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检索条件"主题词=Iterative algorithms"

共 16587 条记录，以下是381-390 订阅

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iterative joint and interference nulling/cancellation decoding algorithms for multigroup space time trellis coded systems

Iterative joint and interference nulling/cancellation decodi...

引用

IEEE Conference on Wireless Communications and Networking

作者： S.N. Al-Ghadhban B.D. Woemer Mobile and Portable Radio Research Group Virginia Polytechnic Institute and State University Blacksburg VA USA Virginia Polytechnic Institute and State University Blacksburg VA US Mobile & Portable Radio Res. Group Virginia Polytech. Inst. & State Univ. USA

In this paper, we will propose and evaluate the performance of several decoding algorithms for multigroup space time trellis coded (MGSTTC) systems. By considering a single user who transmits simultaneously through K parallel space time trellis encoders, the system can provide high spectral efficiencies; transmit diversity advantages and coding gains. The system is analogous to synchronous multiusers each is transmitting a space time trellis code. The transmitter will divide the information stream and transmits from each encoder (called a group) simultaneously resulting in an increase in the transmitted data rates. The receiver will apply some multiuser detection (MUD) algorithms to detect and decode each group. The paper will focus on joint detection and interference nulling/cancellation algorithms.

关键词： Interference cancellation iterative decoding iterative algorithms Maximum likelihood decoding MIMO Transmitting antennas Multiuser detection Receiving antennas Diversity reception Signal processing algorithms

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Adaptive reduced-rank constrained constant modulus beamforming algorithms based on joint iterative optimization of filters

Adaptive reduced-rank constrained constant modulus beamformi...

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IEEE/SP Workshop on Statistical Signal Processing (SSP)

作者： Lei Wang Rodrigo C. de Lamare Communications Research Group Department of Electronics University of York UK

This paper proposes a robust reduced-rank scheme and algorithms for adaptive beamforming based on joint iterative optimization (JIO) of adaptive filters. The scheme provides an efficient way to deal with filters with large number of elements. It consists of a bank of full-rank adaptive filters that forms a transformation matrix and an adaptive reduced-rank filter that operates at the output of the bank of filters. The transformation matrix projects the received vector onto a low-dimension vector, which is processed by the reduced-rank filter to estimate the desired signal. The expressions of the transformation matrix and the reduced-rank weight vector are derived according to the constrained constant modulus (CCM) criterion subject to different constraints. Two low-complexity adaptive algorithms are devised for the implementation of the proposed scheme with different constraints. Simulations are performed to show superior performance of the proposed algorithms in comparison with the existing methods.

关键词： Array signal processing iterative algorithms Constraint optimization Adaptive filters Signal processing algorithms Adaptive algorithm Wiener filter Sensor arrays Robustness Filter bank

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Performance evaluation of load balancing algorithms for parallel single-phase iterative PDE solvers

Performance evaluation of load balancing algorithms for para...

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Scalable High Performance Computing Conference

作者： N. Chrisochoides N. Mansour G. Fox Northeast Parallel Architectures Center Syracuse University Syracuse NY USA

We review and evaluate the performances of six data mapping algorithms used for parallel single-phase iterative PDE solvers with irregular 2-dimensional meshes on multicomputers. We provide a table that compares the six algorithms for eight measures covering load balance, interprocessor communication, flexibility, ease of use and speed. Based on the comparison results, we recommend the use of the simplest and fastest (P/spl times/Q) of the six algorithms considered for sequential compile-time mapping of 2-dimensional meshes.< >

关键词： Load management iterative algorithms Partitioning algorithms Equations Linear systems Performance evaluation Data structures Geometry Neural networks Simulated annealing

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algorithms for iterative learning control of nonlinear plants employing time-variant system descriptions

Algorithms for iterative learning control of nonlinear plant...

引用

IEEE Conference on Control Technology and Applications (CCTA)

作者： H. Hengen S. Hillenbrand M. Pandit Control and Signal Processing Group University of Kaiserslautern Kaiserslautern Germany

Deals with the design of iterative learning controllers (ILC) based on extended state space models for nonlinear cyclic process control. In order to design a suitable learning operator, knowledge about the plant's dynamical behaviour is needed which implies that a system model has to be set up. It is expedient to acquire a state space model of the plant using identification methods. Here we deal especially with the case, that a linear model represents system dynamics inadequately. We start with a nonlinear model and linearize the system along the current trajectory, thus obtaining a linear time variant model. Using this as the basis, we develop methods for identification and control of the nonlinear process. Experimental results show that a good system model is also useful to perform a pre-training for the ILC; this is especially interesting in case large deviations from a desired system output trajectory must be avoided. The presented algorithms have been implemented and tested experimentally with a real-life nonlinear processing plant.

关键词： iterative algorithms Nonlinear control systems Control systems State-space methods Signal processing algorithms Sampling methods Error correction Equations Process control Nonlinear dynamical systems

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New cost metrics for iterative task assignment algorithms in heterogeneous computing systems

New cost metrics for iterative task assignment algorithms in...

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Heterogeneous Computing Workshop

作者： R.D. Venkataramana N. Ranganathan Department of Computer Science and Engineering University of South Florida Tampa FL USA

Task assignment and scheduling algorithms for heterogeneous computing systems can be classified as iterative and non-iterative techniques, and are designed to optimize a specific cost function defined on the system. The quality of the solutions generated is controlled by the nature of this cost metric. The common metrics that are used include minimizing the overall execution time or minimizing the load on the maximum loaded processor. In this work, a new set of cost metrics have been proposed that can be used by iterative task assignment algorithms. These metrics exploit the fact that in iterative algorithms the mapping of the subtasks to the processors is known at every iteration. They reflect the actual scheduling cost of the application, thereby improving the quality of the solutions generated by the algorithm. The proposed metrics are evaluated using a learning automata based iterative algorithm. Observations are made regarding the nature of the metrics from the results obtained.

关键词： iterative algorithms Cost function Processor scheduling Electrical capacitance tomography High performance computing Minimization methods Computer science Automata Read only memory Heuristic algorithms

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iterative-batch and sequential algorithms for single microphone speech enhancement

Iterative-batch and sequential algorithms for single microph...

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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： S. Gannot D. Burshtein E. Weinstein Dept. of Electrical Engineering-Systems Tel-Aviv University Tel-Aviv Israel

Speech quality and intelligibility might significantly deteriorate in the presence of background noise, especially when the speech signal is subject to subsequent processing. In this paper we represent a class of Kalman-filter based speech enhancement algorithms with some extensions, modifications, and improvements. The first algorithm employs the estimate-maximize (EM) method to iteratively estimate the spectral parameters of the speech and noise parameters. The enhanced speech signal is obtained as a by-product of the parameter estimation algorithm. The second algorithm is a sequential, computationally efficient, gradient descent algorithm. We discuss various topics concerning the practical implementation of these algorithms. Experimental study, using real speech and noise signals is provided to compare these algorithms with alternative speech enhancement algorithms, and to compare the performance of the iterative and sequential algorithms.

关键词： iterative algorithms Microphones Speech enhancement Wiener filter Speech processing Parameter estimation Kalman filters Equations Maximum likelihood estimation Yield estimation

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Creating Streaming iterative Soft Clustering algorithms

Creating Streaming Iterative Soft Clustering Algorithms

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Conference of the North American Fuzzy Information Processing Society - NAFIPS

作者： Prodip Hore Lawrence O. Hall Dmitry B. Goldgof Department of Computer Science and Engineering University of South Florida Tampa FL USA

There are an increasing number of large labeled and unlabeled data sets available. Clustering algorithms are the best suited for helping one make sense out of unlabeled data. However, scaling iterative clustering algorithms to large amounts of data has been a challenge. The computation time can be very great and for data sets that will not fit in even the largest memory, only carefully chosen subsets of data can be practically clustered. We present a general approach which enables iterative fuzzy/possibilistic clustering algorithms to be turned into algorithms that can handle arbitrary amounts of streaming data. The computation time is also reduced for very large data sets while the results of clustering will be very similar to clustering with all the data, if that was possible. We introduce transformed equations for fuzzy-C-means, possibilistic C-means, the Gustafson-Kessel algorithm and show the excellent performance with a streaming fuzzy C-means implementation. The resulting clusters are both sensible and for comparable data sets (those that fit in memory) almost identical to those obtained with the original clustering algorithm.

关键词： Clustering algorithms iterative algorithms Partitioning algorithms Equations Sampling methods Computer science iterative methods Fuzzy sets Labeling Wrapping

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Blind Adaptive Successive Interference Cancellation using Code-Constrained Constant Modulus algorithms and iterative Detection in Multipath Channels

Blind Adaptive Successive Interference Cancellation using Co...

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Asilomar Conference on Signals, Systems & Computers

作者： R.C. de Lamare R. Sampaio-Neto Communications Research Group Department of Electronics University of York York UK CETUC/PUC-RIO Rio de Janeiro Brazil

In this work we propose blind adaptive successive interference cancellation (SIC) receivers with iterative detection for direct sequence code division multiple access (DS-CDMA) systems in frequency selective channels. A code-constrained constant modulus (CCM) design criterion based on constrained optimization techniques is proposed for SIC detectors in scenarios subject to multipath and computationally efficient blind adaptive stochastic gradient (SG) and recursive least squares (RLS) algorithms are described for estimating the parameters of SIC detectors. A novel iterative detection scheme that generates different cancellation orders and selects the most likely symbol estimate on the basis of the instantaneous minimum constant modulus (CM) criterion is also proposed. Simulation results for an uplink scenario assess the algorithms, the proposed blind adaptive SIC detectors against existing receivers and evaluate the effects of error propagation of the new cancellations techniques

关键词： Interference cancellation iterative algorithms Multipath channels Silicon carbide Detectors Direct-sequence code-division multiple access Multiaccess communication Frequency conversion Algorithm design and analysis Interference constraints

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Convergence behavior of iterative turbo multiuser detection algorithms

Convergence behavior of iterative turbo multiuser detection ...

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IEEE Conference on Wireless Communications and Networking

作者： M.H. Moghari B. Shahrrava Department of Electrical and Computer Engineering University of Windsor Windsor ONT Canada

Mutual information transfer characteristics of soft-in/soft-out decoders have been used recently for studying the convergence behavior of iterative decoding algorithms. The swapping function of the extrinsic information is pictured as a decoding trajectory in the extrinsic information transfer (EXIT) chart. EXIT chart is a powerful tool for estimating the convergence and bit error rate of iterative decoding algorithms. We study the convergence behavior of turbo multiuser detection, and also of the group blind multiuser detection algorithm proposed recently, using the EXIT chart method. The influence of the different code memory lengths, code polynomials and cross correlation matrixes on the convergence behavior of the turbo multiuser detection algorithm are studied as well. Finally, the sensitivity of the turbo multiuser decoding algorithm to the signal-to-noise ratio mismatch at the receiver, is investigated by means of the EXIT chart.

关键词： Convergence Multiuser detection iterative algorithms iterative decoding Detectors Mutual information Signal to noise ratio Bit error rate Estimation error Convolutional codes

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Parallel iterative image restoration algorithms

Parallel iterative image restoration algorithms

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Midwest Symposium on Circuits and Systems (MWSCAS)

作者： J.K. Paik A.K. Katsaggelos Department of Electrical Engineering and Computer Science The Technological Institute Northwestern University Evanston IL USA

Three parallel iterative image restoration algorithms with and without preconditioning are proposed and analyzed. The first algorithm corresponds to a coarse-grained general-purpose multiprocessor computer, the second to a massively parallel computer with synchronization, and the third to a massively parallel computer without synchronization. It is shown that the second and third algorithms can give a speed-up proportional to the number of processors when proper assumptions are satisfied, while the first one performs the best when simulated by a uniprocessor computer.< >

关键词： Image restoration iterative algorithms Concurrent computing Wiener filter Filtering iterative methods Synchronization Least squares methods Degradation Signal restoration

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