In this paper we provide an in-depth evaluation of the SOM as a feasible tool for nonlinear adaptive filtering. A comprehensive survey of existing SOM-based and related architectures for learning input-output mappings is carried out and the application of these architectures to nonlinear adaptive filtering is formulated. Then, we introduce two simple procedures for building RBF-based nonlinear ...

The kernel method has become a useful trick and has been widely applied to various learning models to extend their nonlinear approximation and classification capabilities. Such extensions have also recently occurred to the Self-Organising Map (SOM). In this paper, two recently proposed kernel SOMs are reviewed, together with their link to an energy function. The Self-Organising Mixture Network ...

Solid phase microextraction (SPME) coupled with gas chromatography was employed to estimate bioavailability of pyrene in soils with different properties of textures, organic matter contents (SOM) and aging periods. Experimental results indicated that biodegradation rates increased from 0.10 (sandy loam) to 0.15 (silty loam) microg g-1 hr1. By contrast, biodegradation rate decreased from 0.10(1....

In this paper, we propose an enhanced parallel Selforganizing Map (SOM) framework based on heterogeneous system platform, specifically Central Processing Unit (CPU) and Graphic Processing Unit (GPU) soldered together on a single chip. The framework is to improve speed of parallel SOM using GPU since processing parallel SOM on GPU burden by communication latency due to isolate device architectur...

A produção de som por instrumentos musicais acústicos é provocada pela vibração de uma estrutura ressonante que pode ser descrita por um sinal correspondente à evolução temporal da vibração associada com a pressão do som. O fato de que o som pode ser caracterizado por um conjunto de sinais, sugere que um dispositivo possa gerar som e, portanto, imitar sons de instrumentos acústicos. Tal disposi...

Cluster structure of gene expression data obtained from DNA microarrays is analyzed and visualized with the Self-Organizing Map (SOM) algorithm. The SOM forms a non-linear mapping of the data to a two-dimensional map grid that can be used as an exploratory data analysis tool for generating hypotheses on the relationships, and ultimately of the function of the genes. Similarity relationships wit...

We propose a neural preprocess approach for video-based gesture recognition system. Second-order neural network (SONN) and self-organizing map (SOM) are employed for extracting moving hand regions and for normalizing motion features respectively. The SONN is more robust to noise than frame difference technique. Obtained velocity feature vectors are translated into normalized feature space by th...

The Self-Organizing Map (SOM) is an artificial neural network model based on unsupervised learning. In this paper, the use of the SOM in natural language processing is considered. The main emphasis is on natural features of natural language including contextuality of interpretation, and the communicative and social aspects of natural language learning and usage. The SOM is introduced as a gener...

Hippocampal theta rhythm arises from a combination of recently described intrinsic theta oscillators and inputs from multiple brain areas. Interneurons expressing the markers parvalbumin (PV) and somatostatin (SOM) are leading candidates to participate in intrinsic rhythm generation and principal cell (PC) coordination in distal CA1 and subiculum. We tested their involvement by optogenetically ...

Soil organic matter (SOM) is an important component of soils, and knowing the spatial distribution and variation of SOM is the premise for sustainably utilizing soils. The objective of this study was to compare geographically weighted regression (GWR) with regression kriging (RK) for estimating the spatial distribution of SOM using field-sample data in SOM and auxiliary data in correlated envir...