Adaptation in natural and artificial systems
Adaptation in natural and artificial systems
Characterization of Signals from Multiscale Edges
IEEE Transactions on Pattern Analysis and Machine Intelligence
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Self-organised dynamic recognition states for chaotic neural networks
Information Sciences—Informatics and Computer Science: An International Journal - Special issue on recent advances in soft computing
Homoclinic and heteroclinic orbits in a modified Lorenz system
Information Sciences—Informatics and Computer Science: An International Journal - Special issue: Informatics and computer science intelligent systems applications
Filtering for a class of nonlinear discrete-time stochastic systems with state delays
Journal of Computational and Applied Mathematics
Information Sciences: an International Journal
Self-organizing genetic algorithm based tuning of PID controllers
Information Sciences: an International Journal
A genetic algorithm approach to determine the sample size for attribute control charts
Information Sciences: an International Journal
Information Sciences: an International Journal
Information Sciences: an International Journal
A hybrid genetic algorithm with the Baldwin effect
Information Sciences: an International Journal
Engineering Applications of Artificial Intelligence
A hybrid model based on rough sets theory and genetic algorithms for stock price forecasting
Information Sciences: an International Journal
Associating visual textures with human perceptions using genetic algorithms
Information Sciences: an International Journal
Analytic network process for pattern classification problems using genetic algorithms
Information Sciences: an International Journal
Max-plus algebra-based wavelet transforms and their FPGA implementation for image coding
Information Sciences: an International Journal
Information Sciences: an International Journal
Information Sciences: an International Journal
Adaptive chaotic noise reduction method based on dual-lifting wavelet
Expert Systems with Applications: An International Journal
Center Based Genetic Algorithm and its application to the stiffness equivalence of the aircraft wing
Expert Systems with Applications: An International Journal
Information Sciences: an International Journal
An optimal image watermarking approach based on a multi-objective genetic algorithm
Information Sciences: an International Journal
Information Sciences: an International Journal
Information Sciences: an International Journal
Integration of particle swarm optimization and genetic algorithm for dynamic clustering
Information Sciences: an International Journal
Wavelets and filter banks: theory and design
IEEE Transactions on Signal Processing
Evolutionary programming made faster
IEEE Transactions on Evolutionary Computation
Singularity detection and processing with wavelets
IEEE Transactions on Information Theory - Part 2
De-noising by soft-thresholding
IEEE Transactions on Information Theory
Adaptive wavelet thresholding for image denoising and compression
IEEE Transactions on Image Processing
Finding the minimum number of elements with sum above a threshold
Information Sciences: an International Journal
Joint image denoising using adaptive principal component analysis and self-similarity
Information Sciences: an International Journal
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Time series observed in real world is often nonlinear, even chaotic. However, observed data is often contaminated by noise of various types. To effectively extract desired information from observed data, it is vital to preprocess data to reduce noise for both the analysis of dynamical systems and many potential applications of these systems. In this paper, we present a noise reduction approach to the problem of additive source separation characterized by wide band power spectra when one of the sources is chaotic. The algorithm is based on a Center-Based Genetic Algorithm (CBGA) in lifting wavelet framework, in which the CBGA is used for threshold optimization. This method intelligently adapts itself to various types of noise, and it weighs preservation of dynamics and denoising through Signal-to-Noise Ratio (SNR) and Root-Mean-Square Error (RMSE). Computer simulations show that the approach is very effective in diminishing different kinds of noise, and performs better in terms of visual quality as well as quantitative metrics than existing algorithms.