Leaky LMS algorithm: MSE analysis for Gaussian data
IEEE Transactions on Signal Processing
Nonlinear adaptive prediction of nonstationary signals
IEEE Transactions on Signal Processing
A nonlinear adaptive estimation method based on local approximation
IEEE Transactions on Signal Processing
Unbiased and stable leakage-based adaptive filters
IEEE Transactions on Signal Processing
L∞ constrained high-fidelity image compression via adaptive context modeling
IEEE Transactions on Image Processing
Implementation of artificial intelligence in the time series prediction problem
SMO'06 Proceedings of the 6th WSEAS International Conference on Simulation, Modelling and Optimization
Comparison of artificial intelligence methods for predicting the time series problem
SMO'06 Proceedings of the 6th WSEAS International Conference on Simulation, Modelling and Optimization
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This paper presents a hybrid ADPCM that combines linear and nonlinear predictors, so that the advantages of both predictors can be utilized. This method estimates the linear part of the observed signal by the linear predictor, and then compensates the linear prediction error by the database-based nonlinear predictor. We develop a database update procedure so that the database size is not monotonously increased and nonstationary signals can be treated. The hybrid ADPCM achieves faster processing speed than a single nonlinear ADPCM and better compression performance than a single linear ADPCM and a single nonlinear ADPCM.