common spatial pattern (csp) is a method commonly used to enhance the effects of event‑related desynchronization and event‑related synchronization present in multichannel electroencephalogram‑based brain‑computer interface (bci) systems. in the present study, a novel csp sub‑band feature selection has been proposed based on the discriminative information of the features. besides, a distinction ...

We applied a method called Distinction-Sensitive Learning Vector Quantization (DSLVQ) to the classification of footsteps. The measurements were made by a pressure-sensitive floor, which is part of the smart sensing living room in our research laboratory. The aim is to identify walkers based on their single footsteps. DSLVQ is an extended version of Learning Vector Quantization (LVQ), and it can...

Common spatial pattern (CSP) is a method commonly used to enhance the effects of event-related desynchronization and event-related synchronization present in multichannel electroencephalogram-based brain-computer interface (BCI) systems. In the present study, a novel CSP sub-band feature selection has been proposed based on the discriminative information of the features. Besides, a distinction ...

The proposed IAFC neural networks have both stability and plasticity because theyuse a control structure similar to that of the ART-1(Adaptive Resonance Theory) neural network.The unsupervised IAFC neural network is the unsupervised neural network which uses the fuzzyleaky learning rule. This fuzzy leaky learning rule controls the updating amounts by fuzzymembership values. The supervised IAFC ...

Closely related species may be very difficult to distinguish morphologically, yet sometimes morphology is the only reasonable possibility for taxonomic classification. Here we present learning-vector-quantization artificial neural networks as a powerful tool to classify specimens on the basis of geometric morphometric shape measurements. As an example, we trained a neural network to distinguish...

An artiicial neural network vector quantizer is developed for use in data compression applications such as Digital Video. Two techniques are employed to improve the performance of the encoder. First, Diierential Vector Quantization (DVQ) is used to signiicantly improve edge delity. Second, an adaptive ANN algorithm known as Frequency-Sensitive Competitive Learning is used to develop an frequenc...