citations
1	Distribution of the sample magnitude-squared coherence obtained using overlapped Fourier transforms 2005 ·R. Lugannani	2
2	Optically phase-locked electronic speckle pattern interferometer system performance for vibration measurement in random displacement fields 1989 ·Journal of the Optical Society of America A ·(unknown), R. Lugannani, (unknown), (unknown)	5
3	Distribution of the Ratio of Quadratic Forms in Normal Variables—Numerical Methods 1984 ·SIAM Journal on Scientific and Statistical Computing ·R. Lugannani, S. O. Rice	6
4	Numerical evaluation of a class of integrals by integrating along a string of saddle points 1981 ·Journal of Computational Physics ·R. Lugannani, S. O. Rice	3
5	Saddle point approximation for the distribution of the sum of independent random variables 1980 ·Advances in Applied Probability ·R. Lugannani, Stephen A. Rice	67
6	Saddle point approximation for the distribution of the sum of independent random variables breakdown → 1980 ·Advances in Applied Probability ·R. Lugannani, Stephen A. Rice	536
7	Use of Gaussian convergence factors in the numerical evaluation of slowly converging integrals 1980 ·Journal of Computational Physics ·R. Lugannani, Stephen A. Rice	3
8	Sample Function Regularity of Shot Processes 1978 ·SIAM Journal on Applied Mathematics ·R. Lugannani	5
9	Series Approximations for the Amplitude Distribution and Density of Shot Processes 1978 ·IRE Transactions on Communications Systems ·On-Ching Yue, R. Lugannani, Stephen A. Rice	9
10	Approximate likelihood ratio detectors for linear processes 1977 ·IEEE Transactions on Information Theory ·(unknown), R. Lugannani	7
11	Sample Stability of Periodically Correlated Pulse Trains 1973 ·Journal of the Franklin Institute ·R. Lugannani	3
12	Convergence Properties of the Sample Mean and Sample Correlation for a Class of Pulse Trains 1971 ·SIAM Journal on Applied Mathematics ·R. Lugannani	5
13	Intersymbol interference and probability of error in digital systems 1969 ·IEEE Transactions on Information Theory ·R. Lugannani	69
14	The central limit theorem for a class of stochastic processes 1968 ·Journal of Mathematical Analysis and Applications ·R. Lugannani, John B. Thomas	3
15	A probability inequality for band-limited pulse trains 1968 ·IEEE Transactions on Information Theory ·R. Lugannani	1
16	On a class of stochastic processes which are closed under linear transformations 1967 ·Information and Control ·R. Lugannani, John B. Thomas	12

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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