Institution
Stevens Institute of Technology
Education•Hoboken, New Jersey, United States•
About: Stevens Institute of Technology is a education organization based out in Hoboken, New Jersey, United States. It is known for research contribution in the topics: Computer science & Cognitive radio. The organization has 5440 authors who have published 12684 publications receiving 296875 citations. The organization is also known as: Stevens & Stevens Tech.
Topics: Computer science, Cognitive radio, Communication channel, Wireless network, Artificial neural network
Papers published on a yearly basis
Papers
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TL;DR: There has been a controversy over the TiO(2) PCO mechanisms of arsenite for the past 10 years but the adsorption mechanisms of inorganic and organic arsenic onto TiO (2)-based materials are relatively well established.
328 citations
TL;DR: Simulation results show that the proposed method can provide an accurate channel estimate and achieve a substantial training overhead reduction and the inherent sparsity in mmWave channels is exploited.
Abstract: In this letter, we consider channel estimation for intelligent reflecting surface (IRS)-assisted millimeter wave (mmWave) systems, where an IRS is deployed to assist the data transmission from the base station (BS) to a user. It is shown that for the purpose of joint active and passive beamforming, the knowledge of a large-size cascade channel matrix needs to be acquired. To reduce the training overhead, the inherent sparsity in mmWave channels is exploited. By utilizing properties of Katri-Rao and Kronecker products, we find a sparse representation of the cascade channel and convert cascade channel estimation into a sparse signal recovery problem. Simulation results show that our proposed method can provide an accurate channel estimate and achieve a substantial training overhead reduction.
327 citations
TL;DR: Stochastic optimization problems involving stochastic dominance constraints are introduced and necessary and sufficient conditions of optimality and duality theory are developed and it is shown that the Lagrange multipliers corresponding to dominance constraint are concave nondecreasing utility functions.
Abstract: We introduce stochastic optimization problems involving stochastic dominance constraints. We develop necessary and sufficient conditions of optimality and duality theory for these models and show that the Lagrange multipliers corresponding to dominance constraints are concave nondecreasing utility functions. The models and results are illustrated on a portfolio optimization problem.
327 citations
TL;DR: In this paper, the microstructure and mechanical properties of nanograin-sized WC-Co composites were investigated and compared with those of conventional cermets, and it was shown that the nanostructured composites have higher tungsten content in the binder phase and a higher FCC HCP ratio of the cobalt.
325 citations
TL;DR: In this paper, the authors introduce the notion of Dymanic Order and Choas (DOC) for the stochastic layer of a stochastically ordered graph, and describe two types of spatial patterns: two-dimensional hydrodynamic patterns with symmetry and quasi-symmetry.
Abstract: Part I. General Concepts: Hamiltonian dynamics Stability and chaos Part II. Dymanic Order and Choas: The stochastic layer Stochastic layer - stochastic sea transition The stochastic web Uniform web Part III. Spatial Patterns: Two-dimensional patterns with quasi-symmetry Two-dimensional hydrodynamic patterns with symmetry and quasi-symmetry Chaos and streamlines Part IV. Miscellanea: Patterns in art and nature References Index.
325 citations
Authors
Showing all 5536 results
| Name | H-index | Papers | Citations |
|---|---|---|---|
| Paul M. Thompson | 183 | 2271 | 146736 |
| Roger Jones | 138 | 998 | 114061 |
| Georgios B. Giannakis | 137 | 1321 | 73517 |
| Li-Jun Wan | 113 | 639 | 52128 |
| Joel L. Lebowitz | 101 | 754 | 39713 |
| David Smith | 100 | 994 | 42271 |
| Derong Liu | 77 | 608 | 19399 |
| Robert R. Clancy | 77 | 293 | 18882 |
| Karl H. Schoenbach | 75 | 494 | 19923 |
| Robert M. Gray | 75 | 371 | 39221 |
| Jin Yu | 74 | 480 | 32123 |
| Sheng Chen | 71 | 688 | 27847 |
| Hui Wu | 71 | 347 | 19666 |
| Amir H. Gandomi | 67 | 375 | 22192 |
| Haibo He | 66 | 482 | 22370 |