Results 21 to 30 of about 167,226 (306)
Optimal channels for channelized quadratic estimators
Journal of the Optical Society of America A, 2016 We present a new method for computing optimized channels for estimation tasks that is feasible for high-dimensional image data. Maximum-likelihood (ML) parameter estimates are challenging to compute from high-dimensional likelihoods. The dimensionality reduction from M measurements to L channels is a critical advantage of channelized quadratic ...
Meredith K, Kupinski, Eric, Clarkson
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Energy-Efficient Channel Estimation
IEEE Access, 2020 We investigate the energy-efficient channel estimation in wireless networks, where one pilot is inserted for every several data slots to estimate the channel coefficients. Both the channel state information estimation error and the time-varying model are
Guandong Wei +5 more
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Fast Sparse Bayesian Learning-Based Channel Estimation for Underwater Acoustic OFDM Systems
Applied Sciences, 2022 Harsh underwater channels and energy constraints are the two critical issues of underwater acoustic (UWA) communications. To achieve a high channel estimation performance under a severe underwater channel, sparse Bayesian learning (SBL)-based channel ...
Yong-Ho Cho
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Channel estimation with noisy entanglement [PDF]
Physics Letters A, 2001 We analyze the Pauli-channel estimation with mixed nonseparable states. It turns out that within a specific range entanglement can serve as a nonclassical resource. However, this range is rather small, that is entanglement is not very robust for this application.
Bschorr, Thorsten C. +2 more
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Efficient Estimation of Pauli Channels [PDF]
ACM Transactions on Quantum Computing, 2020 Pauli channels are ubiquitous in quantum information, both as a dominant noise source in many computing architectures and as a practical model for analyzing error correction and fault tolerance. Here, we prove several results on efficiently learning Pauli channels and more generally the Pauli projection of a quantum channel.
Flammia, Steven T., Wallman, Joel J.
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Pilot design for underwater MIMO cosparse channel estimation based on compressed sensing
International Journal of Distributed Sensor Networks, 2021 In multiple-input multiple-output–orthogonal frequency-division multiplexing underwater acoustic communication systems, the correlation of the sampling matrix is the key of the channel estimation algorithm based on compressed sensing. To reduce the cross-
Yun Li +4 more
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Distributed estimation over parallel fading channels with channel estimation error
2008 IEEE International Conference on Acoustics, Speech and Signal Processing, 2008 We consider distributed estimation of a source observed by sensors in additive Gaussian noise, where the sensors are connected to a fusion center with unknown orthogonal (parallel) flat Rayleigh fading channels. We adopt a two-phase approach of (i) channel estimation with training, and (ii) source estimation given the channel estimates, where the total
Senol, Habib, Tepedelenlioglu, Cihan
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Unitarity Estimation for Quantum Channels
IEEE Transactions on Information Theory, 2023 Estimating the unitarity of an unknown quantum channel $\mathcal{E}$ provides information on how much it is unitary, which is a basic and important problem in quantum device certification and benchmarking. Unitarity estimation can be performed with either coherent or incoherent access, where the former in general leads to better query complexity while ...
Kean Chen +3 more
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Distributed Estimation with Channel Estimation Error over Orthogonal Fading Channels
2007 Conference Record of the Forty-First Asilomar Conference on Signals, Systems and Computers, 2007 We study distributed estimation of a source corrupted by an additive Gaussian noise and observed by sensors which are connected to a fusion center with unknown orthogonal (parallel) flat Rayleigh fading channels. The fading communication channels are estimated with training.
Şenol, Habib, Tepedelenlioğlu, Cihan
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Learning the MMSE Channel Estimator [PDF]
IEEE Transactions on Signal Processing, 2018 To appear in IEEE Transactions on Signal ...
David Neumann +2 more
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