Optimization of control parameters for genetic algorithms
IEEE Transactions on Systems, Man and Cybernetics
Digital spectral analysis: with applications
Digital spectral analysis: with applications
Outline for a Logical Theory of Adaptive Systems
Journal of the ACM (JACM)
Autoregression and irregular sampling: spectral estimation
Signal Processing
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Random Data: Analysis and Measurement Procedures
Random Data: Analysis and Measurement Procedures
Automatic Autocorrelation and Spectral Analysis
Automatic Autocorrelation and Spectral Analysis
Genetic algorithm for the personnel assignment problem with multiple objectives
Information Sciences: an International Journal
Automatica (Journal of IFAC)
A new adaptive genetic algorithm for fixed channel assignment
Information Sciences: an International Journal
Population variation in genetic programming
Information Sciences: an International Journal
A hybrid genetic algorithm and bacterial foraging approach for global optimization
Information Sciences: an International Journal
Genetically optimized fuzzy polynomial neural networks with fuzzy set-based polynomial neurons
Information Sciences: an International Journal
Two chi-square statistics for determining the orders p andq of an ARMA (p, q) process
IEEE Transactions on Signal Processing
An optimal instrumental variable method for ARMA spectralestimation
IEEE Transactions on Signal Processing
System parameter estimation with input/output noisy data andmissing measurements
IEEE Transactions on Signal Processing
ARMA model order estimation based on the eigenvalues of thecovariance matrix
IEEE Transactions on Signal Processing
Extension to the maximum entropy method II
IEEE Transactions on Information Theory
Convergence analysis of canonical genetic algorithms
IEEE Transactions on Neural Networks
Chromosome refinement for optimising multiple supply chains
Information Sciences: an International Journal
Journal of Control Science and Engineering
Cross-fuzzy entropy: A new method to test pattern synchrony of bivariate time series
Information Sciences: an International Journal
A decision support approach for assigning reviewers to proposals
Expert Systems with Applications: An International Journal
Information Sciences: an International Journal
Information Sciences: an International Journal
Two-stage DOA estimation for CDMA multipath signals
Information Sciences: an International Journal
Evolutionary spectrum for random field and missing observations
ICISP'12 Proceedings of the 5th international conference on Image and Signal Processing
Modified particle swarm optimization structure approach to direction of arrival estimation
Applied Soft Computing
An adaptive robust fuzzy beamformer for steering vector mismatch and reducing interference and noise
Information Sciences: an International Journal
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This study considers the problem of estimating the autoregressive moving average (ARMA) power spectral density when measurements are corrupted by noise and by missed observations. The missed observations model is based on a probabilistic structure. Unlike conventional cases of missed observation in parameter estimation problems, the variance of noise is unavailable, that is the time points of missed observations are unknown, and the probability of missing data needs to be estimated. In this situation, spectral estimation is more difficult to solve and becomes a highly nonlinear optimization problem with many local minima. In this paper, we use the genetic algorithm (GA) method to achieve a global optimal solution with a fast convergence rate for this spectral estimation problem. From the simulation results, we have determined that the performance is significantly improved if the probability of data loss is considered in the spectral estimation problem.