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Pattern Recognition with Fuzzy Objective Function Algorithms
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Citations
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Journal ArticleDOI
Constructing a fuzzy controller from data
Frank Klawonn,Rudolf Kruse +1 more
TL;DR: This paper discusses how fuzzy clustering techniques can be applied to construct a fuzzy controller from data and introduces special clustering algorithms that are tailored for this problem.
Journal ArticleDOI
Real-time intelligent pattern recognition algorithm for surface EMG signals
Mahdi Khezri,Mehran Jahed +1 more
TL;DR: This study shows that ANFIS real-time learning method coupled with mixed time and time-frequency features as EMG features can provide acceptable results for designing sEMG pattern recognition system suitable for hand prosthesis control.
Journal ArticleDOI
Parametric and non-parametric unsupervised cluster analysis
TL;DR: It is shown that, whilst both methods are capable of determining cluster validity for data sets in which clusters tend towards a multivariate Gaussian distribution, the parametric method inevitably fails for clusters which have a non-Gaussian structure whilst the scale-space method is more robust.
Journal ArticleDOI
Type-2 fuzzy neural networks with fuzzy clustering and differential evolution optimization
Rafik A. Aliev,Witold Pedrycz,B. G. Guirimov,R. R. Aliev,Umit Ilhan,Mustafa Babagil,Sadik Mammadli +6 more
TL;DR: Type-2 fuzzy logic systems developed with the aid of evolutionary optimization forms a useful modeling tool subsequently resulting in a collection of efficient ''If-Then'' rules, which efficiently capture the factor of uncertainty.
Journal ArticleDOI
Allocation of the load profiles to consumers using probabilistic neural networks
TL;DR: A methodology for allocating consumers' load profiles using probabilistic neural network (PNN) is presented, based on the preprocessed measured load profiles (MLPs), clustered with a FCM clustering algorithm with an appropriate cluster-validity measure.
References
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Journal ArticleDOI
Nearest neighbor pattern classification
Thomas M. Cover,Peter E. Hart +1 more
TL;DR: The nearest neighbor decision rule assigns to an unclassified sample point the classification of the nearest of a set of previously classified points, so it may be said that half the classification information in an infinite sample set is contained in the nearest neighbor.
Book
Introduction to Statistical Pattern Recognition
TL;DR: This completely revised second edition presents an introduction to statistical pattern recognition, which is appropriate as a text for introductory courses in pattern recognition and as a reference book for workers in the field.
A fuzzy relative of the isodata process and its use in detecting compact well-separated clusters
TL;DR: In this paper, two fuzzy versions of the k-means optimal, least squared error partitioning problem are formulated for finite subsets X of a general inner product space, and the extremizing solutions are shown to be fixed points of a certain operator T on the class of fuzzy, k-partitions of X, and simple iteration of T provides an algorithm which has the descent property relative to the LSE criterion function.