Reports on Progress in Physics, ISSN 0034-4885, 02/2012, Volume 75, Issue 2, pp. 022001 - 10

In recent years we have seen the birth of a new field known as Hamiltonian complexity lying at the crossroads between computer science and theoretical physics....

COMPUTATIONAL-COMPLEXITY | VELOCITY | APPROXIMATION | PHYSICS, MULTIDISCIPLINARY | LIEB-ROBINSON BOUNDS | QUANTUM | GAP | PERTURBATION | DYNAMICS | ALGORITHMS | PROPAGATION | Mathematical models | Computer simulation | Theoretical physics | Birth | Complexity

COMPUTATIONAL-COMPLEXITY | VELOCITY | APPROXIMATION | PHYSICS, MULTIDISCIPLINARY | LIEB-ROBINSON BOUNDS | QUANTUM | GAP | PERTURBATION | DYNAMICS | ALGORITHMS | PROPAGATION | Mathematical models | Computer simulation | Theoretical physics | Birth | Complexity

Journal Article

Discrete & Computational Geometry, ISSN 0179-5376, 4/2019, Volume 61, Issue 3, pp. 595 - 625

Given a set S in $$\mathbb {R}^n$$ R n , a $$(\delta ,\varepsilon )$$ ( Î´ , Îµ ) -ball approximation of S is defined as a collection of balls that covers the...

Computational Mathematics and Numerical Analysis | Union of balls | 52C99 | Shape approximation | Morphological erosion and dilation | Covering | Mathematics | Medial axis | 68U05 | Combinatorics | Complexity | MATHEMATICS | COMPUTER SCIENCE, THEORY & METHODS | ALGORITHMS | DISCRETE MEDIAL AXIS | Approximation | Computation | Mathematical analysis | Morphology | Disks | Collection | Erosion | Computer Science | Computational Geometry

Computational Mathematics and Numerical Analysis | Union of balls | 52C99 | Shape approximation | Morphological erosion and dilation | Covering | Mathematics | Medial axis | 68U05 | Combinatorics | Complexity | MATHEMATICS | COMPUTER SCIENCE, THEORY & METHODS | ALGORITHMS | DISCRETE MEDIAL AXIS | Approximation | Computation | Mathematical analysis | Morphology | Disks | Collection | Erosion | Computer Science | Computational Geometry

Journal Article

IEEE Transactions on Communications, ISSN 0090-6778, 08/2005, Volume 53, Issue 8, pp. 1288 - 1299

Various log-likelihood-ratio-based belief-propagation (LLR-BP) decoding algorithms and their reduced-complexity derivatives for low-density parity-check (LDPC)...

Algorithm design and analysis | reduced-complexity decoding | Computational modeling | Quantization | Iterative decoding | Delay | density evolution (DE) | low-density parity-check (LDPC) codes | Belief-propagation (BP) decoding | Approximation algorithms | Parity check codes | Iterative algorithms | Performance analysis | Sum product algorithm | Density evolution (DE) | Reduced-complexity decoding | Low-density parity-check (LDPC) codes | DENSITY EVOLUTION | iterative decoding | PARITY-CHECK CODES | BELIEF PROPAGATION | TELECOMMUNICATIONS | belief-propagation (BP) decoding | ENGINEERING, ELECTRICAL & ELECTRONIC | Iterative methods (Mathematics) | Algorithms | Communication | Codes | Low density parity check codes | Binary system | Approximation | Computation | Mathematical analysis | Decoding | Derivatives | Representations | Density

Algorithm design and analysis | reduced-complexity decoding | Computational modeling | Quantization | Iterative decoding | Delay | density evolution (DE) | low-density parity-check (LDPC) codes | Belief-propagation (BP) decoding | Approximation algorithms | Parity check codes | Iterative algorithms | Performance analysis | Sum product algorithm | Density evolution (DE) | Reduced-complexity decoding | Low-density parity-check (LDPC) codes | DENSITY EVOLUTION | iterative decoding | PARITY-CHECK CODES | BELIEF PROPAGATION | TELECOMMUNICATIONS | belief-propagation (BP) decoding | ENGINEERING, ELECTRICAL & ELECTRONIC | Iterative methods (Mathematics) | Algorithms | Communication | Codes | Low density parity check codes | Binary system | Approximation | Computation | Mathematical analysis | Decoding | Derivatives | Representations | Density

Journal Article

IEEE Transactions on Signal Processing, ISSN 1053-587X, 09/2018, Volume 66, Issue 18, pp. 4957 - 4970

An algorithm for the estimation of multiple targets from partial and corrupted observations is introduced based on the concept of a partially distinguishable...

Target tracking | Multi-target tracking | partial information | Signal processing algorithms | Estimation | Approximation algorithms | Probability distribution | Complexity theory | Indexes | PHD FILTERS | RANDOM FINITE SETS | TRACKING | ENGINEERING, ELECTRICAL & ELECTRONIC | Algorithms | Filtration | Approximation | Tracking (position) | Target detection | Linearization | Complexity

Target tracking | Multi-target tracking | partial information | Signal processing algorithms | Estimation | Approximation algorithms | Probability distribution | Complexity theory | Indexes | PHD FILTERS | RANDOM FINITE SETS | TRACKING | ENGINEERING, ELECTRICAL & ELECTRONIC | Algorithms | Filtration | Approximation | Tracking (position) | Target detection | Linearization | Complexity

Journal Article

Discrete Applied Mathematics, ISSN 0166-218X, 10/2019

Journal Article

IEEE Transactions on Vehicular Technology, ISSN 0018-9545, 10/2015, Volume 64, Issue 10, pp. 4839 - 4845

For uplink large-scale multiple-input-multiple-output (MIMO) systems, the minimum mean square error (MMSE) algorithm is near optimal but involves matrix...

Algorithm design and analysis | minimum mean square error (MMSE) | Gauss-Seidel (GS) method | low complexity | Large-scale MIMO | Approximation algorithms | MIMO | Vectors | Complexity theory | Uplink | Signal detection | signal detection | large-scale multiple-input-multiple-output (MIMO) | DESIGN | TRANSPORTATION SCIENCE & TECHNOLOGY | TELECOMMUNICATIONS | ENGINEERING, ELECTRICAL & ELECTRONIC | Mean square errors | Algorithms | Approximation | Mathematical analysis | Inversions | Mathematical models | Channels | Complexity | Convergence

Algorithm design and analysis | minimum mean square error (MMSE) | Gauss-Seidel (GS) method | low complexity | Large-scale MIMO | Approximation algorithms | MIMO | Vectors | Complexity theory | Uplink | Signal detection | signal detection | large-scale multiple-input-multiple-output (MIMO) | DESIGN | TRANSPORTATION SCIENCE & TECHNOLOGY | TELECOMMUNICATIONS | ENGINEERING, ELECTRICAL & ELECTRONIC | Mean square errors | Algorithms | Approximation | Mathematical analysis | Inversions | Mathematical models | Channels | Complexity | Convergence

Journal Article

7.
Full Text
Average-Case Complexity Versus Approximate Simulation of Commuting Quantum Computations

Physical Review Letters, ISSN 0031-9007, 08/2016, Volume 117, Issue 8, p. 080501

We use the class of commuting quantum computations known as IQP (instantaneous quantum polynomial time) to strengthen the conjecture that quantum computers are...

ALGORITHMS | HARDNESS | MODELS | PHYSICS, MULTIDISCIPLINARY | PERMANENT | GRAPHS | Approximation | Computer simulation | Computation | Constants | Polynomials | Sampling | Hardness | Complexity

ALGORITHMS | HARDNESS | MODELS | PHYSICS, MULTIDISCIPLINARY | PERMANENT | GRAPHS | Approximation | Computer simulation | Computation | Constants | Polynomials | Sampling | Hardness | Complexity

Journal Article

IEEE Transactions on Signal Processing, ISSN 1053-587X, 01/2018, Volume 66, Issue 2, pp. 294 - 308

In this paper, we present an algorithm for the sparse signal recovery problem that incorporates damped Gaussian generalized approximate message passing (GGAMP)...

sparse Bayesian learning (SBL) | expectation-maximization algorithms | Complexity theory | Sparse matrices | Convergence | Gaussian scale mixture | approximate message passing (AMP) | Signal processing algorithms | Approximation algorithms | Robustness | Bayes methods | Compressed sensing | multiple measurement vectors (MMV) | Approximate message passing (AMP) | Expectation-maximization algorithms | Sparse Bayesian learning (SBL) | Multiple measurement vectors (MMV) | SIGNAL RECOVERY | GRAPHS | ENGINEERING, ELECTRICAL & ELECTRONIC | Signal processing | Algorithms | Research | Artificial intelligence

sparse Bayesian learning (SBL) | expectation-maximization algorithms | Complexity theory | Sparse matrices | Convergence | Gaussian scale mixture | approximate message passing (AMP) | Signal processing algorithms | Approximation algorithms | Robustness | Bayes methods | Compressed sensing | multiple measurement vectors (MMV) | Approximate message passing (AMP) | Expectation-maximization algorithms | Sparse Bayesian learning (SBL) | Multiple measurement vectors (MMV) | SIGNAL RECOVERY | GRAPHS | ENGINEERING, ELECTRICAL & ELECTRONIC | Signal processing | Algorithms | Research | Artificial intelligence

Journal Article

Theoretical Computer Science, ISSN 0304-3975, 2011, Volume 412, Issue 12, pp. 1054 - 1065

Reconfiguration problems arise when we wish to find a step-by-step transformation between two feasible solutions of a problem such that all intermediate...

PSPACE-complete | Approximation | Reachability on solution space | Graph algorithm | COMPUTER SCIENCE, THEORY & METHODS | Mathematical models | Transformations | Complexity | Reconfiguration

PSPACE-complete | Approximation | Reachability on solution space | Graph algorithm | COMPUTER SCIENCE, THEORY & METHODS | Mathematical models | Transformations | Complexity | Reconfiguration

Journal Article

Journal of the Royal Statistical Society. Series B (Statistical Methodology), ISSN 1369-7412, 1/2002, Volume 64, Issue 4, pp. 583 - 639

We consider the problem of comparing complex hierarchical models in which the number of parameters is not clearly defined. Using an information theoretic...

Approximation | Sample size | Multilevel models | Predictive modeling | Bayesian networks | Parameterization | Parametric models | Modeling | Spatial models | Estimators | Bayesian model comparison | Effective number of parameters | Decision theory | Leverage | Markov chain Monte Carlo methods | Model dimension | Hierarchical models | Deviance information criterion | Information theory | leverage | decision theory | effective number of parameters | MIXED MODELS | deviance information criterion | Markov | REGRESSION-MODELS | STATISTICS & PROBABILITY | LONGITUDINAL DATA | INFERENCE | GENERALIZED LINEAR-MODELS | model dimension | CHOICE | hierarchical models | information theory | chain Monte Carlo methods | SELECTION | INFORMATION CRITERION | LIKELIHOOD | DIAGNOSTICS

Approximation | Sample size | Multilevel models | Predictive modeling | Bayesian networks | Parameterization | Parametric models | Modeling | Spatial models | Estimators | Bayesian model comparison | Effective number of parameters | Decision theory | Leverage | Markov chain Monte Carlo methods | Model dimension | Hierarchical models | Deviance information criterion | Information theory | leverage | decision theory | effective number of parameters | MIXED MODELS | deviance information criterion | Markov | REGRESSION-MODELS | STATISTICS & PROBABILITY | LONGITUDINAL DATA | INFERENCE | GENERALIZED LINEAR-MODELS | model dimension | CHOICE | hierarchical models | information theory | chain Monte Carlo methods | SELECTION | INFORMATION CRITERION | LIKELIHOOD | DIAGNOSTICS

Journal Article

Communications in Mathematical Physics, ISSN 0010-3616, 12/2017, Volume 356, Issue 2, pp. 451 - 500

We give a quasi-polynomial time classical algorithm for estimating the ground state energy and for computing low energy states of quantum impurity models. Such...

Quantum Physics | Mathematical Physics | Classical and Quantum Gravitation, Relativity Theory | Theoretical, Mathematical and Computational Physics | Complex Systems | Physics | ISING-MODEL | RESISTANCE | GROUND-STATE | PHYSICS, MATHEMATICAL | ALGORITHM | Analysis | Algorithms

Quantum Physics | Mathematical Physics | Classical and Quantum Gravitation, Relativity Theory | Theoretical, Mathematical and Computational Physics | Complex Systems | Physics | ISING-MODEL | RESISTANCE | GROUND-STATE | PHYSICS, MATHEMATICAL | ALGORITHM | Analysis | Algorithms

Journal Article

2010, ISBN 0521122546, Volume 9780521192484, xxix, 184

"The focus of this book is the P-versus-NP Question and the theory of NP-completeness. It also provides adequate preliminaries regarding computational problems...

Approximation theory | Polynomials | Computer algorithms | Computational complexity

Approximation theory | Polynomials | Computer algorithms | Computational complexity

Book

Automatica, ISSN 0005-1098, 04/2014, Volume 50, Issue 4, pp. 1217 - 1226

A universal, approximation-free state feedback control scheme is designed for unknown pure feedback systems, capable of guaranteeing, for any initial system...

Nonaffine systems | Uncertain systems | Low-complexity | Prescribed performance | Global approximation-free control | TRANSIENT-BEHAVIOR | UNCERTAIN NONLINEAR-SYSTEMS | NETWORK CONTROL | ENGINEERING, ELECTRICAL & ELECTRONIC | TRACKING CONTROL | AFFINE | FUZZY CONTROL | AUTOMATION & CONTROL SYSTEMS | ADAPTIVE NEURAL-CONTROL | Control systems | Analysis | State feedback | Automation | Approximation | Feedback | Feedback control | Control theory | Complexity

Nonaffine systems | Uncertain systems | Low-complexity | Prescribed performance | Global approximation-free control | TRANSIENT-BEHAVIOR | UNCERTAIN NONLINEAR-SYSTEMS | NETWORK CONTROL | ENGINEERING, ELECTRICAL & ELECTRONIC | TRACKING CONTROL | AFFINE | FUZZY CONTROL | AUTOMATION & CONTROL SYSTEMS | ADAPTIVE NEURAL-CONTROL | Control systems | Analysis | State feedback | Automation | Approximation | Feedback | Feedback control | Control theory | Complexity

Journal Article