Results 31 to 40 of about 376,317 (337)
Compactification near and on the light front [PDF]
, 1999 We address problems associated with compactification near and on the light front. In perturbative scalar field theory we illustrate and clarify the relationships among three approaches: (1) quantization on a space-like surface close to a light front; (2)
A. Bilal +33 more
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Metrology and Measurement Systems, 2015 This paper deals with the amplitude estimation in the frequency domain of low-level sine waves, i.e. sine waves spanning a small number of quantization steps of an analog-to-digital converter.
Bellan Diego
doaj +1 more source
IEEE Access, 2021 We consider a power constrained downlink communication scenario where energy efficiency, reliability, and latency take precedence over rate, as in some Internet of Things (IoT) applications.
Sherief Helwa, Naofal Al-Dhahir
doaj +1 more source
Succesful renormalization of a QCD-inspired Hamiltonian
, 2003 The long standing problem of non perturbative renormalization of a gauge field theoretical Hamiltonian is addressed and explicitly carried out within an (effective) light-cone Hamiltonian approach to QCD.
Anisovich +8 more
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Computer Vision and Image Understanding, 2011 Vector quantization(VQ) is a lossy data compression technique from signal processing, which is restricted to feature vectors and therefore inapplicable for combinatorial structures. This contribution presents a theoretical foundation of graph quantization (GQ) that extends VQ to the domain of attributed graphs.
Jain, Brijnesh J., Obermayer, Klaus
openaire +2 more sources
About its own time and the mass of the universe
St. Petersburg Polytechnical University Journal: Physics and Mathematics, 2021 A modification of the quantum theory of gravity in the case of a closed universe, in which the dynamics is reduced to the motion in the orbit of a group of general covariance, is proposed.
Gorobey Natalia +2 more
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Generalized residual vector quantization for large scale data
, 2016 Vector quantization is an essential tool for tasks involving large scale data, for example, large scale similarity search, which is crucial for content-based information retrieval and analysis.
Liu, Shicong, Lu, Hongtao, Shao, Junru
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Communication Efficient Federated Learning With Quantization-Aware Training Design
IEEE Transactions on Machine Learning in Communications and NetworkingModel quantization is an effective method that can improve communication efficiency in federated learning (FL). The existing FL quantization protocols almost stay at the level of post-training quantization (PTQ), which comes at the cost of large ...
Xiang Fang +4 more
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Analysis of Application of Cluster Descriptions in Space of Characteristic Image Features
Data, 2018 In this paper, we propose an investigation of the properties of structural image recognition methods in the cluster space of characteristic features. Recognition, which is based on key point descriptors like SIFT (Scale-invariant Feature Transform), SURF
Oleksii Gorokhovatskyi +2 more
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Physical Review Letters, 2012 We propose a method for quantization of Lagrangians for which the Hamiltonian, as a function of momentum, is a branched function with cusps. Appropriate boundary conditions, which we identify, insure unitary time evolution. In special cases a dual (canonical) transformation maps the problem into a problem of quantum mechanics on singular spatial ...
Shapere, Alfred, Wilczek, Frank
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