Comparison of linear, nonlinear, and feature selection methods for EEG signal classification
D Garrett, DA Peterson, CW Anderson… - IEEE Transactions on …, 2003 - ieeexplore.ieee.org
The reliable operation of brain-computer interfaces (BCIs) based on spontaneous
electroencephalogram (EEG) signals requires accurate classification of multichannel EEG …
electroencephalogram (EEG) signals requires accurate classification of multichannel EEG …
[图书][B] The design of innovation: Lessons from and for competent genetic algorithms
DE Goldberg - 2002 - Springer
" It is well known that" building blocks", whether they be the atoms of chemistry, the words of
a language, or the modules of a computer, play a key role in our understanding of the world …
a language, or the modules of a computer, play a key role in our understanding of the world …
[图书][B] The practical handbook of genetic algorithms: applications
LD Chambers - 2000 - taylorfrancis.com
Rapid developments in the field of genetic algorithms along with the popularity of the first
edition precipitated this completely revised, thoroughly updated second edition of The …
edition precipitated this completely revised, thoroughly updated second edition of The …
Evolutionary undersampling for classification with imbalanced datasets: Proposals and taxonomy
Learning with imbalanced data is one of the recent challenges in machine learning. Various
solutions have been proposed in order to find a treatment for this problem, such as …
solutions have been proposed in order to find a treatment for this problem, such as …
Reformulating software engineering as a search problem
Metaheuristic techniques such as genetic algorithms, simulated annealing and tabu search
have found wide application in most areas of engineering. These techniques have also …
have found wide application in most areas of engineering. These techniques have also …
Time-frequency complexity and information
P Flandrin, RG Baraniuk… - Proceedings of ICASSP'94 …, 1994 - ieeexplore.ieee.org
Many functions have been proposed for estimating signal information content and
complexity on the time-frequency plane, including moment-based measures such as the …
complexity on the time-frequency plane, including moment-based measures such as the …
Enhancing the effectiveness and interpretability of decision tree and rule induction classifiers with evolutionary training set selection over imbalanced problems
Classification in imbalanced domains is a recent challenge in data mining. We refer to
imbalanced classification when data presents many examples from one class and few from …
imbalanced classification when data presents many examples from one class and few from …
Search heuristics, case-based reasoning and software project effort prediction
C Kirsopp, MJ Shepperd, J Hart - 2002 - bura.brunel.ac.uk
This paper reports on the use of search techniques to help optimise a case-based reasoning
(CBR) system for predicting software project effort. A major problem, common to ML …
(CBR) system for predicting software project effort. A major problem, common to ML …
Collective data mining from distributed, vertically partitioned feature space
H Kargupta, DE Hershberger, EL Johnson… - US Patent …, 2004 - Google Patents
A system and method for collective data mining from a distributed, vertically partitioned
feature space as described. Collective data mining involves a unique approach for finding …
feature space as described. Collective data mining involves a unique approach for finding …
Feature selection and blind source separation in an EEG-based brain-computer interface
DA Peterson, JN Knight, MJ Kirby… - EURASIP Journal on …, 2005 - Springer
Most EEG-based BCI systems make use of well-studied patterns of brain activity. However,
those systems involve tasks that indirectly map to simple binary commands such as" yes" or" …
those systems involve tasks that indirectly map to simple binary commands such as" yes" or" …