K e y w o r d s K o h o n e n feature mapping algorithm, Supermartingale, Global minima, Stochastic differential equation, Vanishing learning rate parameters (VLRPs). 1. I N T R O D U C T I O N In recent years, there are extensive research works devoted to the study of the Kohonen feature mapping algorithm, both theoretically and numerically [1-3]. In [4,5], and references given therein, the au...

This paper examines two vector quantization algorithms which can combine the tasks of compression and classiication: Bayes risk weighted vector quantization (BRVQ) proposed by Oehler et al., and Optimized Learning Vector Quantization 1 (OLVQ1) proposed by Kohonen et al. BRVQ uses a parameter to control the tradeoo between compression and clas-siication. BRVQ performance is studied for a range o...

The Kohonen Self-Organizing Map (SOM) is an unsupervised learning technique for summarizing high-dimensional data so that similar inputs are, in general, mapped close to each other. When applied to textual data, SOM has been shown to be able to group together related concepts in a data collection. This article presents research in which we sought to validate this property of SOM, called the Pro...

Automatic disorders recognition in speech can be very helpful for therapist while monitoring therapy progress of patients with disordered speech. This article is focused on sound repetitions. The signal is analyzed using Continuous Wavelet Transform with 16 bark scales, the result is divided into vectors and passed into Kohonen network. Finally, the Kohonen winning neuron result is put on the 3...

This paper describes and compares three clustering techniques: traditional methods, Kohonen maps latent class models. The also proposes some novel measures of the quality a clustering. To best our knowledge, this is first contribution in literature to compare these techniques context where classes are not known advance.

We calculate analytically the magnification behaviour of a generalized family of self-organizing feature maps inspired by a variant introduced by Kohonen in 1991, denoted here as Winner Relaxing Kohonen algorithm, which is shown here to have a magnification exponent of 4/7. Motivated by the observation that a modification of the learning rule for the winner neuron influences the magnification l...

The traditional approaches of classification are always unfavorable in the description of information distribution. This paper describes the BP neural network approach and the Kohonen neural network approach to the classification of remote sensing images. Two algorithms have their own traits and can be good used in the classification. A qualitative comparison demonstrates that both original ima...