Search Results - "Ramezani Mayiami, Mahmoud"

Perfect secrecy via compressed sensing by Ramezani Mayiami, Mahmoud, Seyfe, Babak, Bafghi, Hamid G.

“…In this paper we consider the compressive sensing based encryption and proposed the conditions in which the perfect secrecy is achievable. We prove that when…”
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Bayesian Topology Learning and noise removal from network data by Ramezani Mayiami, Mahmoud, Hajimirsadeghi, Mohammad, Skretting, Karl, Dong, Xiaowen, Blum, Rick S., Poor, H. Vincent

“…Learning the topology of a graph from available data is of great interest in many emerging applications. Some examples are social networks, internet of things…”
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Correction to: Bayesian Topology Learning and noise removal from network data by Ramezani-Mayiami, Mahmoud, Hajimirsadeghi, Mohammad, Skretting, Karl, Dong, Xiaowen, Blum, Rick S., Poor, H. Vincent

“…A correction to this paper has been published: https://doi.org/10.1007/s43926-021-00013-8…”
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Perfect Secrecy Using Compressed Sensing by Mayiami, Mahmoud Ramezani, Seyfe, Babak, Bafghi, Hamid G

“…In this paper we consider the compressed sensing-based encryption and proposed the conditions in which the perfect secrecy is obtained. We prove when the…”
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Robust Graph Topology Learning and Application in Stock Market Inference by Ramezani-Mayiami, Mahmoud, Skretting, Karl

“…In many applications, there are multiple interacting entities, generating time series of data over the space. To describe the relation within the set of data,…”
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Topology Inference and Signal Representation Using Dictionary Learning by Ramezani-Mayiami, Mahmoud, Skretting, Karl

“…This paper presents a Joint Graph Learning and Signal Representation algorithm, called JGLSR, for simultaneous topology learning and graph signal…”
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Joint Graph Learning and Signal Recovery via Kalman Filter for Multivariate Auto-Regressive Processes by Ramezani-Mayiami, Mahmoud, Beferull-Lozano, Baltasar

“…In this paper, an adaptive Kalman filter algorithm is proposed for simultaneous graph topology learning and graph signal recovery from noisy time series. Each…”
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Graph recursive least squares filter for topology inference in causal data processes by Ramezani-Mayiami, Mahmoud, Beferull-Lozano, Baltasar

“…In this paper, we introduce the concept of recursive least squares graph filters for online topology inference in data networks that are modelled as Causal…”
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JOINT TOPOLOGY LEARNING AND GRAPH SIGNAL RECOVERY VIA KALMAN FILTER IN CAUSAL DATA PROCESSES by Ramezani-Mayiami, Mahmoud, Beferull-Lozano, Baltasar

“…In this paper, a joint graph-signal recovery approach is investigated when we have a set of noisy graph signals generated based on a causal graph process. By…”
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Graph Topology Learning and Signal Recovery Via Bayesian Inference by Ramezani-Mayiami, Mahmoud, Hajimirsadeghi, Mohammad, Skretting, Karl, Blum, Rick S., Vincent Poor, H.

“…The estimation of a meaningful affinity graph has become a crucial task for representation of data, since the underlying structure is not readily available in…”
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Nonparametric Sparse Representation by Mayiami, Mahmoud Ramezani, Seyfe, Babak

“…This paper suggests a nonparametric scheme to find the sparse solution of the underdetermined system of linear equations in the presence of unknown impulsive…”
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Opportunistic relaying in ad-hoc networks for throughput improvement by Malekee, Sajjad Kouhkan, Rahimi, E., Ramezani Mayiami, M.

“…In this paper, n mobile source-destination pairs and m relay nodes are considered in the same frequency band. In the previous works, it is assumed that the ad…”
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